Mary Meeker
May 31, 2017
kpcb.com/InternetTrends
INTERNET TRENDS 2017
CODE CONFERENCE
KP INTERNET TRENDS 2017 | PAGE 2
Internet Trends 2017
1) Global Internet Trends = SolidSlowing Smartphone Growth
4-9
2) Online Advertising (+ Commerce) = Increasingly Measurable + Actionable
10-79
3)
Interactive Games = Motherlode of Tech Product Innovation + Modern Learning
80-150
4) Media = Distribution Disruption @ Torrid Pace
151-177
5) The Cloud = Accelerating Change Across Enterprises
178-192
6) China Internet = Golden Age of Entertainment + Transportation
193-231
(Provided by Hillhouse Capital)
7)
India Internet = Competition Continues to IntensifyConsumers Winning
232-287
8) Healthcare @ Digital Inflection Point
288-319
9) Global Public / Private Internet Companies
320-333
10) Some Macro Thoughts
334-351
11) Closing Thoughts
352-353
KP INTERNET TRENDS 2017 | PAGE 3
Thanks...
Kleiner Perkins Partners
Alexander Krey & Ansel Parikh - who were fearless and sometimes sleepless - helped
steer the ideas / presentation we hope you find useful / learn from / improve on. Key
contributors to specific content include: Noah Knauf & Nina Lu (Healthcare), Bing Gordon
(Interactive Games), Alex Tran & Anjney Midha (India), Daegwon Chae (Ads +
Commerce) and Alex Kurland & Lucas Swisher (Enterprise). In addition, Mood Rowghani,
Eric Feng, Daniel Axelsen, Dino Becirovic and Shabih Rizvi were more than on call with
help.
Hillhouse Capital
Especially Liang Wuhis / their contribution of the China sector of Internet Trends
provides an especially thoughtful overview of the largest market of Internet users in the
world
Participants in Evolution of Internet Connectivity
From creators to consumers who keep us on our toes 24x7...and the people who directly
help us prepare this presentation...
Kara & Walt
For continuing to do what you do so well...
KP INTERNET TRENDS 2017 | PAGE 4
GLOBAL INTERNET TRENDS =
SOLID USER GROWTH
SLOWING SMARTPHONE GROWTH
KP INTERNET TRENDS 2017 | PAGE 5
Global Internet Trends =
Solid User GrowthSlowing Smartphone Growth
1) Global Internet Users = 3.4BFlat Growth +10% vs. 10% Y/Y
+8% vs. 8% Y/Y (ex. India)
2) Global Smartphone Shipments = Slowing +3% vs. +10% Y/Y
3) Global Smartphone Installed Base = Slowing +12% vs. +25% Y/Y
4) USA Internet Usage (Engagement) = Solid +4% Y/Y
KP INTERNET TRENDS 2017 | PAGE 6
Source: United Nations / International Telecommunications Union, US Census Bureau. Internet user data is as of mid-year. Internet user data for:
USA from Pew Research, China from CNNIC, Iran from Islamic Republic News Agency / InternetWorldStats / KPCB estimates, India from KPCB
estimates based on IAMAI data, Indonesia from APJII.
Global Internet Users = 3.4B @ 46% Penetration...
+10% Y/Y vs. +10%...+8% Y/Y vs. +8% (Ex-India)
0%
5%
10%
15%
20%
25%
30%
35%
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
2009
2010
2011
2012
2013
2014
2015
2016
Y/Y % GrowthGlobal Internet Users (MM)Global Internet Users (MM)
Y/Y Growth (%)
Global Internet Users (MM), 2009 2016
KP INTERNET TRENDS 2017 | PAGE 7
Global Smartphone Unit Shipments = Continue to Slow...
@ +3% Y/Y vs. +10% (2015) / +28% (2014)
Source: Morgan Stanley Research (5/17)
Smartphone Unit Shipments by Operating System (MM), Global, 2009 2016
0%
20%
40%
60%
80%
100%
0
300
600
900
1,200
1,500
2009
2010
2011
2012
2013
2014
2015
2016
Y/Y Growth (%)Global Smartphone Unit Shipments (MM)Android
iOS
Other
Y/Y Growth
KP INTERNET TRENDS 2017 | PAGE 8
Source: Morgan Stanley Research (5/17)
Note: Owing to use of different source, prior period data may have slight adjustments vs prior reports. Smartphone installed base based on
preceding 8 quarters of smartphone shipments.
Global Smartphone Installed Base = 2.8B
+12% Y/Y vs. +25% (2015) / +37% (2014)
0%
10%
20%
30%
40%
50%
60%
70%
0
500
1,000
1,500
2,000
2,500
3,000
3,500
2009
2010
2011
2012
2013
2014
2015
2016
Y/Y % GrowthGlobal Smartphone Installed Base (MM)Global Smartphone Installed Base (MM)
Y/Y Growth (%)
Global Smartphone Installed Base (MM), 2009 2016
KP INTERNET TRENDS 2017 | PAGE 9
Internet Usage (Engagement) = Solid Growth+4% Y/Y
Mobile >3 Hours / Day per User vs. <1 Five Years Ago, USA
Source: eMarketer 9/14 (2008-2010), eMarketer 4/15 (2011-2013), eMarketer 4/17 (2014-2016). Note: Other connected devices include OTT and
game consoles. Mobile includes smartphone and tablet. Usage includes both home and work. Ages 18+; time spent with each medium includes
all time spent with that medium, regardless of multitasking.
Time Spent per Adult User per Day with Digital Media, USA,
2008 2016
0.2
0.3
0.4
0.3
0.3
0.3
0.3
0.4
0.4
2.2
2.3
2.4
2.6
2.5
2.3
2.2
2.2
2.2
0.3
0.3
0.4
0.8
1.6
2.3
2.6
2.8
3.1
2.7
3.0
3.2
3.7
4.3
4.9
5.1
5.4
5.6
0
1
2
3
4
5
6
2008
2009
2010
2011
2012
2013
2014
2015
2016
Hours per DayOther Connected Devices
Desktop / Laptop
Mobile
KP INTERNET TRENDS 2017 | PAGE 10
ONLINE ADVERTISING (+ COMMERCE) =
INCREASINGLY
MEASURABLE + ACTIONABLE
KP INTERNET TRENDS 2017 | PAGE 11
Ad Growth =
Driven by Mobile
KP INTERNET TRENDS 2017 | PAGE 12
Online Advertising = Growth Accelerating, +22% vs. +20% Y/Y...
Mobile $ > Desktop (2016) on Higher Growth, USA
Source: IAB / PWC Internet Advertising Report (2016)
USA Internet Advertising ($B), 2009 2016
$23
$26
$32
$37
$43
$50
$60
$73
0%
5%
10%
15%
20%
25%
30%
35%
40%
$0
$10
$20
$30
$40
$50
$60
$70
$80
2009
2010
2011
2012
2013
2014
2015
2016
% Y/Y GrowthUSA Internet Advertising ($B)Desktop Advertising
Mobile Advertising
Y/Y Growth
KP INTERNET TRENDS 2017 | PAGE 13
Advertising $ =
Shift to Usage (Mobile) Continues
% of Time Spent in Media vs. % of Advertising Spending, USA, 2016
4%
9%
38%
20%
28%
12%
9%
38%
20%
21%
0%
10%
20%
30%
40%
50%
Print
Radio
TV
Internet
Mobile
% of Total Media Consumption Timeor Advertising SpendingTime Spent
Ad Spend
Total
Internet Ad
= $73B
Of Which
Mobile Ad
= $37B
~$16B
Opportunity
in USA
Source: Internet and Mobile advertising spend based on IAB and PwC data for full year 2016. Print, Radio, and TV advertising spend based on
Magna Global estimates for full year 2016. Print includes newspaper and magazine. Internet (IAB) includes desktop + laptop + other connected
devices. ~$16B opportunity calculated assuming Mobile (IAB) ad spend share equal its respective time spent share. Time spent share data
based on eMarketer (4/17). Arrows denote Y/Y shift in percent share. Excludes out-of-home, video game, and cinema advertising.
KP INTERNET TRENDS 2017 | PAGE 14
Advertising $ =
Internet > TV Within 6 Months, Global
Internet vs. TV Ad Spend ($B), Global, 1995-2017E
$0
$50
$100
$150
$200
$250
Global Advertising Spend ($B)Global Internet Ad Spend
Global TV Ad Spend
Source: Zenith Advertising Expenditure Forecasts (3/17)
KP INTERNET TRENDS 2017 | PAGE 15
$
$5
$10
$15
$20
$25
$30
$35
$40
$45
$50
USA Advertising Revenue ($B)$0
$5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
Google + Facebook =
85% (& Rising) Share of Internet Advertising Growth, USA
Advertising Revenue ($B) and Growth Rates (%) of
Google vs. Facebook vs. Other, USA, 2015 2016
2015
2016
2015
2016
2015
2016
Google
Facebook
Others
+20% Y/Y
+62% Y/Y
+9% Y/Y
Source: IAB / PWC Advertising Report (2016), Facebook, Morgan Stanley Research
Note: Facebook revenue includes Canada. Google USA ad revenue per Morgan Stanley estimates as company only discloses total ad revenue
and total USA revenue. "Others" includes all other USA internet (mobile + desktop) advertising revenue ex-Google / Facebook.
KP INTERNET TRENDS 2017 | PAGE 16
Ad Measurability =
Can Be Triple-Edged
When Things Are Measured =
People Don't Always Like What They See
Users Don't Always Like Data Collected
KP INTERNET TRENDS 2017 | PAGE 17
56%
21%
15%
0%
10%
20%
30%
40%
50%
60%
70%
Engagement Conversion
& Revenue
Amplification
& Brand
Awareness
% of RespondentsAdvertisers = Like Measurable Engagement Metrics But
Some Find Measuring ROI Challenging (as with Offline)
Social Advertisers
Metrics Used to Measure Success, 6/16
Social Media Marketing
Top Challenges, 6/16
61%
38%
34%
0%
10%
20%
30%
40%
50%
60%
70%
Measuring
ROI
Securing
Budget &
Resources
Tying Social
Campaigns
to Business
Goals
% of RespondentsSource: SimplyMeasured State of Social Marketing Annual Report (6/16)
Note: Based on a survey of social media advertisers, n=350.
KP INTERNET TRENDS 2017 | PAGE 18
Ad Blocking = Growth ContinuesEspecially in Developing Markets
Users Increasingly Opt Out of Stuff They Don't Want
0
100
200
300
400
2009 2010 2011 2012 2013 2014 2015 2016
Global AdblockingUsers (MM)Desktop Adblocking Software Users
Mobile Adblocking Browser Users
Adblocking Users on Web
(Mobile + Desktop), Global, 4/09 12/16
Adblocking Penetration
(Mobile + Desktop), Selected
Countries, 12/16
Country
Desktop
Mobile
China
1%
13%
India
1%
28%
USA
18%
1%
Brazil
6%
1%
Japan
3%
--
Russia
6%
3%
Germany
28%
1%
Indonesia
8%
58%
UK
16%
1%
France
11%
1%
Canada
24%
--
Source: PageFair 2015, 2017 reports. These two data sets have not been de-duplicated. The number of desktop adblockers after 1/16 are estimates based on the
observed trend in desktop adblocking and provided by PageFair. Note that mobile adblocking refers to web / browser-based adblocking and not in-app adblocking.
Desktop adblocking estimates are for global monthly active users of desktop adblocking software between 4/09 12/16, as calculated in the PageFair's 2015 and 2017
reports. Mobile adblocking estimates are for global monthly active users of mobile browsers that block ads by default between 9/14 12/16, including the number of
Digicel subscribers in the Caribbean (added 10/15), as calculated in the PageFair & Priori Data 2016 and PageFair 2017 Adblocking Report.
KP INTERNET TRENDS 2017 | PAGE 19
Leading Platform Ad Offerings =
Rapidly Improving with
Back-End Data +
Front-End Measurement Tools +
Targeted Delivery of Ads
Users Increasingly Want
KP INTERNET TRENDS 2017 | PAGE 20
Source: Facebook, Google, Snap
Leading Online Ad Platforms =
Providing More Ways to Target + Measure Ads
Facebook (Delivery Insights)
Google (AdWords)
Snap (Snap Ads)
KP INTERNET TRENDS 2017 | PAGE 21
Product Listing Ads (Google) =
Driving Clicks to Product Pages
Google Product Listing Ads (PLAs)
Share of Retail Paid Clicks on Google, USA, 2014-2016
29%
52%
0%
10%
20%
30%
40%
50%
60%
PLA Share of Retail Paid Clicks on Google (%)Google PLA on Mobile Web,
12/16
Source: Merkle Digital Marketing Report (Q1:14-Q1:17), Right image: Search Engine Land
KP INTERNET TRENDS 2017 | PAGE 22
Targeted Pins (Pinterest) =
Driving Product Discovery + Purchase
Pinterest
Browsing Turning into Buying, 4/17
33%
12%
44%
24%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Browse
Buy
% of Respondents4/15
4/17
Which of these services is a
great place to browse for
things you might want to buy?
Which of these services is a
great place to buy things online?
Shop the Look
Inspired Purchases, 2/17
Source: Pinterest
Note: Based on an internal survey of global internet users, n=12K. Other answers to the questions include Facebook, Instagram, Twitter, Snap,
YouTube, and Google with each respondent only allowed to choose one option.
KP INTERNET TRENDS 2017 | PAGE 23
Contextual Ads (Facebook) =
Driving Direct Purchases
Facebook Messenger
Conversational Transactions,
9/16
26%
7%
10%
74%
93%
90%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Clicked on an Ad
Didn't Click on Ad
Not Sure
% of RespondentsMade a Purchase
Did Not Make a Purchase
Facebook Users
26% that Click Ads Make Purchase, USA, 3/17
In past 30 days, have you clicked an ad on Facebook?
In past 30 days, have you purchased a product you saw
on Facebook?
Source: Survata (4/17), Messenger Image: Facebook Blog (9/16)
Note: Based on survey of USA internet users, n=1,500 (3/17).
KP INTERNET TRENDS 2017 | PAGE 24
Goal Based Bidding Ads (Snap) =
Driving User Action
Snap / Gatorade Ad Campaign
Users Swipe Through Ad to Web Game, 8/16
Users Spend Average of 196 Seconds Playing Game
Source: Snap Case Study: Gatorade (8/16)
KP INTERNET TRENDS 2017 | PAGE 25
Geo-Targeted Local Ads (Google) =
Driving Foot Traffic to Stores
Google Location-Tagged Ads
99% Accuracy Tracking Visits to 200MM Stores Globally, 9/16
5B Cumulative Tracked Store Visits, Up 5x Y/Y*, 5/17
Source: Google Adwords Blog (5/16, 9/16, 5/17), Image: Google Adwords Blog (9/16)
* 5B (5/17) vs. 1B cumulative tracked (5/16).
KP INTERNET TRENDS 2017 | PAGE 26
Incentive-Based + Skippable Video Ads =
Driving Positive Interactions
Incentive-Based + Skippable Video Ads
More Likely to be Viewed Positively, 5/16
How would you characterize your attitude towards the following formats of online video advertising?
19%
20%
21%
26%
45%
46%
51%
52%
68%
81%
80%
79%
74%
55%
54%
49%
48%
32%
Mobile App Pop-Up
Pre-Roll
In-Banner Auto-Play
Social Auto-Play
In-Banner Click-to-Play
Skippable Mobile Pop-up
Skippable Pre-Roll
Social Click-to-Play
Mobile App Reward
% of Respondents
Positive
Negative
Source: MillwardBrown AdReaction Video Creative in a Digital World (5/16)
Note: Survey of people from Argentina, Australia, Brazil, France, Germany, Mexico, UK, and USA who watched 20 ads (at least 100 per ad) and
answered positive or negative, n=10.739. The survey included TV, YouTube skippable pre-roll, Facebook auto-play, Facebook click-to-play, and
mobile video ad formats.
KP INTERNET TRENDS 2017 | PAGE 27
In-App Ads + Dynamic Creative (Vungle) =
Driving Higher In-App Install Performance
Dynamic Tab Ad
Video + Images
0.00%
0.10%
0.20%
0.30%
0.40%
0.50%
0.60%
0
100
200
300
400
500
600
1/162/163/164/165/166/167/168/169/1610/1611/1612/161/172/173/174/17Conversion Rate (%)Dynamic Creative Variations (K)Dynamic Creative Variations
Conversion Rate
Vungle Dynamic Creative Ads
Improving Conversion Rates, 5/17
Source: Vungle (5/17)
Note: "Dynamic creative" is any creative ad that changes automatically based on information about the user (behavior, location, or context). A
dynamic tab ad includes multiple interactive promotional modules alongside a video ad.
KP INTERNET TRENDS 2017 | PAGE 28
In-Ride / In-Hand Recommendations (Uber + Foursquare) =
Location + Route + Destination + Time of Day (+ an Offer)
Uber / Foursquare Partnership
In-App Recommendations for Nearby Businesses, 4/17
Source: Uber (4/17)
KP INTERNET TRENDS 2017 | PAGE 29
Hyperlocal Targeting (NextdoorxAd) =
From Home (Neighborhood) to Work (Commute)
xAd
Tracking Where / When Purchases
Likely to be Made
Nextdoor
Neighbors Drive Word of Mouth
+8% Engagement Lift
for Ring
Source: Nextdoor, xAd
KP INTERNET TRENDS 2017 | PAGE 30
Advertising Inefficiency =
Increasingly Exposed by Data
Right 'Ad' @ Right Place / Time
KP INTERNET TRENDS 2017 | PAGE 31
Right Ad @ Right Place / Time (Driven by Algorithms)
User-Typed Input (Words)
Linked to Relevant Ad =
Google AdWords (Launched 2000)
Source: Historyofinformation.com, Google
KP INTERNET TRENDS 2017 | PAGE 32
Right Ad @ Right Place / Time
Based on User-Typed Input (Words) = Big Business for Google
Google = $679B Market Capitalization
+30x vs. IPO
$0
$200
$400
$600
$800
$1,000
$1,200
8/042/058/052/068/062/078/072/088/082/098/092/108/102/118/112/128/122/138/132/148/142/158/152/168/162/17Share Price ($)Source: Yahoo Finance
Note: Priced as of 5/26/17 market close. Google IPO'ed @ $85 / share on 8/19/04.
KP INTERNET TRENDS 2017 | PAGE 33
Right Ad @ Right Place / Time (Driven by Algorithms)
User-Uploaded Input (Real-Time Images)
Linked to Relevant Ad =
SnapAds (Launched 2014)
Source: Image: Adweek (10/14)
KP INTERNET TRENDS 2017 | PAGE 34
Right Ad @ Right Place / Time
Based on User-Uploaded Input (Images) = Big Business for Snap
Snap = $25B Market Capitalization
0
20
40
60
80
100
120
140
160
180
$0
$20
$40
$60
$80
$100
$120
$140
$160
$180
Q1:15
Q2:15
Q3:15
Q4:15
Q1:16
Q2:16
Q3:16
Q4:16
Q1:17
DAU (MM)Net Revenue ($MM)Net Revenue
DAU
Source: Snap Filings
Note: Priced as of 5/26/17 market close. Snap IPO'ed @ $17 / share on 3/2/17.
KP INTERNET TRENDS 2017 | PAGE 35
A lot of the future of search is
going to be about pictures
instead of keywords.
- Ben Silbermann, Pinterest Founder / CEO, 4/17
Source: CNBC interview (4/3/17)
KP INTERNET TRENDS 2017 | PAGE 36
Ads Evolving Rapidly =
Often Organic + Data @ Core
KP INTERNET TRENDS 2017 | PAGE 37
Emerging Retailers + Crafty Big Brands =
Finding Ways to Make
Collaborative Ad Creation
(Social + UGC) Work for Them
KP INTERNET TRENDS 2017 | PAGE 38
Brands + Consumers =
Re-Distribution Driving Engagement
Ben & Jerry's / UGC on Instagram, 5/17
Effective UGC can generate 6.9x higher engagement than
brand generated content on Facebook, per Mavrck, 2/17
Source: Mavrck Facebook UGC Benchmark Report (2/17), Image: benandjerrys Instagram featuring mistress_spice (4/17)
Note: Study based on 536,238 micro-influencer brand activations completed via Mavrck Platform from 1/1/16-12/13/16.
KP INTERNET TRENDS 2017 | PAGE 39
Brands + Consumers =
Brands Sourcing Content from Fans
Brands = Leveraging UGC on Instagram
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Amazon Video
Emirates
Turkish Airlines
Cathay Pacific
Starbucks
Netflix
Sephora
Wayfair
BMW
Red Bull
Qatar Airways
% of Instagram Content Regrammed
Source: SimplyMeasured (11/16)
Note: Data collected from each company's Instagram page from 7/16-10/16. Posts were manually tagged for regrams based on mentions on
'regram' in the post or the camera emojis.
KP INTERNET TRENDS 2017 | PAGE 40
Brands + Influencers =
Re-Distribution Driving Engagement
Influencers = Can Impact Followers
Source: Stance
KP INTERNET TRENDS 2017 | PAGE 41
Emerging Retailers + Crafty Big Brands =
Finding Ways to Make
Images (+ Video) + Data +
Algorithms + Voice Work for Them
KP INTERNET TRENDS 2017 | PAGE 42
Image-Based Platform Front-Ends =
Tap + Augment Can Replace Typing
'Front-End'
User-Generated Real-Time Geolocated Images
Source: Left Image: Snap, Right Image: Instagram blog (3/17)
KP INTERNET TRENDS 2017 | PAGE 43
Image-Based Platform Front-Ends =
Taking Pictures Can Replace Typing
'Front-End'
Google Lens Will Provide Greater Context to Images
Source: Google I/O (5/17)
KP INTERNET TRENDS 2017 | PAGE 44
Image-Based Platform Back-Ends =
Algorithms Infer User Context from Images
'Back-End'
Algorithms Infer Images / Project AR Objects into Scenes
Source: Images: CB Insights, Seene Patents (acquired by Snap in 6/16) and Looksery Patents (acquired by Snap in 9/15)
KP INTERNET TRENDS 2017 | PAGE 45
Image Recognition Back-Ends =
Can Provide Contextual Relevance for Advertisers
Snap Image Recognition
Potential Ad Targeting Tool
Google Visual Positioning Service
Tracking Path to PurchaseIn-Store
Source: Left Image : Snap Patent (7/16), Right Image: Google I/O (5/17)
KP INTERNET TRENDS 2017 | PAGE 46
Voice-Based Mobile Platform Front-Ends =
Voice Can Replace Typing
Google Assistant
Nearly 70% of Requests are Natural / Conversational Language, 5/17
20% of Mobile Queries Made via Voice, 5/16
Source: Google I/O (5/16), Image: Macrumors (2/17)
KP INTERNET TRENDS 2017 | PAGE 47
Voice-Based In-Home Platform Front-Ends =
Voice Can Replace Typing
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
Number of SkillsAmazon Echo Device Installed Base,
USA
Amazon Echo Skills
Broadening Use Cases
Amazon Echo Evolution, 11/14 5/17
Echo = Shopping + Media
Echo Look = Shopping + Recommendations
Echo Show = Video + Voice Calls
0
2
4
6
8
10
12
Echo Installed Base (MM)Source: Image: Amazon, Consumer Intelligence Research Partners LLC, Geekwire, Technology Review, Wired, Fast Company
KP INTERNET TRENDS 2017 | PAGE 48
Voice-Based Platform Back-Ends =
Voice Recognition Accuracy Continues to Improve
Google Machine Learning
Achieving Higher Word Accuracy, 2013-2017
95%
95%
70%
80%
90%
100%
2013
2014
2015
2016
2017
Word Accuracy Rate (%)Google
Threshold for Human Accuracy
Source: Google (5/17)
Note: Data as of 5/17/17 and refers to recognition accuracy for English language. Word error rate is evaluated using real world search data which
is extremely diverse and more error prone than typical human dialogue.
KP INTERNET TRENDS 2017 | PAGE 49
Ads =
Becoming Targeted Storefronts
KP INTERNET TRENDS 2017 | PAGE 50
Ads / Content / Products / Transactions =
Lines Blurring. Fast
The Content = The Store
Emails
Curated Storefronts
Facebook Feed
Browsable Storefronts
Source: Left Image: Facebook, Right Image: Stitch Fix
KP INTERNET TRENDS 2017 | PAGE 51
Ads / Content / Products / Transactions =
Lines Blurring. Fast.
The Ad = The Transaction
Instagram Feed
Tap to Book, 4/17
Snap eCommerce Ad
Swipe Up to Buy, 5/16
Source: Left Image: Instagram, Right Image: Snap
KP INTERNET TRENDS 2017 | PAGE 52
Product Quality + Customer
Support + Transparency
Bars Rising =
Owing to Social Media
KP INTERNET TRENDS 2017 | PAGE 53
60%
53%
29%
21%
0%
10%
20%
30%
40%
50%
60%
70%
Easier Access to Online
Support Channels
Faster Agent Reponse
Times
Consistent Customer
Experience Across
Channels
Faster Access to Live
Support
% of ResponsesSocial Media =
Can Provide Opportunity to Improve Customer Service
If you could choose two things for organizations to improve in customer service,
what would they be? (Select two), 8/16
Source: Ovum Get It Right: Deliver the Omni-Channel Support Customers Want (8/16)
Note: Survey of consumers ages 18-80 in Australia, Europe, New Zealand, and USA, n=400.
KP INTERNET TRENDS 2017 | PAGE 54
Social Media =
Can Drive Accountability
82% of Customers Stopped Doing Business with a Company
After Bad Experience vs. 76% in 2014, 8/16
Source: Image: Allbirds, Ovum Get It Right: Deliver the Omni-Channel Support Customers Want (8/16)
Note: Survey based on consumers ages 18-80 in Australia, Europe, New Zealand, and USA; n=400.
KP INTERNET TRENDS 2017 | PAGE 55
Intercom
Simple + Engaging UI
Real-Time Online Customer Conversations =
Rising Rapidly
Intercom Conversations Started, Global,
12/13-12/16
0
100
200
300
400
Conversations Started (MM)Source: Intercom
Note: Conversations include messages initiated by businesses & consumers.
KP INTERNET TRENDS 2017 | PAGE 56
Customers =
Increasingly Expect to Understand How Things Work
SoFi 'How It Works'
Most Viewed Content, After Home Page
SoFi Member Dashboard
Send Questions Directly to CEO
Source: SoFi
KP INTERNET TRENDS 2017 | PAGE 57
Retailers Emerging With
Especially Effective Strategies
KP INTERNET TRENDS 2017 | PAGE 58
Chewy.com = Pet Treats / Food / Supplies
Strong User Community + Great Target Market
Engaged Community +
High Customer Satisfaction
Strong Revenue Growth
$0
$100
$200
$300
$400
$500
$600
$700
$800
$900
$1,000
2015
2016
Revenue ($MM)Dynamic Customer Service
Source: Chewy.com
KP INTERNET TRENDS 2017 | PAGE 59
Glossier = Skincare & Beauty Products...
Content Marketing
User Generated Content = Influencers
300%
350%
400%
450%
500%
550%
600%
2015
2016
Active Customer % Y/Y GrowthAccelerating Active Customer Growth
'Into the Gloss' = Content Marketing
Source: Glossier, Top Left Image: Instagram user genius_hotel, Bottom Left Image: Glossier
KP INTERNET TRENDS 2017 | PAGE 60
UNTUCKit = Shirts
Online-Offline Synergies in Marketing + Merchandising
Source: UNTUCKit
Note: Online session defined as website visit.
0
1
2
3
4
5
6
7
8
2015
2016
Sessions (MM)Online Sessions
Up >2.5x Y/Y
Offline Engagement
Direct Touchpoints in Physical World
Online Storefront
Digital Merchandising Insights
In-Store Interactions
Intimacy + Active Dialogue
Digital-Physical Feedback Loop
Deliberate Branding + Clear Messaging @ Core
KP INTERNET TRENDS 2017 | PAGE 61
Allbirds = Shoes
Innovative Product + Simple Choice (Less Selection = More)
Source: Allbirds
* 3/16-6/16, H1:17 data from 1/17-5/17.
0
1
2
3
4
5
6
H1:16*
H2:16
H1:17
eCommerceSessions (MM)Growing eCommerce Sessions
Two Comfortable, High Quality Styles
Tongue base
double row stitch
implemented
Tongue
lace loop
reworked
Tongue
reinforcement
layer added
New internal toe
reinforcement
added
3x adjustments to
U-throat opening
Insole geometry
modified
New process/
material logo
tabs developed
Outsole
durometer
reduced
Outsole
redesigned
Alternative
insole cover
material
developed
New vamp
lining wool
textile
introduced
Product Changes Based on Customer Input
KP INTERNET TRENDS 2017 | PAGE 62
Trendyol = Apparel...
Private Label + Local Sourcing for Local Consumers (Middle East)
High Purchase Re-Engagement
Items Purchased per Shopper Continue to Rise
0
2
4
6
8
10
12
2014
2015
2016
2017 YTD
Average Units per Active ShopperPrivate Label + Local Sourcing
Low Prices + Short Lead Times
~1K Suppliers 50km from Trendyol HQ
Fast Replenishment (7-10 days)
Private Label @ 38% of Revenue
Other Fashion Brands
Source: Trendyol
Note: Average units per active shopper calculated over the course of shopper lifetime.
KP INTERNET TRENDS 2017 | PAGE 63
MM.LaFleur = Women's Professional Wardrobe
Relationship-Driven Experience (Online & Offline)
High Growth + Retention
$0
$5
$10
$15
$20
$25
$30
$35
2015
2016
Revenue ($MM)Returning Customers
New Customers
Wardrobe Survey
Algorithmic Optimization
Bento Box
Curated
Impressions
Online Shopping
Ongoing Customer
Engagement
In-Store Stylist
Appointments
Human Touch +
Active Dialogue
Source: MM.LaFleur
KP INTERNET TRENDS 2017 | PAGE 64
eCommerce A-Ha's
KP INTERNET TRENDS 2017 | PAGE 65
0%
2%
4%
6%
8%
10%
12%
0
2
4
6
8
10
12
2010
2011
2012
2013
2014
2015
2016
Y/Y Growth (%)Parcel Volume* (B)If It Seems Like Package / Parcel Growth is Accelerating
It's Because It Is, +9% Y/Y
Parcel Volume*, USA, 2010-2016
Source: USPS, Fedex, UPS Filings
*Combines USPS's Domestic Shipping and Package Services volumes, Fedex's calendar year Domestic Package volumes, and UPS's Domestic
Package volumes.
KP INTERNET TRENDS 2017 | PAGE 66
Apartment Building Lobbies Becoming Warehouses
Doormen Becoming Foremen
Landlords
Expanding Package Rooms to Accommodate Rising Online Order Delivery
Source: Image: NYTimes Photographer Tony Cenicola
KP INTERNET TRENDS 2017 | PAGE 67
Unwrapping Boxes
Becoming Entertainment
Unboxing YouTube Top 5 Channels =
33MM+ Subscribers, 5/17
Source: YouTube: Ryan's Toy Review, Fun Toys Collector Disney Toys Review, Disney Car Toys, Toys AndMe, Blu Toys Club Surprise, Images:
CKN Toys
KP INTERNET TRENDS 2017 | PAGE 68
Eating Out is
Increasingly Eating In
Top 10 DoorDash San Francisco Bay Area Restaurants
Delivery as % of Revenue = 7% vs. 2% (2015)
Revenue Growth = +45% Y/Y vs. 10% (2015)
Eating Out
Eating In
Source: DoorDash, Left image: Pexels, Right image: DoorDash
KP INTERNET TRENDS 2017 | PAGE 69
Grocery Shopping
Getting Personal / Fast / Easy
Instacart = Personalized Grocery Recommendations
8x More Likely to Buy
When Prompted with
'Buy It Again' Option
85% of In-Store Replacements...
Chosen Based on Algorithmic Recommendations
Source: Instacart
KP INTERNET TRENDS 2017 | PAGE 70
Lowe's Doing Augmented Reality
Helping Consumers Find Products In-Store
Lowe's / Google Partnership
Guides Customers to In-Store Items via Augmented Reality on Mobiles, 3/17
Source: Google, Lowe's
KP INTERNET TRENDS 2017 | PAGE 71
Stitch Fix Launching Another Private-Label Clothing Brand &
It's Computer-Generated (1% of Products for Now)...
Product Attributes + Customer Feedback + Data Science / Testing
New Style, 5/17
Silhouette
Sleeve
Lace Feature
Hem Type
Print
Cassie Crochet Detail Top
Source: Stitch Fix, Left Image: Stitch Fix Algorithms Tour, Right Image: Stitch Fix
KP INTERNET TRENDS 2017 | PAGE 72
Retail Store Closings May Break 20 Year Record While...
Amazon Opens Retail Stores
Retail Unit Closings, USA, 1995-2017 YTD
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
19951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017EUnit ClosingsAverage
Amazon Looks to Expand its
Physical Footprint
Source: Credit Suisse, Amazon
Note: 2017 is YTD as of 4/6/17. 2017 estimate per Credit Suisse.
KP INTERNET TRENDS 2017 | PAGE 73
Digitally Native Brands = Go Offline
I don't think retail is dead. Mediocre retail experiences are dead.
- Neil Blumenthal, Co-CEO @ Warby Parker, 1/17
Bonobos Guide Shops
Try On In-StoreShip to Home
Warby Parker
Schedule Eye ExamsBuy Glasses
Source: WSJ interview 1/23/17, Left image: Pinterest, Right image: Fashion Trends Daily
KP INTERNET TRENDS 2017 | PAGE 74
World's Largest Offline Retailer (Wal-Mart)
Getting Aggressive Online
Wal-Mart eCommerce Revenue Y/Y Growth, Global
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
% Y/Y Growth90% of Americans Live Within 10 Miles of a Wal-Mart
FQ1:18 eCommerce
Revenue Growth @
63% Y/Y vs. 29%
FQ4:17, USA
Modcloth.com, 3/17
Moosejaw, 2/17
JD.com (Increased to
12%), 2/17
Shoebuy, 1/17
Recent
Acquisitions &
Investments
Organic + Inorganic
Growth
Source: Wal-Mart
Note: Fiscal year ends January. Wal-Mart stopped disclosing global eCommerce revenue growth after FQ4:17 and began disclosing USA
eCommerce revenue growth.
Acquired Jet.com, 8/16
KP INTERNET TRENDS 2017 | PAGE 75
Amazon Becoming a Leading Private-Label Supplier of
Baby Wipes + Batteries, USA
Amazon Basics Market Share, 8/16 USA
0%
5%
10%
15%
20%
25%
30%
35%
Online Baby Wipes Market Share (%)0%
5%
10%
15%
20%
25%
30%
35%
Online Battery Market Share (%)Source: Images: Amazon, 1010 Data
Note: Data collected from 9/15-8/16
KP INTERNET TRENDS 2017 | PAGE 76
eCommerce Growth = +15% Y/Y
Accelerating, Again, USA
Online Retail Sales vs. Y/Y Growth, USA 2010-2016
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
$0
$50
$100
$150
$200
$250
$300
$350
$400
$450
2010
2011
2012
2013
2014
2015
2016
% Y/Y GrowthUSA Online Retail Sales ($B)Source: St. Louis Federal Reserve FRED Database
KP INTERNET TRENDS 2017 | PAGE 77
And Now We Have a New Kind of Store =
A Subscription Store
Amazon Subscription Store = Central Hub for Monthly Services, 4/17
Entertainment
Education
Professional
Services
Cloud
Storage
News
Source: Amazon
KP INTERNET TRENDS 2017 | PAGE 78
More / Faster Than Ever =
Great Products Find Customers
Customers Find Great Products
Process + Data Collection + Intermediaries =
Changing @ Torrid Pace
KP INTERNET TRENDS 2017 | PAGE 79
1) Ad Growth = Driven by Mobile
2) Ad Measurability = Can Be Triple-Edged
3) Ads Evolving Rapidly = Often Organic + Data @ Core
4) Ads = Becoming Targeted Storefronts
5) eCommerce Growth = Accelerating, Again
6) eCommerce A-Ha's
Online Advertising (+ Commerce) =
Increasingly Measurable + Actionable
KP INTERNET TRENDS 2017 | PAGE 80
INTERACTIVE GAMES =
MOTHERLODE OF
TECH PRODUCT INNOVATION / EVOLUTION +
MODERN LEARNING
WITH THANKS TO BING GORDON FOR INSIGHT + INSPIRATION
KP INTERNET TRENDS 2017 | PAGE 81
Global Interactive Gaming =
Mainstream / Evolving Rapidly /
Still Early Days
2.6B Gamers* vs. 100MM in 1995
Source: Unity Q1:17 estimate (5/17), Electronic Arts 2016 estimate (12/16), Electronic Arts 1995 estimate (5/17)
*Unity estimates reflect the total number of users seen playing mobile games (at least once every three months) powered by both proprietary and
leading 3rd party game engines. This number assumes all PC or Console gamers also play at least 1 mobile game.
KP INTERNET TRENDS 2017 | PAGE 82
Gaming Evolution =
Individual Play Global Collaborative Play (1967-2017)
45 Years
Solo Living Room
Many Arena (Thousands)
Online (Millions)
Moore's Law
(Processing)
Zuckerberg's Law*
(Sharing)
1 Player =
Arcade
2 Players =
Consoles
2+ Players =
Consoles +
LAN
Millions of
Players =
Online
Network
Millions of
Players +
Spectators =
eSports
Source: Images: National Museum of American History (Brown Box), Wikipedia Creative Commons (Pac-Man, Atari 2600, SG-1000, SNES, N64, PS1, Xbox, PS2), Flickr
user Sham Hardy (World of Warcraft), Flickr user coneybeare (Words with Friends), ESL (ESL Logo), Twitch (Twitch Logo), Major League Gaming (MLG Logo),
Wikimedia Creative Commons (Pong), Flickr user BagoGames (eSports Stadium)
Note: In 1967 TV Game Unit #7, also known as the "Brown Box" was launched as a prototype and is considered the father of video game consoles per the National
Museum of American History.
*Zuckerberg's Law describes the exponential growth of online social networks as per Saul Hansell in NY Times, 11/6/08.
KP INTERNET TRENDS 2017 | PAGE 83
Source: Images: Wikimedia Creative Commons (Pong, Asteroids, Space Invaders, Pac-Man), Flickr user BagoGames (Mario Bros), Mobygames
(John Madden Football), Electronic Arts (FIFA), Pokmon (Pokmon Red and Blue versions), World of Warcraft (Warcraft), Supercell (Clash of
Clans), Minecraft (Minecraft Logo), Riot Games (League of Legends), King (Candy Crush Saga), Activision Blizzard (Overwatch), Pokmon Go
(Pokmon Go)
Gen X + Millennials =
Gamified Since Birth
1970
2000
2010
1980
1990
Gen X
Millennials
KP INTERNET TRENDS 2017 | PAGE 84
Gaming = Large + Broad + Growing Business
Revenue @ $100B, +9% Y/Y
Interactive Gaming Revenue Estimates per Newzoo, Global, 2016
$3
$3
$4
$17
$25
$47
Middle East & Africa
Eastern Europe
Latin America
Western Europe
North America
Asia Pacific
Revenue ($B)
Source: Newzoo Global Games Market Report (2016)
Note: Excludes console / gaming PC hardware revenue.
KP INTERNET TRENDS 2017 | PAGE 85
Gamers = All Ages
35 Year-Old Average, USA
Gamer Demographics vs. Average Age, USA, 2003-2016
0
5
10
15
20
25
30
35
40
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Average Age% of GamersUnder 18
18-50
50+
Average Age
Source: Entertainment Software Association (ESA) Essential Facts About the Computer and Video Game Industry 2003-2016
Note: Based on a survey of 4,000 U.S. households.
KP INTERNET TRENDS 2017 | PAGE 86
Female Gamers = Players Since Early Days But Genres Vary
2000 (Year) Marked Rise of Casual Female Gamer
% of Female Players by Game Genre,
Global, 1/17
2%
6%
7%
16%
18%
36%
42%
69%
69%
Sports
Racing
First-Person Shooter
MMOs (Sci-Fi)
Action Adventure
MMOs (Fantasy)
Casual Puzzle
Family / Farm Sim
Match 3
Match 3
Pioneered by Diamond Mine /
Bejeweled, 2000
Family / Farm Sim
Pioneered by Sims, 2000
Source: Quantic Foundry, Top Right Image: Popcap, Bottom Left Image: MoMA
Note: Each genre analyzed contained between 3-5 game titles. The median sample size for each game title was 1,184. And the median sample
size for each genre was 4,657.
KP INTERNET TRENDS 2017 | PAGE 87
Gaming Tools = Pervasive Online
Can Optimize Learning +
Engagement
Foundational for Internet Services
KP INTERNET TRENDS 2017 | PAGE 88
Gaming Tools =
Can Optimize Learning + Engagement
Foundational for Internet Services
Repetition
Dynamic Difficulty Adjustment
Solving Puzzles
Planning Workflows
Completing Projects
Leveling Up
Competing
Exploring / Discovering
Following Rules
Collaborating Social Connection / Leadership
Observing
Interacting With / Analyzing Data
Self Optimizing
Creative Story Telling
KP INTERNET TRENDS 2017 | PAGE 89
Source: Center quote from Len Schlesinger: "Failure doesn't mean the game is over, it means try again with experience," Global Leadership
Summit (8/11/11), Images: Playpacmanonline.net
Repetition =
Learn from Losing
Trial & Error
Gaming Lifecycle
Try again, with
experience
Respawn
Fail
Play
Test Tactics
KP INTERNET TRENDS 2017 | PAGE 90
Dynamic Difficulty Adjustment =
Ultimate Trial & Error Experience
Engaging Learning Process
Machine-Learning Fine-Tunes Gaming Mechanics
Source: Image: Games for Learning Institute
KP INTERNET TRENDS 2017 | PAGE 91
Solving Puzzles =
Pattern Recognition + Critical Thinking
Defined Rules + Strategy
(Short-Form)
Minesweeper
Unstructured Puzzles
(Long-Form)
L.A. Noire Detective Cases
Source: Left image: Game Set Watch, Right image: L.A. Noire (Rockstar Games)
KP INTERNET TRENDS 2017 | PAGE 92
Planning Workflows =
Manage Time + Resource Efficiency
Time Management
Legend of Zelda: Majora's Mask Quest
Progress Resets Periodically
Resource Management
Starcraft II 'Require More Minerals'
Source: Left image: Zelda Informer, Right image: Activision Blizzard Battle.net
KP INTERNET TRENDS 2017 | PAGE 93
Completing Projects =
Track Finish Line from Start
Focus on End Goal
Pokmon 'Gotta catch 'em all!'
Track Experience
Skyrim
Source: Left Images: Logos Wikia, Bulbapedia, Right Images: Skyrim, YouTube user HighlandMarker, Portforward.com, metagamebook, Stack
Exchange
KP INTERNET TRENDS 2017 | PAGE 94
Leveling Up =
On-Going Progress Measurement
Leveling Up
Candy Crush Saga
Gain Experience Completing Puzzles
Quantified Mastery
Max Level in World of Warcraft
Source: Left Images: Apptipper, King, Right Image: Blizzardwatch
KP INTERNET TRENDS 2017 | PAGE 95
Competing =
Play Against Self + Others Sharpens Skills
Competing Against Yourself
Time Trials in Mario Kart 64
Competing Against Others
Scoring Goals Online in Rocket League
Source: Left Image: YouTube user Drew Weatherton, Right Image: GameSpot
KP INTERNET TRENDS 2017 | PAGE 96
Exploring / Discovering =
Open Closed DoorsHack to Improvement
Discovering Easter Eggs
Silent Hill 2 + Tony Hawk's Pro Skater 2
Discovering Glitches
Secret Level in Super Mario Bros
Source: Left Images: Nintendo, Right Images: Digital Trends, Games Radar
KP INTERNET TRENDS 2017 | PAGE 97
A game is a system in which players engage in an artificial
conflict, defined by rules, that results in a quantifiable outcome.
- Salen & Zimmerman, Rules of Play: Game Design Fundamentals, 9/03
Following Rules =
Structured Play
Players = Free to Break Rules
But = Consequences
Source: Salen & Zimmerman, Rules of Play: Game Design Fundamentals, Left image: YouTube user Ross Campbell, Right image: YouTube
user x Pepper
KP INTERNET TRENDS 2017 | PAGE 98
Collaborating Social Connection / Leadership =
Learn From / Work With Others
Blizzard = Millions Playing Together Online, Global
Key Multiplayer Franchises = World of Warcraft + Diablo + Starcraft + Overwatch
21
29
28
26
26
33
42
41
41
0
5
10
15
20
25
30
35
40
45
Q1:15
Q2:15
Q3:15
Q4:15
Q1:16
Q2:16
Q3:16
Q4:16
Q1:17
MAU (MM)Source: Activision, Morgan Stanley
Note: Graph emphasizes Blizzard over Activision and King users due to the multiplayer nature of most Blizzard franchises.
KP INTERNET TRENDS 2017 | PAGE 99
Observing =
Learn From Watching Others Perform
Live Streamed
Gameplay
Live Streamed
Player Reactions
Live Chat Interaction
with Player
Subscribe to
Streamer
1.2
2.4
3.2
4.0
4.9
0.0
0.5
1.0
1.5
2.0
2.5
0
1
2
3
4
5
6
2012
2013
2014
2015
2016
Unique Monthly Streamers (MM)Hours Streamed (B)Hours Streamed
Unique Monthly Streamers
Twitch Hours Streamed vs.
Unique Monthly Streamers
Source: Left image: Twitch Streamer: cherrysamora, Twitch Annual Reports 2013-2016
Twitch Streaming
10MM DAU, 2/17
KP INTERNET TRENDS 2017 | PAGE 100
Interacting With / Analyzing Data =
Many Games Have Strong Math Underpinnings
Fantasy Sports
Fans Engaged in Analytics, USA, 1988-2016
Live Stats
Feed Into Video Games +
Fantasy Sports
0%
5%
10%
15%
20%
25%
0
10
20
30
40
50
60
70
198819911994200320042005200620072008200920102011201420152016% of USA Population Over 18Fantasy Sports Players* (MM)USA Fantasy Sports Players
% of USA Population
John Madden
Football Released
Source: FSTA, Left image: Flickr user We Are Social, U.S. Census Bureau
*Fantasy Sports Players are defined as U.S. individuals aged 18+ having played fantasy sports in the past year. Based on survey of USA
individuals aged 18+, n=1,000.
KP INTERNET TRENDS 2017 | PAGE 101
Self-Optimizing =
Driven by Math (Statistics / Metrics / Rankings)
In-Game Player Analytics / Dashboards
Increasingly Found in Enterprise / Consumer Products / Services
Madden 2017 Player Stats
Looker Business Intelligence Dashboard
Source: Top left image: YouTube user Brian Mazique, Bottom left image: Uproxx, Right Image: Looker
KP INTERNET TRENDS 2017 | PAGE 102
Creative Story Telling =
Can Be Master of a Universe
Laying Building Blocks of a Virtual World
Minecraft
Choosing Gameplay Experience
Mass Effect 3
Source: Left image: Gamepedia blog, Right image: Kotaku Minecraft
KP INTERNET TRENDS 2017 | PAGE 103
Gaming Tools =
Can Optimize Learning + Engagement
Foundational for Internet Services
Reputation / Rankings
Digital Recognition
Interactive Storytelling
Interactive Learning
Upgrades + Downloadable Content
Secondary Markets
Messaging
Live Camera Angles
Graphics Computation
KP INTERNET TRENDS 2017 | PAGE 104
Reputation / Rankings =
Deep Roots in Gaming
Airbnb
Superhost Program Recognizes
Top Performing Hosts
Early Gaming (1978)
Mainstream Internet (Now)
Space Invaders
First Arcade Game to Record
High Scores
Source: Left image: Codexdex, Right image: Airbnb, Probnb
KP INTERNET TRENDS 2017 | PAGE 105
Digital Recognition =
Deep Roots in Gaming
Activision 2600 Games
Physical Badges for In-Game Achievements
Facebook
Give Digital Badges to Others
Early Gaming (1980)
Mainstream Internet (Now)
Source: Left image: Atari Age, Right image: Facebook
KP INTERNET TRENDS 2017 | PAGE 106
Interactive Storytelling =
Deep Roots in Gaming
Atari
First Role Playing Game
Netflix + Amazon / Twitch
Experimenting with Interactive Shows
Early Gaming (1980)
Mainstream Internet (Now)
Source: Left image: mprd.se, Right images: Netflix, Amazon
KP INTERNET TRENDS 2017 | PAGE 107
Duolingo
Leveling Up in Languages
Lemonade Stand
Teaching Economics 101
Interactive Learning =
Deep Roots in Gaming
Early Gaming (1979)
Mainstream Internet (Now)
Source: Left Image: Archive.org, Right Image: Duolingo,
KP INTERNET TRENDS 2017 | PAGE 108
Tesla
Over-the-Air Software Updates
Sega
Downloadable Content via Cable
Upgrades + Downloadable Content =
Deep Roots in Gaming
Early Gaming (1993)
Mainstream Internet (Now)
Source: Left image: Gamecrate, Right image: Tesla
KP INTERNET TRENDS 2017 | PAGE 109
Secondary Markets =
Deep Roots in Gaming
Runescape
Secondary Markets for Items / Currency
Apple iMessage
3rd Parties Offer Sticker Packs
Early Gaming (2001)
Mainstream Internet (Now)
Source: Left image: RPGStash, Right image: Macstories
KP INTERNET TRENDS 2017 | PAGE 110
Messaging =
Deep Roots in Gaming
768MM DAU
12/16
1999
5MM DAU
1/17
2009
2013
9MM DAU
5/17
Early Gaming
Mainstream Internet (Now)
Source: WeChat 2016 Year End Report (12/16), Ali Rayl Interview (Head of Global Customer Experience at Slack) (1/17), Venture Beat (5/17),
Top left image: Pingwest, Top right images: Tencent, Middle images: SiteProNews, Bottom left image: ifeng, Bottom right image: Corsair
KP INTERNET TRENDS 2017 | PAGE 111
Live Camera Angles =
Deep Roots in Gaming
Madden Football
Unique Game Perspectives
Cable TV Cameras
Unique Angles of Live Games
Early Gaming (1996)
Mainstream Media (Now)
Source: Left image: Electronic Arts, Right image: Giants NFL
KP INTERNET TRENDS 2017 | PAGE 112
Graphics Computation =
Deep Roots in Gaming
NVIDIA
Launches GeForce 256 GPU
Early Gaming (1999)
Mainstream Internet (Now)
Many Companies
GPUs Used for Artificial Intelligence
Source: Left Images: NVIDIA, VGA Museum, Right images: Google Deepmind, Amazon, IBM
KP INTERNET TRENDS 2017 | PAGE 113
In Era of
Perceived Disengagement =
'Engagement' + Measurement Rising
KP INTERNET TRENDS 2017 | PAGE 114
Video Gaming =
Most Engaging Form of Social Media
Daily Minutes Spent per User Across Select Digital Media Platforms
51
50
35
30
21
0
10
20
30
40
50
60
Video Gaming
(Consoles, 9/16)
Facebook
Ecosystem (4/16)
King (Mobile
Games, 5/17)
Snapchat (5/17)
Instagram (10/14)
Average Daily Minutes Spent by Active UsersSource: Global Web Index (9/16), Facebook Q1:16 Earnings Call (4/16) & Q3:14 Earnings Call (10/14), Activision Q1:17 Earnings Call (5/17), Snapchat Q1:17 Earnings Call (5/17)
Note: Video Gaming (Consoles): Global survey, n=17,990, of console users aged 16-64 asking "Roughly how many hours do you spend playing on game consoles during a typical day."
Includes Xbox One, Nintendo Wii U, PS4, Xbox 360, PS3, Nintendo Wii King: Average time spent per DAU. King used to illustrate mobile gaming time spent given the global nature of the
platform and large base of daily active users (peaked at 158MM as of Q1:15, 128MM in Q4:15 was last disclosure). Snapchat: Average of the 25-30 minutes of daily usage found in the S-1
filing.
KP INTERNET TRENDS 2017 | PAGE 115
Mobile Daily Gaming Session Duration =
+33% (3/17 vs. 7/15), Global, per Unity Games
Mobile Average Daily Gaming Session Duration on Unity Games,
Global, 7/15 3/17
Source: Unity
KP INTERNET TRENDS 2017 | PAGE 116
When I play a video game, it's the only time
I put away the phone and forget it exists.
Video games command your attention in a
way that nothing else can or will.
- Gary Whitta, Screenwriter, Rogue One: A Star Wars Story, 5/17
Source: GamesBeat Summit 2017: How games, sci-fi, and tech create real-world magic (5/12/17)
KP INTERNET TRENDS 2017 | PAGE 117
Perhaps Interactive Gaming
Evolution / Growth / Usage
Has Been Helping Prepare Society for
Ongoing Rise of
Human-Computer Interaction?
KP INTERNET TRENDS 2017 | PAGE 118
Gaming Tools =
Improving Human Performance
Virtual + Augmented Reality /
Simulations / Real-Time Analytics
KP INTERNET TRENDS 2017 | PAGE 119
Immersive Gaming Tools =
Improving Athlete Performance
KP INTERNET TRENDS 2017 | PAGE 120
Video + Virtual Reality =
Mental Reps Can Improve Performance
STRIVR Labs + Stanford Football
Utilize Video + Virtual Reality to Repeatedly Run Plays / Scenarios
Source: STRIVR Labs, Inc.
KP INTERNET TRENDS 2017 | PAGE 121
Video + Machine Learning =
Visuals + Deep Analytics Can Improve Performance
Second Spectrum
150K+ Tracked Events per Game,* 5/17
0
2
4
6
8
10
0
5
10
15
20
25
Q1:16 Q2:16 Q3:16 Q4:16 Q1:17
Videos per Team (K)TeamsTeams
Video Sessions per Team
Video Analytics of Key Plays
Teams vs. Video Sessions per Team
Source: Second Spectrum
Note: Video session is defined as every time a user at a team watches a play using the Second Spectrum system.
*Events are data surrounding key in-game actions such as pick-and-roll defenses, off-ball screens, shot probability or rebound probability. This
allows players to query specific tactical actions during a game to gain better insight into how individuals / the team played.
KP INTERNET TRENDS 2017 | PAGE 122
Audio + Guided Meditation =
Mental Focus Can Improve Performance
CJ McCollum, NBA Shooting Guard
Uses Headspace to Maintain Focus, 6/16
There's a lot of stress in my joband a 10 minute
Headspace meditation helps you take care of all of
those things and more.
- CJ McCollum, 4/17
Headspace
Run Streak Reinforce Habits
Source: Headspace
KP INTERNET TRENDS 2017 | PAGE 123
Physically Interactive Media (PIM) =
Real-Time Activity / Analytics Can Boost Intensity / Focus for Athletes
Peloton
100K+ Bike Subscribers
(95% Retention After 1 Year)400K+ Home Riders
1MM+ Home Workouts Streamed in 3/17
2 Workouts per Week per
Subscriber
Source: Peloton
KP INTERNET TRENDS 2017 | PAGE 124
I could go ten hours at a stretch [playing soccer video games]
and I'd often spot solutions in the games that I parlayed into real life.
Zlatan Ibrahimovic, I Am Zlatan: My Story On and Off the Field, 6/14
Video Games =
Simulations Can Improve Athlete Strategy + Performance
From FIFA Online
To the Real Game
Source: I Am Zlatan: My Story On and Off the Field 2014, Left Image: New York Times (10/16), Right Image: The Sun
KP INTERNET TRENDS 2017 | PAGE 125
Video Games =
Stats Can Assist Athletes + Coaches
Video Game Player Stats
Real-Time Feedback Offline, 9/16
Hoffenheim Scout Discovers Roberto Firmino
Using Football Manager Video Game, 11/16
Players + Coaches View Digital Stats as Important Performance Measure
Source: Left Image: Twitter user Michy Batshuay, Right Image: Hardware Zone
KP INTERNET TRENDS 2017 | PAGE 126
Game
Year
Teams
Madden
Actual
Winner
Score Winner Score
Super Bowl LI
2017
Patriots vs. Falcons
Patriots
27-24
Patriots
34-28
Super Bowl L
2016
Broncos vs. Panthers
Panthers 24-20 Broncos 24-10
Super Bowl XLIX
2015
Patriots vs. Seahawks
Patriots
25-24
Patriots
28-24
Super Bowl XLVIII
2014
Broncos vs. Seahawks
Broncos 31-28 Seahawks 43-8
Super Bowl XLVII
2013
49ers vs. Ravens
Ravens
27-24 Ravens 34-31
Super Bowl XLVI
2012
Patriots vs. Giants
Giants
27-24
Giants
21-17
Super Bowl XLV
2011
Steelers vs. Packers
Steelers
24-20 Packers 31-25
Super Bowl XLIV
2010
Saints vs. Colts
Saints
35-31
Saints
31-17
Super Bowl XLIII
2009
Steelers vs. Cardinals
Steelers
28-24 Steelers 27-23
Super Bowl XLII
2008
Patriots vs. Giants
Patriots
38-30
Giants
17-14
Super Bowl XLI
2007
Colts vs. Bears
Colts
38-27
Colts
29-17
Super Bowl XL
2006
Steelers vs. Seahawks
Steelers
24-19 Steelers 21-10
Super Bowl XXIX
2005
Patriots vs. Eagles
Patriots
47-31
Patriots
24-21
Super Bowl XXXVIII
2004
Patriots vs. Panthers
Patriots
23-20
Patriots
32-29
Video Games = Stats Can Be Predictive
Madden Super Bowl Winner Prediction Accuracy @ 71% (14 Years)
Madden Football Super Bowl Predictions vs. Actual Results, 2004-2017
Source: Electronic Arts, ESPN, USA Today, Forbes
KP INTERNET TRENDS 2017 | PAGE 127
Immersive Gaming Tools =
Improving Performance
Across Disciplines
KP INTERNET TRENDS 2017 | PAGE 128
Gamification =
Influencing Multiple Consumer Services
Education
Duolingo
Personal Finance
Acorns
Energy Conservation
Nest
Personal Health
Mango Health
Exercise
myfitnesspal
Food
Starbucks
Dating
Bumble
Advertising
Snapchat
Source: Top Row Images: Duolingo, Mango, Acorns, Nest, Bottom Row: iPhone in Canada (Starbucks), Consumer fitness news (Myfitnesspal),
5why.com (Bumble), Snapchat
KP INTERNET TRENDS 2017 | PAGE 129
Gamification =
Influencing Multiple Businesses
Military Training
Healthcare Research
Foldit
Pilot Training
Boeing
Healthcare Training
Simulated Surgery
Neuroscience
PTSD Therapy
Work Productivity
Betterworks
Source: Top Left Image: Fold.it, Top Middle Image: US Army Sgt 1st Class Caleb Barrieau, Top Right Image: Betterworks, Bottom Left Image:
Boeing, Bottom Center Image: Simulated Surgical Systems, Bottom Right Image: Archpaper.com
KP INTERNET TRENDS 2017 | PAGE 130
Gamification =
Influencing Complex Virtual Worlds + Real-World Simulations
Improbable in Real World
Simulate Cities + Power / Web Networks
Improbable in Gaming
Simulate Vast Virtual Worlds
Source: Worlds Adrift: Bossa Studios, Improbable
KP INTERNET TRENDS 2017 | PAGE 131
As Rapid Data Growth Continues =
Gaming Tools / Interfaces / Processors
Will Continue to
Organize + Drive Usefulness
KP INTERNET TRENDS 2017 | PAGE 132
Data Volume Growth Continues @ Rapid Clip
% Structured / Tagged (~10%) Rising Fast
0
20
40
60
80
100
120
140
160
180
Zetabtytes (ZB)2005:
0.1 ZB
2010:
2 ZB, 9%
2015:
12 ZB, 9%
% Structured / Tagged
Information Created Worldwide =
Expected to Continue Accelerating
2020:
47 ZB, 16%
2025E:
163 ZB, 36%
Source: IDC DataAge 2025 Study, sponsored by Seagate (3/17)
Note: 1 petabyte = 1MM gigabytes, 1 zeta byte = 1MM petabytes
KP INTERNET TRENDS 2017 | PAGE 133
GPU Processing Power Ramp Continues
NVIDIA Transistors, 1998-2016
Source: NVIDIA
Note: 1 GFLOP = 1B FLOPS, or "floating point operations per second."
0
1,000
2,000
3,000
4,000
5,000
6,000
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
Transistors (MM)Transistors
2002 = 5 GFLOPS
Battlefield 1942
2007 = 350 GFLOPS
Unreal Tournament 3
2016 = 10K GFLOPS
Paragon
KP INTERNET TRENDS 2017 | PAGE 134
Gaming Platforms =
Evolving @ High Speed
KP INTERNET TRENDS 2017 | PAGE 135
New Gaming Development Tools / Platforms =
Evolving to Continue to Build Virtual Worlds
Development Platforms
In-Game Sandboxes
Developers
Players
Have Virtual
Experiences
Build / Share /
Explore Creations
Build Virtual Worlds /
Share Ideas
Construct Virtual
Worlds with New
Dimensions
Build / Share
Creations
Distribute Content
Discover / Buy /
Share Content
Explore Virtual
Worlds
VR / AR Platforms
Gaming Marketplaces
Source: Unreal, Unity, HTC Vive, Oculus (Facebook) Microsoft, Minecraft, Roblox, Tencent, Steam (Valve), Sony
KP INTERNET TRENDS 2017 | PAGE 136
New Gaming Development Tools / Platforms =
Supporting Rapid Growth
0
1
2
3
4
5
6
7
Registered Developers (MM)0
10
20
30
40
50
60
May-16
Jun-16
Dec-16
Mar-17
MAU (MM)0
5
10
15
Peak Concurrent Users (MM)Unity = Registered Developers
Roblox = Monthly Active Users
Steam = Peak Concurrent Users*
Source: Unity, Roblox, Steam (Valve), Forbes, Venturebeat, Bloomberg
*Taken on the last available day of each month using waybackmachine.org.
KP INTERNET TRENDS 2017 | PAGE 137
eSports =
Expanding Gaming Ecosystem via
Fans / Spectators
KP INTERNET TRENDS 2017 | PAGE 138
eSports =
45 Year Evolution to Global Stage
1997
Red Annihilation
Quake Tournament =
Early eSports
Competition
2000
Electronic Sports
League + Korea
eSports Assn. =
Emerge as First
eSports Leagues
2006
Justin.tv Founded =
Precursor to
Twitch.tv
2016
League of Legends
2016 World
Championship =
43MM viewers
2009
League of Legends
Released =
Becomes One of
Most Played Strategy
Games (100MM MAU,
9/16)
2012
OnGameNet Begins
Broadcasting League
of Legends =
First Major Korean
Tournament on TV
Evolution of Global eSports
1972
Stanford University
AI Lab = First Ever
Gaming Tournament
(Spacewars)
1980
Atari Space Invader
Competition = Early
National Gaming
Tournament
Source: Spacewars image: Kokatu, Atari image: Ausretrogamer.com, Red Annihilation image: timetoast, Fortune (7/15), ESL logo: ESL, MLG,
KeSPA Logo: Team Liquid, MLG Logo: MLG, Halo 2 Logo: Pinterest, Justin.tv Logo: startupgenome.com, Twitch Logo: Twitch, Riot Games
(10/08), League of Legends Logo: League of Legends, Forbes (9/16), na.lolesports, OGN Logo: Twitch, eSports.inquirer.net, eSportsTV logo:
mb.cision.com, League of Legends World Championship
KP INTERNET TRENDS 2017 | PAGE 139
eSports =
People Watch What They Play
League of Legends Expands from Home to Staples Center, LA
(Worlds 2016 Finals = ~20K in Stadium + 43MM Online)
Source: Top left image: Mel Melcon Los Angeles Times, Bottom left image: Dexerto, Top right image: Red Bull, Bottom right image: YouTube
KP INTERNET TRENDS 2017 | PAGE 140
eSports Trending vs. Traditional Sports =
Very Strong with Younger Generations
Millennials = 27% 'Significant Preference' for eSports vs. 27% for Traditional Sports
Non-Millennials = 45% for Traditional Sports vs. 13% for eSports
Which do you prefer, your favorite traditional sport or favorite eSport?
21%
27%
13%
13%
13%
13%
19%
18%
20%
13%
15%
11%
34%
27%
45%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
All Responses
All Millennials
All Non-Millennials
% of Respondents that indicated at least a slight interest in eSportsSignificantly prefer favorite eSport
Slightly prefer favorite eSport
No preference
Slightly prefer favorite traditional sport
Significantly prefer favorite traditional sport
Source: L.E.K. Sports Survey, Digital Engagement Part One: Sports and the "Millennial Problem" (2/17)
KP INTERNET TRENDS 2017 | PAGE 141
eSports Monthly Viewers @ 161MM
+40% Y/Y & Accelerating
eSports Monthly Viewers, Global, 2012-2016
58
74
90
115
161
28%
22%
28%
40%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
0
20
40
60
80
100
120
140
160
180
2012
2013
2014
2015
2016
Y/Y Growth (%)eSports Viewers (MM)eSports Monthly Viewers
Y/Y Growth
Source: Newzoo Global eSports Market Report (2/17), Newzoo press release (1/16), Newzoo Casual Connect Europe Presentation (2/15)
*eSports Enthusiasts watch eSports once a month and/or participate in tournaments.
KP INTERNET TRENDS 2017 | PAGE 142
eSports League of Legends Championship Viewers @ 43MM
+19% Y/Y
League of Legends World Championship Global Viewership
Largest eSports Viewer Base
2
8
32
27
36
43
0
1
9
11
14
15
0
5
10
15
20
25
30
35
40
45
50
2011
2012
2013
2014
2015
2016
Viewers (MM)Total Unique Viewers
Peak Concurrent Viewers
Total Unique Viewers vs. Peak Concurrent Viewers
Source: Engadget, Polygon, The Verge, eSports Marketing, LoLeSports
KP INTERNET TRENDS 2017 | PAGE 143
eSports Monthly Viewers =
79% <35 Years Old29% Female
Monthly eSports Viewers by Age / Gender, Global, 2016
27%
53%
18%
2%
0
20
40
60
80
100
120
10-20
21-35
36-50
51-65
Global eSports Enthusiasts (MM)Male
Female
% of Total Monthly
eSports Viewers
Source: Newzoo 2017 Global eSports Market Report (2/17)
KP INTERNET TRENDS 2017 | PAGE 144
eSports (Like Sports) = Money Follows Viewers + Winners
Fan In-Game Purchases Boost Prize Pools
Prize Pool for The International (DOTA 2), 2011-2017
$1.6
$1.6
$2.9
$10.9
$18.4
$20.8
$10.7
$0
$5
$10
$15
$20
$25
2011
2012
2013
2014
2015
2016
2017 YTD
Prize Pool ($MM)Base Prize Pool
Compendium*
Source: ESPN, eSports Earnings, DOTA 2 (5/24/17)
Note: * The International Compendium represents 25% of in-game purchases during a promotional period leading up to the event. Players can
buy virtual items, levels, and other in-game content. As the total prize pool reaches different milestones all players who participated gain access
to more exclusive content. 2017 YTD as of 5/25/17.
KP INTERNET TRENDS 2017 | PAGE 145
Facebook = Expands
eSports Relationships with
ESL Streaming Deal, 5/17
NBA + Up with Take Two =
2K eSports League, 2/17
German Soccer Club,
FC Schalke 04 =
Acquires eSports
Team, Elements, 5/16
Partnerships + Investments =
Helping Bring eSports into Mainstream
Philadelphia 76ers =
Acquire eSports
Teams, Dignitas &
Apex, 9/16
Miami Heat = Invests
in eSports Team,
Misfits, 1/17
Expanding Connections with Sports / Media Platforms
Italian Soccer Club AS
Roma = Partners with
eSports Team, Fnatic, 2/17
Riot Games +
BAMTech = $300MM
6yr LoL Streaming
Rights, 12/16
Source: ESPN, Engadget, Yahoo Sports, Live Production, Dot eSports, Forbes
KP INTERNET TRENDS 2017 | PAGE 146
Gaming Experience =>
Technology
Leadership + Innovation?
KP INTERNET TRENDS 2017 | PAGE 147
Ten Years Ago (2007) =
A Stanford Professor Said
If you want to see what
business leadership may look like in
three to five years, look at what's
happening in online games.
- Byron Reeves, Professor of Communication, Stanford University, 6/07
Source: Byron Reeves
KP INTERNET TRENDS 2017 | PAGE 148
~Ten Years Later =
Entrepreneurs Often Fans of Gaming Experience
I like video games. In fact, that's what got me into software engineering when I
was a kid. I wanted to make money so I could buy a better computer so I could
play better video games.
- Elon Musk, CEO Tesla & SpaceX, 10/16
As a child I played a lot of Avalon Hill board games. And each board game is
actually a complex set of rules and circumstances So it was actually in fact my
childhood gaming for being able to build a model of what a game was that
was essentially the fundamental thing that informs my strategic sense.
- Reid Hoffman, Co-Founder of LinkedIn, 8/15
I do think this dynamic around kids growing up, building games, and playing
games, is an important one because I think this is how a lot of kids get into
programming. I definitely wouldn't have gotten into programming if I hadn't played
games.
- Mark Zuckerberg, CEO Facebook, 5/15
Source: Elon Musk: Forbes Interview (10/1/16), Reid Hoffman: Interview on the Tim Ferris Show (8/31/15), Mark Zuckerberg: Facebook Q&A
Session (5/14/15)
KP INTERNET TRENDS 2017 | PAGE 149
Perhaps Interactive Gaming
Evolution / Growth / Usage With
Related Data Collection / Analytics /
Real-Time Simulations + Engagement
Has Been Helping Prepare Society for
On-Going Rise of
Human-Computer Interaction?
KP INTERNET TRENDS 2017 | PAGE 150
1) Global Gaming = Mainstream / Evolving Rapidly / Still Early Days
2) Gaming Tools = Pervasive Online
3) Gaming Tools = Improving Human Performance
4) Gaming Platforms = Evolving @ High Speed
5) eSports = Expanding Gaming Ecosystem via Fans / Spectators
6) Gaming Experience => Technology Leadership + Innovation?
Interactive Games = Motherlode of
Tech Product Innovation + Modern Learning
KP INTERNET TRENDS 2017 | PAGE 151
MEDIA =
DISTRIBUTION DISRUPTION @
TORRID PACE
KP INTERNET TRENDS 2017 | PAGE 152
Digital Leaders =
Transforming Media With
Better User Experiences +
Lower PricesData + Scale
KP INTERNET TRENDS 2017 | PAGE 153
Music = Why Streaming?
Access / Choice / Discovery / Personalization / Mobile / Fewer Ads
Source: Goldman Sachs Research, BPI
Note: BPI Survey as of 12/15, n=1,000 (UK only). Questions: "Why did you decide to pay for a music streaming subscription?" and "Thinking
about music streaming, to you, how important are the following?"
9%
19%
21%
22%
24%
27%
29%
42%
Viewed Ad
Offline
Listening
Bundled
Recs from
Friends /
Family
Listening
Choice
Mobile
Access
Get Rid
of Ads
Free Trial
Convert
Reasons for Paying for Music
Streaming, 12/15
Importance of Streaming Product
Features, 12/15
0%
20%
40%
60%
80%
100%
Share
Playlists
Build
Playlists
Simultaneous
Music Videos
Curation
/ Recs
Keep Up
with Hits
Support
Artists
Multi-Device
Listening
New Music
Discovery
Size of
Catalog
Very
Fairly
Not much
Not at all
KP INTERNET TRENDS 2017 | PAGE 154
Video = Why Cord-Cutting?
Lower Price + Convenience
Source: TiVo Q4 2016 Video Trends Report
Note: Survey includes 18+ year olds in USA and Canada, n=3,079. Other categories omitted include "Not My Choice," "Share SVOD Login,"
"Moved In With New Roommate," "Other."
11%
13%
19%
27%
48%
80%
Bulk of Viewing is
Streaming Service
Original Content
Dropped Cable Upon
Moving / Relocating
Like to Binge Entire
Seasons via
Streaming
Use Antenna to Get
Basic Channels
Use an Internet
Streaming Service
Too Expensive
Reasons for Cutting Pay-TV Service, Q4:16
KP INTERNET TRENDS 2017 | PAGE 155
Digital Evolution of
Music + Video =
Ramping Rapidly
KP INTERNET TRENDS 2017 | PAGE 156
$0
$5
$10
$15
$20
1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015
Recorded Music Revenues ($B)Subscription & Streaming
Download & Synchronization
Physical
Source: Recording Industry Association of America
Note: "Subscription and Sttreaming" includes paid subscriptions (full and limited tier), SoundExchange, ad-supported streaming and other digital.
"Download & Synchronization" includes download single / album, kiosk, download music video, ringtone / ringback, and synchronization.
"Physical" includes LP / EP, vinyl single, 8-track, cassette (full / single), CD / CD single, music video, DVD audio and SACD.
Recorded Music = Revenue +11% After 16 Years of -4% Annual Average Growth
Subscription & Streaming @ 52% of Revenue vs. 0% Thirteen Years Ago, USA
Recorded Music Revenues by Format ($B), USA, 1973-2016
KP INTERNET TRENDS 2017 | PAGE 157
Source: Spotify
* Subscribers as of 3/2017, when Spotify announced they had reached the 50 million subscriber mark.
Spotify = Catalyst for Internet-Driven Evolution of Music Industry
0 50MM Paid Subscribers / 126MM MAUs in <9 Years
0
500
1,000
1,500
2,000
2,500
3,000
0
10
20
30
40
50
60
2008
2009
2010
2011
2012
2013
2014
2015
2016*
Spotify Global Revenue (MM)Spotify Paid Subscribers (MM)Spotify Paid Subscribers
Spotify Global Revenue
Spotify Subscribers (MM) & Revenue (MM), 2008 2016*, Global
Q4:16 Monthly ARPU = 5.80 ($6.10)
KP INTERNET TRENDS 2017 | PAGE 158
Source: Spotify, IFPI 2017 Global Music Report
* Subscribers as of 3/2017, when Spotify announced they had reached the 50 million subscriber mark.
Spotify = 20% of Global Music Industry Revenue vs. 0% in 2008
0%
5%
10%
15%
20%
25%
30%
0
10
20
30
40
50
60
2008
2009
2010
2011
2012
2013
2014
2015
2016*
Spotify as % of Global Music RevenueSpotify Paid Subscribers (MM)Spotify Paid Subscribers (MM)
Share of Global Music Revenue (%)
Spotify Subscribers (MM), 2008 2016*, Global
Q4:16 Monthly ARPU = 5.80 ($6.10)
KP INTERNET TRENDS 2017 | PAGE 159
Source: Spotify
Spotify = Users Listen to 41 Artists per Week, +40% (vs. 1/14) Owing to
Recommendation Engine (Data + Algorithms)
0
10
20
30
40
50
1/14
1/15
1/16
1/17
Unique Artists Listened to per WeekTime
Spotify
Unique Artists Listened to Per Week, Average, Global, 1/14-1/17
KP INTERNET TRENDS 2017 | PAGE 160
Network TV* Minutes Delivered = 2011 Top 5 Networks -10% Average
Netflix +669% Over 5 Years, USA
Source: Matthew Ball REDEF Original 3/14/16, Nielsen, Sandvine, Netflix, SNL Kagan, BTIG
Note: Inclusive of Broadcast + Basic Cable + Premium Cable, C7 Live + VOD + DVR. Does not account for multiple viewers (i.e. unique minutes
delivered) or TV everywhere (though note that even if every TV Everywhere stream started in 12/15 was completed and 1 hour long,
consumption would have increased national TV time by only 1.9%).
0
100
200
300
400
NBC
Universal
Disney
21st
Century
Fox
Netflix
CBS
Time
Warner
Viacom Discovery A&E
ESPN
Monthly Minutes Delivered (B)2010-2011 (through Feb)
2015-2016 (through Feb)
Monthly Minutes Delivered By Network Group, USA, 2010/11-2015/16
669%
11%
14%
30%
21%
35%
16%
33%
1%
1%
KP INTERNET TRENDS 2017 | PAGE 161
$0
$600
$1,200
$1,800
$2,400
$3,000
0
20
40
60
80
100
Netflix Quarterly Revenue ($MM) Netflix Paid Subscribers (MM)Netflix Paid Subscribers (MM)
Netflix Quarterly Revenue ($MM)
9/11
DVD /
Streaming Split
Source: Netflix
Note: Netflix subscription DVD service launched 9/1998. Data before Q3 2001 represents all subscribers because paid subscribers not broken
out. Netflix split streaming subs from DVD subs in Q3 2011; graph shows only streaming subs thereafter. ARPU shown ex-DVD.
Netflix = Catalyst for Internet-Driven Evolution of Video Industry
95MM Streaming Subscribers in 10 Years
Netflix Subscribers (MM) & Quarterly Revenue ($MM), 2/99 3/17, Global
Q1:17 Streaming ARPU per Month = $9.14
9/99
DVD Subscription
Launch
1/07
Streaming
Launch
KP INTERNET TRENDS 2017 | PAGE 162
0%
10%
20%
30%
40%
50%
0
20
40
60
80
100
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017*
Share of USA Home Entertainment Revenue (%)Netflix Paid Subscribers (MM)Netflix Paid Subcribers (MM)
Share of USA Home Entertainment Revenue (%)
Source: Netflix
Note: Share represented by Netflix domestic streaming revenue over total home entertainment revenue in USA. Domestic streaming not broken
out as individual segment until 2012. Netflix split streaming subs from DVD subs in Q3 2011; graph shows only streaming subs thereafter.
* Q1:17 represents Netflix annualized domestic streaming revenue figure. ARPU shown ex-DVD
Netflix Streaming =
From 0% to >30% of Home Entertainment Revenue in 10 Years, USA
Netflix Subscribers, 2009 2017*, Global
Q1:17 Streaming ARPU per Month = $9.14
9/11
DVD /
Streaming Split
1/07
Streaming
Launch
KP INTERNET TRENDS 2017 | PAGE 163
Google Pioneered Search / Find / Obtain (SFO) for Content + Products
Netflix + Spotify Pioneered Search / Find / Serve Up (SFS) for Media
Source: Netflix; Spotify; Michelle Ufford, "Data-Driven at Netflix", talk given at PASS 10/31/16; Gomez-Uribe and Hunt (both Netflix), "The Netflix
Recommender System: Algorithms, Business Value, And Innovation", ACM Transactions on Management Information Systems 6.4, 12/15
Note: Netflix estimated cost savings due to improved engagement and reduction of monthly churn, driving lower need for subscriber acquisition
cost in the future.
98MM Different Netflixes...
$1B cost savings / year
from recommendations (12/15)
126MM Different Spotifys
~5B Discover Weekly streams in
<1 year post-launch (5/16)
From Give to GetWith Data + Algorithms
KP INTERNET TRENDS 2017 | PAGE 164
Digital Evolution of
Music + Video =
Multiple Approaches
KP INTERNET TRENDS 2017 | PAGE 165
Facebook / Instagram / Snap =
Mobile Video Traffic Share Gainers Over 4 Years
Source: Sandvine Global Internet Phenomena Report (2H 2012 and 2016)
0%
5%
10%
15%
20%
25%
30%
35%
40%
YouTube Facebook Instagram
Snap
Netflix
iTunes
Google
Cloud
HTTP /
SSL -
Other
Other
2012
2016
Share of Downstream Video Traffic (%), North America, 2H 2016
KP INTERNET TRENDS 2017 | PAGE 166
Netflix / YouTube =
Fixed-Access Video Traffic Share Leaders
0%
5%
10%
15%
20%
25%
30%
35%
40%
Netflix YouTube Amazon
Video
iTunes
Hulu
Xbox One FacebookBitTorrent HTTP /
SSL -
Other
Other
2012
2016
Share of Downstream Video Traffic (%), North America, 2H 2016
Source: Sandvine Global Internet Phenomena Report (2H 2012 and 2016)
KP INTERNET TRENDS 2017 | PAGE 167
Facebook Platform MAUs, Global, Months Since Launch
Facebook (Facebook / WhatsApp / Messenger / Instagram) =
Video Ramping Across Platform
Source: Facebook, Instagram, Whatsapp, Financial Times, TechCrunch
0
500
1,000
1,500
2,000
2,500
0
12
24
36
48
60
72
84
96
108
120
132
144
156
MAU (MM)Months Since Founding
Instagram
Facebook
WhatsApp
Facebook Messenger
KP INTERNET TRENDS 2017 | PAGE 168
Snap = Ramping Original Short-Form Content
Snap 'Original Shows'
Source: Snap
Second Chance
8MM+ Views for 1st Episode, 5/17
Phone Swap
10MM+ Views for 1st Episode, 5/17
KP INTERNET TRENDS 2017 | PAGE 169
Generational Media Usage =
Chasm Increasing
Shifts to Internet-Enabled
Media Continue
KP INTERNET TRENDS 2017 | PAGE 170
7:16
7:12
7:06
4:14
2:44
2:17
Q4:16
Q4:15
Q4:14
Analog
Digital
Mobile Device Time per Day =
+2x Over 2 Years
Daily Time Spent by Media (Not De-Duped), USA, Q4:14-Q4:16
Source: Nielsen Total Audience Report Q4:16
Note: "Analog" includes Live / DVR / Time-shifted TV, DVR / time-shifted TV, AM / FM radio, DVD / Blu-ray, and game consoles. "Digital" includes
Multimedia devices (viewing on Apple TV, Roku, Chromecast, smartphone, computer etc. connected to TV), internet on PC, video on PC, app /
web on smartphone / tablet, and video on smartphone.
KP INTERNET TRENDS 2017 | PAGE 171
Mobile Device Time per Day =
18-24 Year-Olds @ 49% Digital65+ Year-Olds @ 13%, USA
9:49
9:09
7:17
5:42
4:35
1:30
4:41
5:19
4:42
4:27
65+
50-64
35-49
25-34
18-24
Analog
Digital
Daily Time Spent by Media & Age Bracket (Not De-Duped), USA, Q4:16
Source: Nielsen Total Audience Report Q4:16
Note: "Analog" includes Live / DVR / Time-shifted TV, DVR / time-shifted TV, AM / FM radio, DVD / Blu-ray, and game consoles. "Digital" includes
Multimedia devices (viewing on Apple TV, Roku, Chromecast, smartphone, computer etc. connected to TV), internet on PC, video on PC, app /
web on smartphone, and video on smartphone.
KP INTERNET TRENDS 2017 | PAGE 172
Traditional Cable Conundrum =
Channels + Consumer Prices +
Programming Costs Rising
Subscribers Falling
KP INTERNET TRENDS 2017 | PAGE 173
Pay TV Household Growth = -1.3% Average for Last 12 Quarters
While Programming Costs >2x+ since 2006
Source: Nielsen Total Audience / Cross Platform Reports, US Census Bureau, St. Louis Federal Reserve FRED Database
Note: Pay TV households represented by Nielsen "Cable Plus" metric, which includes households who receive television via Wired Cable (No
Telco), Telco, or Satellite. "Programming Costs" includes total program and production costs for Cable and Other Subscription Programming
firms, 2006-2015, as per US Census Services Annual Survey for Employer Firms ($25B in 2015, up from $12B in 2006).
Pay TV Households (MM), USA, 2010-2016
(5%)
(3%)
(1%)
1%
3%
5%
60
70
80
90
100
110
120
Q1:10Q2:10Q3:10Q4:10Q1:11Q2:11Q3:11Q4:11Q1:12Q2:12Q3:12Q4:12Q1:13Q2:13Q3:13Q4:13Q1:14Q2:14Q3:14Q4:14Q1:15Q2:15Q3:15Q4:15Q1:16Q2:16Q3:16Q4:16% Y/Y GrowthTotal TV Channels Received in USAPay TV Households (MM)
% Y/Y Growth
KP INTERNET TRENDS 2017 | PAGE 174
# TV Channels Watched <10% of Channels Received
Pay TV ARPU 10-15x > Netflix
Source: Nielsen, Matthew Ball & Tal Shachar, REDEF Original 3/9/16, DirecTV, AT&T, Charter, Dish Network, Comcast
Note: TV channel data as of mid-year. DirecTV ARPU calculated by dividing the 2016 Video Entertainment revenue by the average number of Linear Video Connections
during 2016. Charter ARPU calculated by dividing 2016 Video revenue by average Video Residential Primary Service Units during 2016. Dish Network ARPU calculated
by multiplying the 2016 Pay-TV Average Monthly Revenue per Subscriber by 12. Comcast ARPU calculated by dividing the 2016 Residential Video revenue by the
average Video Customers in 2016. Netflix ARPU is based off the Global Streaming revenue and average subscribers in 2016. All estimates are global.
Average TV Channels Received vs.
Watched per Household, USA, 2008-2016
0%
5%
10%
15%
20%
25%
0
50
100
150
200
250
% WatchedTotal TV Channels Received in USATV Channels Received
% Channels Watched
$103
$997
$1,064
$1,131
$1,439
Netflix
Comcast
Dish
Charter
DirecTV
Annual ARPU, Selected Platforms, 2016
Pay TV
Digital Platforms
KP INTERNET TRENDS 2017 | PAGE 175
Digital Subscriptions =
Rising Owing to Massive
User Experience Improvements
On-Demand / A La Carte Selection +
Choice / Personalization / Payment
Systems / 2-Way UGC / Mobile...
KP INTERNET TRENDS 2017 | PAGE 176
Media Evolution (1950-2017) =
Market of Millions Market of One x Millions
Source: Amanda Lotz, The Television Will Be Revolutionized, New York: NYU Press, 2007, Wikimedia Commons, Google Image Commons,
Crunchyroll, Shudder, Fandor, Seeso, Cheddar, Fullscreen
Cater to Sub-Genres /
Power Users /
A La Carte + Subscription
Network Era
1950s-1980s
Cable Era
1980s-2010s
Digital Era
Current
Broad Genres /
Focus on Programming /
Limited Bundle Choices
Cater to All /
High Viewership /
No Personalization
Digital Distributors
Digital Studios
KP INTERNET TRENDS 2017 | PAGE 177
Media = Distribution Disruption @ Torrid Pace
1) Digital Leaders = Transforming Media With Better User Experiences
+ Lower PricesData + Scale
2) Generational Media Usage = Chasm Increasing as Shifts to
Internet-Enabled Media Continue
3) Traditional Cable Conundrum = Channels + Consumer Prices +
Programming Cost RisingSubscribers Falling
4) Digital Subscriptions = Rising Owing to Massive User Experience
Improvements (On-Demand / Selection + Choice / Personalization /
Payment Systems / 2-Way UGC / Mobile...)
KP INTERNET TRENDS 2017 | PAGE 178
THE CLOUD =
ACCELERATING CHANGE ACROSS
ENTERPRISES
ALEX KURLAND @ KLEINER PERKINS
KP INTERNET TRENDS 2017 | PAGE 179
1) Cloud Adoption = Reaching New Heights +
Creating New Opportunities
2) Enterprise Software = Customer Expectations
Mirroring Those of Consumer Apps
3) Security = More Applications More Vulnerabilities
The Cloud = Accelerating Change Across Enterprises
KP INTERNET TRENDS 2017 | PAGE 180
Cloud Adoption =
Reaching New Heights +
Creating New Opportunities
KP INTERNET TRENDS 2017 | PAGE 181
Public + Private Clouds = Approaching Traditional Data Center Spend
+37% to $36B vs. 2014
76%
72%
67%
63%
14%
17%
20%
22%
9%
11%
13%
15%
0%
25%
50%
75%
100%
2013
2014
2015
2016
% of Total IT Infrastructure SpendIT Infrastructure Spend, Global, 2014-2016
Traditional Data Center
Public Cloud
Private Cloud
Source: IDC Worldwide Quarterly Cloud IT Infrastructure Tracker; Gartner; CloudHealth estimates
KP INTERNET TRENDS 2017 | PAGE 182
Public Cloud Adoption Trends =
AWS Maintains LeadAzure + Google Rising
57%
20%
10%
7%
57%
34%
15%
8%
AWS
Azure
Google
Cloud
IBM
2016 2017
Public Cloud Adoption, 2016 vs. 2017
% of Respondents Running Applications
57%
34%
15%
8%
17%
21%
17%
9%
10%
12%
13%
8%
AWS
Azure
Google Cloud
IBM
Running Apps
Experimenting
Planning to Use
Public Cloud Adoption, 2017
% of Respondents Running, Experimenting, or
Planning to Use Applications
Source: Rightscale 2017 State of the Cloud Report
Note: Based on survey of IT Professionals, n=1,002.
KP INTERNET TRENDS 2017 | PAGE 183
Cloud Concerns = Shifting from Data Security + Cost Uncertainty
Vendor Lock-In + Compliance / Governance
42%
38%
33%
21%
21%
18%
14%
7%
35%
21%
19%
27%
14%
20%
18%
22%
Data Security
Uncertainty of
Costs and
Savings
Loss of Control
(Upgrades,
Timing of
Backups)
Compliance /
Governance
Reliability (SLA
Requirements)
Data Portability
and Ownership
Software
Compatability
Lock-In (ability
to change
vendors)
2012
2015
Share of Respondents Citing Criteria as Top-Three Concern, USA,
2012-2015
Source: Bain Cloud Computing Survey, 2015 (n=347); Morgan Stanley AlphaWise Survey of IT Managers (n=304)
KP INTERNET TRENDS 2017 | PAGE 184
Cloud Evolution / Tools = Paving Way for
Innovation Across Infrastructure Landscape
Containers / Microservices =
Simplify software development process / improve consistency between testing
& production environments / reduce complexity of managing & updating apps
due to modular approach
Edge Computing =
Pushing compute away from centralized nodes & closer to sources of data
addresses many IT challenges when running data-centric workloads in cloud
reduces latency / can have security + compliance benefits
Elastic Analytical Databases =
Likes of Google BigQuery / Snowflake / AWS Redshift Spectrum nearly
infinitely scalable / usage based + have minimal maintenance requirements
New Methods of Software Delivery =
APIs / Browser Extensionscreating new wave of capabilities (+ companies)
for both companies and end users
Source: Lloyd Tabb, Looker Founder & CTO; Happiest Minds; Azuqua; TheServerSide; Forbes
KP INTERNET TRENDS 2017 | PAGE 185
New Cloud Companies Emerging
Providing Elegant + Intuitive Experiences for End Users
Rubrik
Managing data across cloud & on-prem infrastructure,
approaching $100MM in annualized bookings
Stripe
Processing billions of transactions a year across 100K+
businesses in 100+ countries
Looker
Empowering data analysis for 40K users across every
department, each averaging 2 new queries every day
CloudHealth
Actively managing more than 1.3MM policies globally
for hybrid & multi-cloud environments
Source: Company-provided & publicly available data; Snipcart
KP INTERNET TRENDS 2017 | PAGE 186
Enterprise Software =
Customer Expectations
Mirroring Those of Consumer Apps
KP INTERNET TRENDS 2017 | PAGE 187
Enterprise Software (2000 2017) = Users Expect Products to be as
Well Designed / Easy-to-Use / Reliable as Consumer Apps
Perpetual, On-Premise Software Cloud-Based SaaS Apps Mobile-First Smart Apps
2000
2017
Delivery Method
On-Prem
Cloud-based
Pricing
Perpetual License
Subscription
UX
Generic
Personalized
Intelligence
Constrained
Unlimited (AI / ML)
Growth Engine
Sales
Product
Purchase Decision
Top-Down
Bottoms-Up
Measure of Engagement &
Customer Satisfaction
N/A
DAUs / MAUs / NPS
KP INTERNET TRENDS 2017 | PAGE 188
Design = Increasingly Core to Enterprise R&D
End-Users Demanding Consumer-Quality Product Experiences
Change in Designer : Developer Ratio, Selected Enterprises, 2010-2017
Source: Company data, Figma
Note: Ratios for entire orgs, unless noted otherwise. Atlassian historical ratio from 2012; Dropbox data for product org only; IBM historical ratio
from 2012, data for product org only; Intercom data for product org only; LinkedIn historical ratio from 2010.
2010 - 2012
2017
1 designer :
1 designer :
25 developers
9 developers
1 designer :
1 designer :
10 developers
6 developers
1 designer :
1 designer : 8 developers
72 developers On Mobile 1 designer : 3 developers
1 designer :
5 developers
N/A
1 designer:
1 designer :
11 developers
8 developers
N/A
KP INTERNET TRENDS 2017 | PAGE 189
Security =
More Applications More Vulnerabilities
KP INTERNET TRENDS 2017 | PAGE 190
Cloud-Enabled App Use in Enterprises = Rising Rapidly
Cheaper to Build / Easier to Adopt / Harder to Secure
Avg. # of Cloud Apps Used by Vertical,
Global, April 2017
Avg. # of Cloud Services used by Category,
Global, April 2017
This has serious security & compliance implications...
94% of all cloud apps used are not "enterprise-ready,"
per Netskope
1,206
1,170
1,092
907
893
0
200
400
600
800
1,000
1,200
1,400
Retail,
Restaurants,
& Hospitality
Financial
Services,
Banking,
& Insurance
Manufacturing Healthcare &
Life Sciences
Technology
& IT services
Avg. Cloud Services Used per EnterpriseCategory
# Per
Enterprise
% Not Enterprise
Ready
Marketing
91
97%
HR
90
96%
Collaboration
70
87%
Finance /
Accounting
60
95%
CRM / Sales
43
94%
Software
Development
41
96%
Productivity
37
95%
Social
30
91%
Cloud
Storage
27
72%
IT Service /
Application
Management
25
98%
Source: Netskope April 2017
Note: 461 cloud apps in April 2017, one year ago = average of 917 from Feb-16 report & 935 from Jun-16 report; "Not enterprise ready" =
received a rating of "medium" or below in the Netskope Cloud Confidence Index.
KP INTERNET TRENDS 2017 | PAGE 191
Network Breaches = Increasingly Caused by Email Spam / Phishing
Spam +350% vs. Q1:15 Monthly Average
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
Spam Without Malicious Attachments
Spam With Malicious Attachments
Change in Amount & Type of Spam, Global, 2015-2016
Indexed to Q1:15 Monthly Average
Source: AntiPhishing Working Group Phishing Activity Trends Report - Q4 2016; IBM X-Force Threat Intelligence Index 2017
% Change in Spam (Indexed to Q1:15 Monthly Average)
KP INTERNET TRENDS 2017 | PAGE 192
Cyber Threats Severity Rising = 10MM+ Identities Exposed in
15 Breaches in 2016vs. 11 in 2014
0%
25%
50%
75%
100%
2012
2013
2014
2015
2016
% of Internet Traffic by Source% Human
% Bot
0
2
4
6
8
10
12
14
16
2014
2015
2016
# Breaches with 10MM+ Identities ExposedBreaches with 10MM+ Identities Exposed,
Global, 2014-2016
% of Internet Traffic by Source,
Global, 2012-2016
Source: Incapsula 2016 Bot Traffic Report (100k Randomly Selected Domains); 2017 Verizon Data Breach Investigations Report
KP INTERNET TRENDS 2017 | PAGE 193
CHINA INTERNET =
GOLDEN AGE OF
ENTERTAINMENT + TRANSPORTATION
*Disclaimer The information provided in the following slides is for informational and illustrative purposes only. No representation or warranty, express or implied, is given and no
responsibility or liability is accepted by any person with respect to the accuracy, reliability, correctness or completeness of this Information or its contents or any oral or written
communication in connection with it. Hillhouse Capital may hold equity stakes in companies mentioned in this section. A business relationship, arrangement, or contract by or among any
of the businesses described herein may not exist at all and should not be implied or assumed from the information provided. The information provided herein by Hillhouse Capital does
not constitute an offer to sell or a solicitation of an offer to buy, and may not be relied upon in connection with the purchase or sale of, any security or interest offered, sponsored, or
managed by Hillhouse Capital or its affiliates.

KP INTERNET TRENDS 2017 | PAGE 194
China Macro =
Positive Trends
KP INTERNET TRENDS 2017 | PAGE 195
48%
49%
50%
51%
52%
53%
90
95
100
105
110
115
1/14
4/14
7/14 10/14 1/15
4/15
7/15 10/15 1/16
4/16
7/16 10/16 1/17
Manufacturing PMI Index Consumer Confidence IndexChina Consumer Confidence Index (LHS)
China Manufacturing PMI (RHS)
China Macro =
Confidence Improving Since CH2:16
Source: China National Bureau of Statistics, Bernstein Research
Consumer Confidence Index & Manufacturing PMI Index, China, 1/14 3/17
KP INTERNET TRENDS 2017 | PAGE 196
China Macro =
Service Sector @ 52% GDP Share vs. 23% Thirty-Five Years Ago
0%
10%
20%
30%
40%
50%
60%
1961
1966
1971
1976
1981
1986
1991
1996
2001
2006
2011
2016
% of GDPService Sector Output as % of Nominal GDP, China, 1961 2016
Source: China National Bureau of Statistics, Morgan Stanley Research
Note: Service sector defined as all industries outside of agriculture, forestry, animal husbandry and fishery industries (except
support services to agriculture, forestry, animal husbandry and fishery industries), mining (except auxiliary activities of mining),
manufacturing (except repairs for metal products, machinery and equipment), production and supply of electricity, steam, gas and
water, and construction.
KP INTERNET TRENDS 2017 | PAGE 197
5%
21%
48%
0%
10%
20%
30%
40%
50%
2005
2010
2016
% of MSCI China Market CapChina Macro = Private (Non-SOEs) Enterprises
Increasingly Driving Wealth Creation + Economic Growth + Jobs
Source: Morgan Stanley Research, MSCI
*SOE = State Owned Enterprise.
Private Enterprise (Non-SOE*) % Share of MSCI China Weighted Market Cap
KP INTERNET TRENDS 2017 | PAGE 198
China Macro =
Technology Companies Lead Public Market Wealth Creation
0%
20%
40%
60%
80%
100%
Telecommunication Services
Energy
Utilities
Industrials
Consumer Staples
Materials
Overall MSCI China
Financials
Consumer Discretionary
Health Care
Information Technology
2016
2005
Source: Morgan Stanley Research, MSCI
*SOE = State Owned Enterprise.
Private Enterprise (Non-SOE) % of MSCI China Market Cap by Sector,
2005 vs. 2016
KP INTERNET TRENDS 2017 | PAGE 199
China Internet Users + Usage =
Healthy User Growth
Usage Outpacing Users
KP INTERNET TRENDS 2017 | PAGE 200
Mobile Internet Users & Y/Y Growth, China, 2008 2016
Source: CNNIC
Note: Internet user data is as of year-end.
0%
10%
20%
30%
40%
50%
60%
70%
0
100
200
300
400
500
600
700
2008
2009
2010
2011
2012
2013
2014
2015
2016
% Y/Y GrowthChina Mobile Internet Users (MM)China Mobile Internet Users
Y/Y Growth
China Mobile Internet Users =
@ ~700MM, +12% Y/Y vs. 11% in 2015
KP INTERNET TRENDS 2017 | PAGE 201
Source: Hillhouse estimates based on daily media time spent data from ZenithOptimedia and mobile data from
QuestMobile
0%
15%
30%
45%
60%
75%
90%
0
500
1,000
1,500
2,000
2,500
3,000
2012
2013
2014
2015
2016
% Y/Y GrowthDaily Time Spent (Hours MM)Mobile Internet Time Spent
Mobile Internet Time Spent Y/Y
Mobile Internet User Y/Y
China Mobile Internet Usage Outpacing User Growth =
+30% Y/Y for Usage+12% for Users
Estimated Mobile Internet Daily Time Spent, China,
2012 - 2016
KP INTERNET TRENDS 2017 | PAGE 202
China Entertainment =
Online Innovation Driving
Robust User + Usage +
Monetization Growth
KP INTERNET TRENDS 2017 | PAGE 203
Source: Zenith Optimedia
0%
10%
20%
30%
40%
50%
60%
70%
0
50
100
150
200
250
300
350
2012
2013
2014
2015
2016
Internet as % of Media ConsumptionDaily Media Consumption (Minutes)Radio
TV
Magazine
Newspaper
Desktop Internet
Mobile Internet
Internet as % of
Total Media
China Media =
Internet @ 55% of Time SpentMobile > TV (2016)
Average Daily Media Consumption Minutes by Medium, China,
2012 - 2016
KP INTERNET TRENDS 2017 | PAGE 204
0
500
1,000
1,500
2,000
2,500
3,000
3,500
11/1412/141/152/153/154/155/156/157/158/159/1510/1511/1512/151/162/163/164/165/166/167/168/169/1610/1611/1612/161/172/173/174/17Average Daily Hours (MM)WeChat
QQ
Tencent Games
Tencent Video
Tencent News
Tencent Music
Tencent Other
UC Browser
Weibo
Taobao / Tmall
Youku
Alibaba Other
iQiyi
Mobile Baidu
Baidu Other
Toutiao
NetEase
All Other
TencentBaiduAlibabaChina Mobile Internet Daily Hours By App, 11/14 4/17
China Entertainment = Key Driver of Mobile Time Spent
eCommerce + Games = Monetize Best Per Time Spent
Source: QuestMobile
Note: Only top 100 apps by time spent are categorized by company affiliation. Tencent, Alibaba and Baidu
affiliates include strategically invested companies.
KP INTERNET TRENDS 2017 | PAGE 205
China Online Entertainment = Consumers Increasingly Willing to Pay
Led by Games + Livestreaming + Video
$0
$10
$20
$30
$40
2011
2012
2013
2014
2015
2016
Annual Revenue ($B)Online Game
Online Video
Online Literature
Livestreaming
Digital Music
Source: Game industry data per per Newzoo and Hillhouse estimates, excludes console or PC hardware related
revenue. Online video data per iResearch (China) and Hillhouse estimates (USA), excludes advertising related
revenue. Digital music data (excl. advertising) per iResearch (China) and RIAA (USA). Livestreaming (China)
data per Hillhouse estimates. eBook data per Hillhouse estimates (China) and AAP and Hillhouse estimate
(USA)
$0
$10
$20
$30
$40
2011
2012
2013
2014
2015
2016
Annual Revenue ($B)Online / Console Game Online Video
eBook
Digital Music
Online Entertainment User-Pay
Revenue By Vertical, China, 2011-2016
Online Entertainment User-Pay
Revenue By Vertical, USA, 2011-2016
KP INTERNET TRENDS 2017 | PAGE 206
$0
$5
$10
$15
$20
$25
$30
2012
2013
2014
2015
2016
2017E
Video Game (excl. Hardware) Revenue ($B)China
USA
EMEA
Asia (ex. China)
Source: Newzoo
* Excluding console / gaming PC hardware revenue.
Global Interactive Game Revenue =
China #1 Market in World* > USA (2016)
Interactive Game Software Revenue by Region, Global, 2012 2017E
KP INTERNET TRENDS 2017 | PAGE 207
Tencent Honor of Kings
Mobile Multiplayer Online Battle Arena
(MOBA) Leader
50MM+ DAU, $3B+ Annualized Bookings
Driven by Social + Simple UI +
Constant Product Improvement
NetEase
Portfolio of Leading Mobile
Massively Multiplayer Online Role Playing
Games (MMORPGs)
Driven by Mobile First Mover Advantage +
IP + Social Design + Quality Production
China Online Gaming =
Tencent + NetEaseMobile MOBA + MMORPG Game Leaders
Source: Tencent, NetEase
KP INTERNET TRENDS 2017 | PAGE 208
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
$4,000
Revenue ($MM)PC Mobile
China Online Gaming =
Tencent + NetEase Driving Mobile Innovation + Revenue
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
$4,000
Revenue ($MM)PC Mobile
Source: Tencent, NetEase, Goldman Sachs Investment Research
Note: Assuming 1USD = 6.9RMB.
NetEase Online Game Revenue,
PC vs. Mobile, Q1:14-Q1:17
Tencent Online Game Revenue,
PC vs. Mobile, Q1:14-Q1:17
KP INTERNET TRENDS 2017 | PAGE 209
Diverse Live Content Type
Singing / Dancing /
Talk Show / Game Play
Local / Social
Nearby Livestreams /
Chat & Add Friends
China Livestreaming =
High Consumer Engagement + Willingness to Pay
Interactive / Social /
Gamified
Like / Chat with Hosts & Audience /
Buy Virtual Gifts to Support
Performers
20+ Virtual Gift
Categories
priced from Rmb0.01
Source: Hillhouse research
KP INTERNET TRENDS 2017 | PAGE 210
$0.00
$0.20
$0.40
$0.60
Online Music
Radio
Online Video
TV
Online Games
Livestreaming
Source: Hillhouse estimates based on Newzoo, iResearch, Questmobile, and select company disclosures
Note: Revenue data includes subscription, advertising and paid download revenue streams.
China Livestreaming =
Compelling Monetization
Estimated Revenue per Hour, China, 2016
KP INTERNET TRENDS 2017 | PAGE 211
China On-Demand Transportation =
#1 Global Market
Cars + Bikes
KP INTERNET TRENDS 2017 | PAGE 212
China On-Demand Transportation (Cars + Bikes) = Global Leader @...
~67% Global Share (10B+ Annualized Trips, + >2x Y/Y)
Source: Hillhouse Capital estimates, include on-demand taxi, private for-hire vehicles, as well as on-demand for-
hire motorbike and bike trips booked through smartphone apps
On-Demand Transportation Trip Volume by Region, Global, Q1:13 Q1:17
0
1,000
2,000
3,000
4,000
1Q13
1Q14
1Q15
1Q16
1Q17
Quarterly Completed Trips (MM)ROW
SE Asia
India
EMEA
N. America
China Bike
China Car
Q1:13
Q1:14
Q1:15
Q1:16
1:17
KP INTERNET TRENDS 2017 | PAGE 213
China On-Demand Bike Sharing =
Mobile Innovation Driving Significant Usage Ramp
In-Bike GPS +
Smartphone
Bike Sharing Without
StationsLocation-Based Virtual
Red Envelope Drives Utilization
QR Code + Mobile
Payment
Easy Unlock & Low Friction
Payment
Ubiquity + Low Cost
(1/~$0.15 per 30 min) +
Convenience
Mass Adoption &
Bike Utilization
Mobike Product Innovation
Source: Mobike
KP INTERNET TRENDS 2017 | PAGE 214
0%
20%
40%
60%
80%
100%
120%
0
5
10
15
20
25
7/16
8/16
9/16
10/16
11/16
12/16
1/17
2/17
3/17
% M/M GrowthChina Bike Sharing MAU (MM)China On-Demand Bike Sharing MAUs
M/M Growth
Source: TrustData
Note: Dip in M/M growth rate in 1/17 was driven by Chinese New Year.
China On-Demand Bike Sharing =
@ 20MM+ MAU100%+ M/M Accelerating Growth
China On-Demand Bike Sharing MAU, 7/16 3/17
KP INTERNET TRENDS 2017 | PAGE 215
China On-Demand Bike Sharing = High Frequency
2/3 Users Ride 3+ Times Per Week
Commute
50%
Leisure /
Exercise
29%
Shopping
12%
Business
3%
School
1% Other
5%
<1x
9%
1-2x
25%
3-5x
32%
6-10x
18%
10+
16%
Source: Transport Commission of Shenzhen Municipality study on bike sharing, based on operating data from
four participating companies and survey data between 10/16 and 3/17, n=16,546
Highlights from Shenzhen Municipality On-Demand Bike Sharing Study, 5/17
On-Demand Bike Trips per Week
Purpose of On-Demand Bike Trips
KP INTERNET TRENDS 2017 | PAGE 216
On-Demand Bike Sharing =
Positive Environmental Impact + High Customer Satisfaction
Source: Transport Commission of Shenzhen Municipality study on bike sharing, based on operating data from
four participating companies and survey data between 10/16 and 3/17, n=16,546
* Based on following assumptions 250k reduction in daily private car trips, avg. trip length of 10km, avg. fuel
consumption of 6.9 L/100km, avg. CO2 emission of 2kg/L of fuel.
Highlights from Shenzhen Municipality On-Demand Bike Sharing Study, 5/17
11MM
Registered Users in
Shenzhen, China
530K
Available Bikes
2.6MM
Daily Trips
5
Trips per Available Bike per
Day
50%
On-Demand Bike Trips Serving as Last-Mile
Connection to Public Transit Trips
10%
Bike Trips Replacing Private Car Driving Trips
100K+ Tons
Reduction in Annual CO2 Emission*
95%
Respondents Support Continued Development
of Bike Sharing
KP INTERNET TRENDS 2017 | PAGE 217
China On-Demand Bike Sharing = Complements On-Demand Cars
@ 75% Shorter Trip Distance & 80% Lower Cost per Mile
On-Demand Car Share
(Didi)
On-Demand Bike
Share (Mobike / Ofo)
Average Trip Distance
8 KM
~5 Miles
2 KM
1.2 Miles
Average Trip Cost
20 RMB
~3 USD
~1 RMB
~0.15 USD
Cost per Km
~2.50 RMB
~0.50 RMB
Cost per Mile
~0.60 USD
~0.12 USD
Source: On-demand car share data per Hillhouse estimate. On-demand bike share data per Transport
Commission of Shenzhen Municipality study on bike sharing, based on operating data from four participating
companies and survey data between 10/16 and 3/17, n=16,5466.92
KP INTERNET TRENDS 2017 | PAGE 218
China Mobile Payment
Infrastructure =
Enabling Rapid Growth +
Monetization of Internet Usage
KP INTERNET TRENDS 2017 | PAGE 219
China Mobile Payment Volume =
+2x Y/Y to $5T+ Led by AliPay + WeChat Pay
Source: Analysys
*Excludes certain P2P and transfer payments. Assume constant FX rate of 1USD = 6.9RMB.
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
2012
2013
2014
2015
2016
China Mobile Payment Volume ($B)AliPay
54%
WeChat
Pay
40%
Others
7%
China Mobile Payment Volume,
2012 - 2016
China Mobile Payment Market
Share*, Q1:17
KP INTERNET TRENDS 2017 | PAGE 220
China Mobile Payments = Convenience vs. Cash & Bank Cards
Small Transactions Growing Especially Fast (<100RMB / $15)
Source: PCAC, Bernstein Analysis
Size of Mobile Payment Transactions,
2012 - 2016
Reasons for Using Mobile Payments,
2012 - 2016
0%
20%
40%
60%
80%
100%
2014
2015
2016
0%
20%
40%
60%
80%
100%
2014
2015
2016
KP INTERNET TRENDS 2017 | PAGE 221
AliPay + WeChat Pay on Mobiles =
Digitizing Micro Payments On + Offline
~$0.15 for On-Demand
Bike
~$0.15 for On-Demand
Mobile Recharge
$0.01+ for Article /
Author Tipping
$0.01+ for Livestreaming
Tipping
$0.50+ for Street Food
Source: Hillhouse estimates
KP INTERNET TRENDS 2017 | PAGE 222
0bps
100bps
200bps
300bps
Cash*
WeChat /
AliPay
China Bank
Cards
USA Debit
Card
USA Credit
Card
PayPal
Merchant Discount Rate (basis points)China Mobile Payments = Low Relative Cost
Helped by Regulated Interchange Rates
Source: Hillhouse estimates based on published rate schedule, JPMorgan Research estimates and transaction
take rate for PayPal in 2016
*Cash payment there is no merchant discount rate, ~40bps of marginal cost of processing cash payment is an
estimate per European Commission study in 2014. USA debit and credit card merchant discount rate is an
estimated offline average, online (card-not-present) merchant discount rate is higher.
Average Merchant Discount Rate,
Basis Points (100bps = 1%)
KP INTERNET TRENDS 2017 | PAGE 223
Payment
Wealth
Management
Financing
Insurance
Credit Rating
/ History
Ant
Financial
451MM
Annual Active
Users1
>300MM
Cumulative
Users2
>100MM Cumulative
Consumer Finance
Users3, >5MM
Cumulative SME
Borrowers4
380MM
Cumulative
Users5
130MM
Cumulative
Users6
Tencent
>600MM
MAU7
>80MM
Cumulative
Users8
>30MM Cumulative
Users9
JD
Finance
119MM
Annual Active
Users10
>20MM
Cumulative
Users11
>30MM
Cumulative Users11
168MM
Cumulative
Users11
>35MM
Cumulative
Users11
Mobile Payments = Gateway for China Internet Leaders to
Become Diversified Financial Services Platforms
Source: Alibaba / Ant Financial, Tencent, JD Finance
1Number of users of Alipay with one or more successful transactions in 2015; 2As of 3/16; 3As of 4/17; 4As of
1/17; 5As of 2015; 6As of 3/16; 7For 12/16; 8As of 11/16; 9As of 5/17; 10As of 12/16; 10Number of users of JD Pay
with one or more successful transactions in 2016; 11As of 5/17
YU'E BAO

ANT CASH NOW
ANT CREDIT PAY
KP INTERNET TRENDS 2017 | PAGE 224
China eCommerce +
Advertising =
Innovation + Growth
KP INTERNET TRENDS 2017 | PAGE 225
China eCommerce = Strong Growth
+24% Y/Y @ $681B GMV71% Mobile
0%
100%
200%
300%
400%
$0
$200
$400
$600
$800
2012
2013
2014
2015
2016
% MobileY/YGrowthB2CeCommerceGMV($B)Desktop
Mobile
Mobile Y/Y Growth
Source: iResearch
Note: Assuming constant FX 1USD = 6.9RMB
China B2C eCommerce Gross Merchandise Value ($B),
Desktop vs. Mobile, 2012 - 2016
KP INTERNET TRENDS 2017 | PAGE 226
China B2C eCommerce @ 15% of Retail Sales
Penetration Ramping Faster Than Peers
0%
5%
10%
15%
20%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
% eCommercePenetrationKorea
UK
China
USA
Germany
Japan
France
Brazil
B2C eCommerce as % of Retail Sales by Country,
2002 - 2016
Source: Euromonitor
KP INTERNET TRENDS 2017 | PAGE 227
Alibaba = Massive Scale + Engagement + Innovation
Source: Alibaba
Note: MAU data as of 3/17, DAU/MAU ratio data refers to mobile Taobao app, as of 5/16. Daily time spent per DAU
limited to Taobao app, per QuestMobile data in 4/17. GMV generated from recommendations data are indexed,
4/15 vs. 4/16.
Taobao App with
Livestreaming / Microblog /
Personalization
Cainiao Logistics
Smart Label / Routing
GMV Generated from
Recommendations,
2015-2016
2015
2016
507MM Mobile MAUs, +24% Y/Y41% DAU/MAU Ratio
24+ Minutes Daily Time Spent per User
KP INTERNET TRENDS 2017 | PAGE 228
JD.com = World Class Fulfillment + Delivery91% / 58% Orders*
Delivered Within 2 Days / 1 Day, Up from 68% / 47% Four Years Ago
Source: JD.com
*Orders exclude third party sellers. **Defined as JD's 211 program any orders received by 11am will be delivered on the same day, and any orders received by
11pm will be delivered by 3pm on the following day. Bulk of orders are delivered within 3-18 hours. Customers also can request that orders placed by 3pm be
delivered in the evening on the same day in selected cities. There is no extra charge for delivery under the 211 program for orders that satisfy the minimum size
requirement. The program does not cover delivery to addresses through third-party couriers or products shipped directly from third-party sellers. Bulky items such
as refrigerators are also eligible for same-day or next-day delivery in selected areas. Customers can also request expedited delivery within two hours by paying an
extra charge in select cities. JD's 211 service covered 1,410 counties and districts across China as of 2016. 2017 YTD data as of Q1.
0%
20%
40%
60%
80%
100%
2013
2014
2015
2016
2017 YTD
% of First Party Orders DeliveredWithin Two Days
Within 24 Hours**
JD.com % of First-Party Orders Delivered by Speed, 2013 2017 YTD
KP INTERNET TRENDS 2017 | PAGE 229
0%
10%
20%
30%
40%
50%
$0
$10
$20
$30
$40
$50
2012
2013
2014
2015
2016
% Y/YGrowthOnlineAdvertising($B)Online Advertising
Y/Y Growth
China Online Advertising Revenue =
+30% Y/Y @ $40B
Source: iResearch
Note: Assuming constant FX 1USD = 6.9RMB.
China Online Advertising Revenue, 2012 - 2016
KP INTERNET TRENDS 2017 | PAGE 230
Algorithmic Mobile Newsfeeds =
Driving Usage + Advertising Growth (Toutiao / Baidu / Weibo / Tencent)
0%
50%
100%
150%
200%
$0
$2,000
$4,000
$6,000
$8,000
2014
2015
2016
2017E
% Y/YGrowthMobileNewsfeedAdvertising($MM)Mobile Newsfeed Advertising
Y/Y Growth
Toutiao / Baidu / Weibo / Tencent
Mobile Newsfeeds with Personalization
China Mobile Newsfeed Advertising Revenue
& Y/Y Growth, 2014 2017E
Source: iResearch
Note: Assuming constant FX 1USD = 6.9RMB.
KP INTERNET TRENDS 2017 | PAGE 231
1) Macro = Positive Trends
2) Internet = Healthy User GrowthUsage Outpacing Users
3) Entertainment = Online Innovation Driving Robust User + Usage +
Monetization Growth
4) On-Demand Transportation = China #1 Global MarketCars + Bikes
5) Mobile Payment Infrastructure = Enabling Rapid Growth + Monetization
of Internet Usage
6) eCommerce + Advertising = Innovation + Growth
China Internet =
Golden Age of Entertainment + Transportation
KP INTERNET TRENDS 2017 | PAGE 232
INDIA INTERNET =
COMPETITION CONTINUES TO INTENSIFY
CONSUMERS WINNING
KP INTERNET TRENDS 2017 | PAGE 233
India Economy (GDP) = Fastest Large Grower
+7% Y/Y @ #7 Global GDP Rank
Source: IMF, 4/2017
Note: Y/Y growth based on constant prices.
$1,233
$1,281
$1,411
$1,799
$1,851
$2,256
$2,463
$2,629
$3,467
$4,939
$11,218
$18,569
$0
$5,000
$10,000
$15,000
$20,000
$25,000
Spain
Russia
Korea
Brazil
Italy
India
France
UK
Germany
Japan
China
USA
2016 GDP (Current Prices, $)
2016 GDP ($B) and GDP Growth Rates (%), Selected Countries >$1T of GDP
Y/Y Growth
1.6%
6.7%
1.0%
1.8%
1.8%
1.2%
6.8%
0.9%
-3.6%
2.8%
-0.2%
3.2%
KP INTERNET TRENDS 2017 | PAGE 234
India Internet Users = +28% (2016-June) vs. 40% Y/Y Growth
@ 27% Penetration355MM Users#2 Behind China
India Internet Users (MM) & Penetration (%), Monthly Active*,
Mid-Year (June) 2009 2016E
54
66
84
111
149
198
277
355
4%
5%
7%
9%
12%
15%
22%
27%
0%
5%
10%
15%
20%
25%
30%
0
50
100
150
200
250
300
350
400
2009
2010
2011
2012
2013
2014
2015
2016E
Online Penetration (%)Internet Users (MM)Number of Internet Users
Online Penetration
Source: IAMAI. UN Population Division, Worldometer, KPCB estimates based on IAMAI data. Uses mid-year figures.
*Note that "Monthly Active Users" are distinct from "Ever" users, which IAMAI defines as anyone who has ever accessed the internet. Owing to
increasing activity levels, the number of "Monthly Active Users" may grow faster than "Ever" users.
KP INTERNET TRENDS 2017 | PAGE 235
India = #1 Global Market (ex-China) Android Phone Time Spent
Google Play Downloads > USA (2016), per App Annie
Source: App Annie 2016 Retrospective
Note: USA @ ~59% vs India 78% Android share of total mobile Internet traffic (Statcounter, 5/17)
* Data excludes China
0
25
50
75
100
125
150
2014
2015
2016
Hours (B)India
Brazil
USA
Indonesia
Mexico
0
2
3
5
6
8
2014
2015
2016
Downloads (B)India
USA
Brazil
Indonesia
Russia
Total Google Play Downloads,
2014-2016
Total Time Spent* on Android Phones,
2014-2016
KP INTERNET TRENDS 2017 | PAGE 236
1 1
2 2 2 2
3 3 4 4
4
5
6
10
13
15
17
18
23
22 22
27
29
26
23
28
32
26
27
0%
50%
100%
150%
200%
250%
0
5
10
15
20
25
30
35
Q1:10Q2:10Q3:10Q4:10Q1:11Q2:11Q3:11Q4:11Q1:12Q2:12Q3:12Q4:12Q1:13Q2:13Q3:13Q4:13Q1:14Q2:14Q3:14Q4:14Q1:15Q2:15Q3:15Q4:15Q1:16Q2:16Q3:16Q4:16Q1:17% Y/Y GrowthUnit Shipments (MM)Smartphone Shipments
Y/Y Growth (%)
India Smartphone Shipments =
+15% Y/Y (Q1:17)+5% (2016)+29% (2015)
India Smartphone Unit Shipments,
Q1:10 Q1:17
2015:
+29% Y/Y
2016:
+5% Y/Y
Source: Morgan Stanley, IDC
KP INTERNET TRENDS 2017 | PAGE 237
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
0
10
20
30
40
50
60
70
80
Q1:10Q2:10Q3:10Q4:10Q1:11Q2:11Q3:11Q4:11Q1:12Q2:12Q3:12Q4:12Q1:13Q2:13Q3:13Q4:13Q1:14Q2:14Q3:14Q4:14Q1:15Q2:15Q3:15Q4:15Q1:16Q2:16Q3:16Q4:16Q1:17% Y/Y GrowthUnit Shipments (MM)Smartphone Shipments
Feature Phone Shipments
Y/Y Growth (%)
Smartphone + Feature Phone Shipments =
+6% Y/Y (Q1:17)-3% (2016)-2% (2015)
India Mobile Phones Unit Shipments,
Q1:10 Q1:17
2015:
-2% Y/Y
2016:
-3% Y/Y
Source: Morgan Stanley, IDC
KP INTERNET TRENDS 2017 | PAGE 238
India Smartphone + Data Costs =
Declining But Still High for
Majority of India's 1.3B Citizens
KP INTERNET TRENDS 2017 | PAGE 239
India Smartphone Cost (excluding Data) = Unaffordable for Many
@ 8% of Annual Average GDP per Capita
0%
5%
10%
15%
20%
25%
30%
35%
40%
$0
$50
$100
$150
$200
$250
$300
$350
$400
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
ASP as % of Per Capita GDPSmartphone ASP ($)Smartphone ASP ($)
ASP as % of GDP per Capita
India Smartphone Average Selling Price (ASP, $) &
ASP as % of GDP per Capita, 2007 - 2016
Source: Morgan Stanley, IDC. GDP per Capita data based on IMF, 4/17.
KP INTERNET TRENDS 2017 | PAGE 240
India Wireless Data Cost* = Declining to More Affordable Levels
@ 1.3% of Annual Average GDP per Capita (3/17) vs. 3% (3/15)
$53
$53
$51
$52
$51
$48
$47
$45
$44
$42
$38
$33
$23
0.0%
1.0%
2.0%
3.0%
4.0%
$0
$15
$30
$45
$60
Cost of Data as % of GDP per Capita (%)Annualized Cost of 1GB / Month Plan ($)Annual Price of 1GB of Data per Month
As a % of GDP/Capita
2% GDP / Capita
Threshold for
Widespread
Affordability, per
Alliance for Affordable
Internet
Annualized Cost of 1GB / Month vs. % of GDP per Capita,
Q1:14 Q1:17
Source: JP Morgan, Bharti Airtel, Idea Cellular, IMF, Alliance for Affordable Internet.
*Industry average calculated using average cost of 1 GB of data from Bharti Airtel and Idea Cellular and exclude the impact of Reliance Jio.
Chart is illustrative and assumes an average consumption of 1GB / month. Alliance for Affordable Internet data suggests that 2% of monthly
income for 1GB of data is within affordable range.
KP INTERNET TRENDS 2017 | PAGE 241
India Internet =
Fierce Global Battleground
(Hardware / Carriers / Software /
Commerce)
KP INTERNET TRENDS 2017 | PAGE 242
India Mobile Hardware (2012-Q1:17) =
Intense Competition Massive Share Shifts
0%
10%
20%
30%
40%
50%
60%
Q4:14
Q4:15
Q4:16
Q1:17
Smartphone Unit Shipments Market Share (%)China-Based Vendors
India-Based Vendors
Global Vendors
India Smartphone Shipments Market
Share by Vendor Country of Origin (%),
Q4:14 Q1:17
Rise of India OEMs (2012-H1:14)
Likes of Micromax / Lava / Karbonn Fight for
Feature Phone Market Share via PriceASPs Fall
~40%Shares Rise
Rise of China OEMs + Reliance (H2:14-Q1:17)
Likes of Lenovo / Xiaomi / Oppo / Vivo Fight for
Smartphone Market Share via Quality / Features /
Online DistributionASPs StableShares
RiseReliance Gains Share in 2016 on Launch of
Jio 4G Service + LYF-Branded Smartphones...
Competition Intensifies (H1:17)
Xiaomi / Oppo / Vivo Share Gains Continue
Smartphones Get Cheaper / Better...
Lava / Micromax / Jio Fight for Low-Cost 4G Feature
Phone Share...
Source: IDC, Morgan Stanley, Lava, Micromax, Jio.
KP INTERNET TRENDS 2017 | PAGE 243
India Wireless Carriers = Incumbents + New Entrants
Fighting Aggressively for Share Over Past 4 Quarters
2015 1H:16
Top 3 India wireless carriers Bharti Airtel / Vodafone / Idea collectively maintain ~60% share
of broadband subscribers + ~$2.80 $3.00 monthly ARPU (Voice + Data + Value-Added
Services).
Q2:16
Wireless incumbents begin to cut data rates in anticipation of Reliance Jio launch in 9/16.
Data costs per GB decline from $3.50 to ~$3.15 (-10%) Q/Q. Voice costs decline 4% Q/Q.
9/16
Reliance Jio after investing $25B over 7 years rolls out 4G Pan-India Jio network +
$0 Monthly ARPU (post 3/17 when ARPU rose to $4.70)
Q4:16 Q1:17
Wireless incumbents begin to lose data subscribers. In response, they cut data prices further
over next 2 quarters. As of 3/17, average cost of 1GB of data @ ~$2 among incumbents,
-48% Y/Y...ARPU -20%. Including Jio, average cost of 1GB of data @ $0.33 (3/17).
3/17
Reliance Jio free-data period ends with ~67% paid migration (72MM convert to paid Jio Prime
subscribers out of 108MM sign-ups)
Source: JP Morgan, Public Filings, TRAI, Reliance Jio.
Jio sign-ups are total number of Jio SIMs registered, while paying subscribers are a subset of sign-ups who have later converted to Jio Prime
paid subscription. Data for incumbents based on average of Idea and Bharti Airtel.
KP INTERNET TRENDS 2017 | PAGE 244
India Wireless Consumer Data Prices = -48%+ in Last Year* as
Incumbent Carriers Responded to Jio's Low Pricing
Data Prices per GB, Industry*, CQ1:14 CQ1:17
$4.4
$4.4
$4.3
$4.3
$4.2
$4.0
$3.9
$3.7
$3.7
$3.5
$3.1
$2.7
$1.9
$0.17
$0.0
$0.5
$1.0
$1.5
$2.0
$2.5
$3.0
$3.5
$4.0
$4.5
$5.0
3/14
6/14
9/14
12/14
3/15
6/15
9/15
12/15
3/16
6/16
9/16
12/16
3/17
Cost of 1GB Data ($)Price of 1GB of Data (Industry Incumbents)
Price of 1GB of Data (Jio)
Industry Incumbents
-48% Y/Y
Reliance Jio 3/17
Source: JP Morgan, Bharti Airtel, Idea Cellular, Reliance Jio.
*Industry incumbent average calculated using weighted average cost of 1 GB of data realization from Bharti Airtel / Idea Cellular.
Reliance Jio data assumed at 10 INR / GB based on March realization.
KP INTERNET TRENDS 2017 | PAGE 245
India Broadband Subscribers* = +85% Y/Y (Q1:17)Accelerating
Reliance Jio Rose to 39% Share vs. 0% (Q3:16) Owing to Low Price Launch
72
108
22
25
28
31
38
41
46
44
49
19
22
24
26
28
32
36
35
38
19
18
20
21
23
27
31
27
25
15
17
19
20
20
21
22
20
22
24
27
30
38
40
42
58
38
35
99
109
121
137
150
162
192
0
50
100
150
200
250
300
Q1:15
Q2:15
Q3:15
Q4:15
Q1:16
Q2:16
Q3:16
Q4:16
Q1:17
Broadband Subscribers (MM)Jio
Bharti Airtel
Vodafone
Idea BSNL Other
236
India Broadband (>512 Kbps) Subscribers* by Service Provider,
CQ1:15 CQ1:17
9/16 =
Jio Release to
General Public
277
Source: TRAI reports.
*Subscribers are defined as all unique SIMs within a carrier's database, less test/service cards, employees, stock in hand, SIMs where the
subscriber retention period has expired, and service suspended pending disconnection.
Note that as of 3/17, Jio's subscribers mentioned here were on free data plans. Subsequent to this free trial period, 72MM so far have converted
to paying subscribers.
KP INTERNET TRENDS 2017 | PAGE 246
India Software Mobile Browser Usage Market Share =
China (UC/Alibaba) @ 50%...USA (Google Chrome) @ 32%...
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
UC Browser
Opera
Chrome
Android
Nokia
Others
India Mobile Browser Usage Market Share, Q1:13 Q2:17
Source: Statcounter 2017
Note: Data reflects usage share across calendar year quarters. As Q2 is in progress, data for Q2 2017 reflects current share as of 5/30/17
KP INTERNET TRENDS 2017 | PAGE 247
India Software Top Downloaded Android Apps =
USA @ 4 of 10China @ 2 of 10India @ 2 of 10
Google
Play Store
Rank (5/29/17)
App
Origin
Category
Rank on
5/30/16
(1 Year Ago)
1
WhatsApp (Facebook)
USA
Messaging
1
2
Facebook Messenger
USA
Messaging
3
3
ShareIt
China
Utility file transfer
5
4
Truecaller
Sweden
Utility dialer
11
5
Facebook
USA
Social
2
6
UC Browser (Alibaba)
China
Browser
4
7
MX Player
Korea
Utility video player
13
8
Hotstar
India
Entertainment
6
9
JioTV
India
Entertainment
301
10
Facebook Lite
USA
Social
9
Source: *Top 10 Non Gaming Apps, Google Play Store, India, 5/29/17
Note: Google Play Store ranks reflect rankings based on daily download volumes
Blue indicates a Facebook app. Green indicates an app owned by Alibaba.
KP INTERNET TRENDS 2017 | PAGE 248
India eCommerce =
Many Players Fighting for Share...
Source: Company logos
KP INTERNET TRENDS 2017 | PAGE 249
Amazon India = Inventory (SKUs) & Sellers +3x Y/Y...
Fulfillment Centers +30% Y/Y...Aggressive / Investing Heavily
0
30
60
90
120
150
0
20
40
60
80
100
09/15
12/15
09/16
Sellers (K)SKU (MM)SKU (MM)
Sellers (000s)
Amazon India SKUs & Sellers,
9/15 12/16
0
5
10
15
20
25
30
2012
2013
2014
2015
2016
Fulfillment CentersAmazon India Fulfillment Centers,
2012 2016
Source: Barclays Research, Amazon.com, MWPVL International
Per public statements, Amazon has pledged to invest $5B into India
KP INTERNET TRENDS 2017 | PAGE 250
India Internet Usage =
Rising Owing to
Cheaper / Faster Access
KP INTERNET TRENDS 2017 | PAGE 251
India Wireless Internet Data Usage =
Rising Dramatically as Access Costs Have Fallen
0
200
400
600
800
1,000
1,200
1,400
3/14
6/14
9/14
12/14
3/15
6/15
9/15
12/15
3/16
6/16
9/16
12/16
3/17
Millions of GB per MonthTotal Monthly Wireless Data Consumed (MM GB)*, 3/14 -
3/17
Total Monthly Wireless Data Consumed (MM GB)
+9x Y/Y
Source: Reliance Jio, Bharti Airtel, Idea, Reliance Communications, Vodafone India.
*Note total data consumed based on publicly available data from Reliance Jio, Bharti Airtel, Idea, Reliance Communications, Vodafone and may
not be collectively exhaustive.
KP INTERNET TRENDS 2017 | PAGE 252
India Wireless Internet Data Usage =
Bandwidth Intensive App Usage Growing Dramatically
0
200
400
600
800
1,000
6/16
9/16
12/16
3/17
Streams per Month (MM)Gaana Streams
+3x Growth
0%
1%
2%
3%
4%
5%
6%
6/16
9/16
12/16
4/17
Daily Active Users as % of Total UsersHotstar DAUs
4x+ Growth
Source: Gaana, SimilarWeb estimates for HotStar, 5/17
Note: DAU estimates are intended to reflect relative growth within reasonable confidence intervals using SimilarWeb's methodology.
Hotstar DAUs, 6/16 4/17*
(Video Streaming App)
Gaana Streams, 6/16 3/17
(Music Streaming App)
KP INTERNET TRENDS 2017 | PAGE 253
India Leadership =
Focused Pro-Digital Policies
KP INTERNET TRENDS 2017 | PAGE 254
India Leadership =
Digital-Focused Government Policies Rolled Out with Speed + Scope
'Banking for All' 'Jan Dhan Yojana' = 8/14
~280MM+ new bank accounts opened to deliver financial
services directly to underbanked in effort to bypass corruption
Startup India = 1/16
High level support of Indian startups via funding &
fast tracking of regulatory support for new companies
Digital India = 7/15
National rollout of high speed broadband access & digital
delivery of land records, income tax filings & other government
services
'Power for All' Rural Electrification = 7/15
Program to electrify 100% of villages by 2019, with 133MM
rural households electrified to date~45MM remaining
Demonetization = 11/16
~85% of paper currency in circulation replaced overnight to
clean 'black' money (estimated at 22%+ of total GDP) &
boost digital payment adoption
Infrastructure Enhancements = 2/17
$59B targeted to upgrade railways / airports / roads
Narendra Modi Elected India Prime Minister = 5/14
Key Policies
Nationwide Tax (GST) Reform = 3/17
Single indirect tax replacing 17 different state & central taxes,
turning India into single national market &
eliminating double taxation for consumers
Skills & Entrepreneurship = 6/15
Dedicated ministry to upgrade youth skillsgoal to
train 10MM new workforce entrants per year
Other Notable Policies
Source: Ministry of Finance, India (5/17). Rural Electrification Corporation (5/17). Reserve Bank of India (7/16). World Bank black money
estimates (7/10). Ministry of Commerce, India (1/16), Ministry of Skill Development & Entrepreneurship (6/15), New York Times (11/16),
Bloomberg (2/17). India Union Budget (2017-2018)
KP INTERNET TRENDS 2017 | PAGE 255
India Internet Usage Growth Strong Owing In Part to
Broader Availability of Low Cost Data Access...
India Internet User Base @ +355MM is Large...
Ongoing Smartphone + Access Price Declines
Key to Onboarding Next 200MM Users
Driving Free Cash Flow for Many Internet
Businesses Challenging Owing to Fierce Competition
Consumers Benefitting from
Competition & Government Policies
KP INTERNET TRENDS 2017 | PAGE 256
India Internet Innovation =
Leapfrogging + Re-Imagining
Leapfrogging
Mobile
Identity
Bandwidth
Payments
Re-Imagining
Entertainment
Education
Healthcare
Marketplaces
KP INTERNET TRENDS 2017 | PAGE 257
India Mobile Usage = A Global Leader vs. Desktop Usage
~80% of Internet Usage on Mobiles
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
NigeriaIndiaSouth AfricaIndonesiaThailandTurkeyUAEPolandChinaSaudi ArabiaMalaysiaMexicoGlobal AverageArgentinaSingaporeSpainPhilippinesUSAAustraliaS. KoreaUKVietnamItalyEgyptBrazilGermanyCanadaJapanFranceRussiaMobile as % of Web TrafficMobile Share of Web Traffic, 1/17
Source: Hootsuite, Statcounter, 1/17.
KP INTERNET TRENDS 2017 | PAGE 258
India Identity = Aadhaar + eKYC Digital Authentication for 1B+ People
Use Growing Rapidly @ 16MM Authentications per Day (3/17) vs 3MM Y/Y
Aadhaar Authentication =
eKYC Authentication
Are You Who You Claim To Be?
Proof of Address / Birth / Photos
If Yes

Binary Yes / No Answer Only
Uses Biometrics (Fingerprint + Iris)
+ Unique 12-Digit Number to Verify

Secure Dropbox for Basic Paper Records
Can Only be Accessed if Aadhaar ID is
Authenticated + User Gives Consent
Aadhaar Authentications / Day,
9/12 - 3/17
0
1
2
3
4
5/16
6/16
7/16
8/16
9/16
10/16
eKYC / Day (MM)eKYC Verifications / Day,
5/16 10/16
-
2
4
6
8
10
12
14
16
18
AadharAuthentications / Day (MM)Source: UIDAI (Indian Government), iSpirit / IndiaStack,
Note: Aadhaar authentication per day estimates provided by Prime Venture Partners, based on monthly authentication figures released by UIDAI
KP INTERNET TRENDS 2017 | PAGE 259
...India Identity = India Aadhaar Digital IDs Have Broad Coverage
@ 82% of Population (1.1B People) vs. Zero 6 Years Ago#1 in World
0%
4%
8%
23%
46%
72%
82%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
0
200
400
600
800
1,000
1,200
2010
2011
2012
2013
2014
2015
2016
% of Total PopulationTotal AadhaarIDs (MM)Aadhaar IDs (MM)
% of Total Population
Total Aadhaar IDs (MM), 2010 2016
Source: UIDAI (Indian Government), iSpirit / IndiaStack, Prime Venture Partners, United Nations
KP INTERNET TRENDS 2017 | PAGE 260
Sim Card
Activation
Before Digital ID = 1-3 Days
Proof of Address / original photo IDs / attested
photocopies + potential fraud
After-Digital ID = 15 Minutes
Aadhaar number + fingerprint / biometric eSign
...India Identity =
Aadhaar IDs + eKYC Improving Foundational Access to Broad Services
Bank Account &
Digital Wallet Opening
Before Digital ID =
Physical visit to bank, paper-based KYC, lack of
ability to scale, improper documentation
After-Digital ID =
Open account on mobile phone
in secure / scalable way
Pensions &
Social Services
Before Digital ID =
Cash-based / leakage of payments to
government officials / corruption / fraud
After-Digital ID =
12-15% increase in final payouts to workers
owing to reduced leakage
Source: UIDAI (Indian Government), iSpirit / IndiaStack, Skoch Group
Note: Image credits Hindu Business Line, NDTV, Reliance Jio, DBS India, Livemint (2017)
KP INTERNET TRENDS 2017 | PAGE 261
India Bandwidth = Reliance Jio High-Speed Bandwidth Ramp
@ 108MM Sign-Ups* in 7 Months...72MM Converted to Paying Subscribers
Reliance Jio Sign-Ups and Subscribers (MM),
9/16 4/17
16
24
52
72
86
100
108
72
0
20
40
60
80
100
120
9/16
10/16
11/16
12/16
1/17
2/17
3/17
Reliance JioSign-Ups / Subscribers (MM)Reliance Jio Sign-Ups
Jio Prime Subscribers
Source: Cellular Operators Association of India (COAI), Reliance Jio, various press releases
*Sign ups represent all those who have signed up for a Jio SIM card. Subscribers are those who remained with Jio after their free trial period
ended on 3/31/2017 and became Jio Prime subscribers.
KP INTERNET TRENDS 2017 | PAGE 262
India Payments = Evolution of Building Blocks for
Digital Payment / Data Infrastructure for 1B+ Indians (2009 2017)...
Phase
Project
Functionality
Results
1) Identity
Aadhaar (1/09) +
eKYC (5/13)
Single digital ID +
authentication database

1B+ Aadhaar cards issued since 2010

~16MM authentications/day (4/17)
2) Banking
Jan Dhan Yojana
(8/14)
'Banking for All'
Bank accounts tied to
Aadhaar for previously non-
banked citizens

280MM+ accounts opened in 3 years...
50% of existing bank accounts
Direct subsidies to citizen bank
accounts have saved $775M owing
largely to reduced corruption leakage
(12/16)
3) Mobile
Services
Universal Payments
Interface (UPI)
(7/16)
Instant money transfer
between bank accounts via
phone numbers
~$380MM monthly transaction volume
(4/16)
Use accelerated after demonetization
(11/16)
Bharat Interface for
Money (BHIM)
(12/16)
Government App for UPI
based payments
17MM+ downloads within 2 months of
launch (2/17)
Source: Kalaari Capital, Prime Venture Partners, Indiastack.org, Department of Financial Services, Government of India (2016)
KP INTERNET TRENDS 2017 | PAGE 263
Paytm Registered Users (MM), 11/14 - 3/17
India Payments = Online Leader Paytm Ramping Users Rapidly
Bolstered by Uptake of Online + Offline Commerce
22
50
100
122
180
215
0
50
100
150
200
250
11/14
4/15
8/15
4/16
12/16
3/17
Registered Users (MM)Paytm
Source: Paytm.
KP INTERNET TRENDS 2017 | PAGE 264
India Payments = UPI (Universal Payments Interface)
Rapidly Enabling Bank-to-Bank Mobile Money Transfers
$0
$5
$7
$15
$106
$249
$285
$359
0%
5%
10%
15%
20%
25%
30%
35%
$0
$50
$100
$150
$200
$250
$300
$350
$400
8/16
9/16
10/16
11/16
12/16
1/17
2/17
3/17
UPI as % of Mobile Wallet VolumeUPI Monthly Transaction Volume ($MM)Monthly Digital Payments Volume in India via UPI ($MM),
8/16 3/17
UPI Transaction Value
UPI Value as % of Total Mobile Wallets
Source: Reserve Bank of India, Monthly Bulletin (Payments and Settlement Systems)
Demonetization (11/16)
KP INTERNET TRENDS 2017 | PAGE 265
India Internet Innovation =
Leapfrogging + Re-Imagining
Leapfrogging
Mobile
Identity
Bandwidth
Payments
Re-Imagining
Entertainment
Education
Healthcare
Marketplaces
KP INTERNET TRENDS 2017 | PAGE 266
Search, Social and
Messaging, 34%
Entertainment, 45%
Shopping, 4%
Finance, 2%
News & Media , 2%
Others,
13%
India Entertainment = Weekly Mobile Time Spent @ 7x TV
45% Mobile Time = Entertainment
Source: MMA Kantar India Mobile Usage Report, 2016
2
4
28
0
5
10
15
20
25
30
35
40
Time Spent with Media per
Week (Hours), 2016
Print
Television
Mobile
Percent of Time Spent on Mobile by
Category, 2016
KP INTERNET TRENDS 2017 | PAGE 267
TV Soap Operas + Reality Shows
On-Demand Web-Video Shows
ex. AIB Roasts, Hotstar
Scripted, family-focused dramas targeted
@ older viewers + families with 'rinse &
repeat' plots
Produced for linear programming without
user data / feedback
Little to no user data, often based on small
TV rating sample sizes / surveys
India Entertainment Re-Imagined = Internet-First Shows Optimized for Mobile
Replacing Longer / Linear Programming Optimized for TV
THEN
NOW
Millennial focused / short-form content
such as 'Hinglish' standup comedy
Made for mobile / shared via
messaging channels (Whatsapp, FB, etc)

Instant user data + feedback
(Views, Geos, Replays etc.)
Dramatic growth assisted by 4G
rollout of JioAIB Channel @ 100MM+ views
Source: Google Play, Reliance Jio Annual Report
Image: Wikipedia, Hotstar, JioTV
KP INTERNET TRENDS 2017 | PAGE 268
India Education = Largest K-12 School System (250MM+ Students) in World With
High Demand for After-School Education
0
50
100
150
200
250
300
India
China
US
UK
Students (MM)Total K-12 Student Enrollments by
Country (MM), 2015
22%
26%
37%
0%
10%
20%
30%
40%
50%
Primary
Upper Primary
Secondary
% of Students% of Students Enrolled in Private Coaching
89%
8%
2%
2%
0%
20%
40%
60%
80% 100%
Augmenting Basic
Education
Prep for Job Exams
Entrance Exam Prep
Others
Reasons for Private Coaching
% of Respondents
Indian Private Coaching Industry,
2014
Source: Nielsel K-12 India Book Publishing Report,2016. UNESCO Education & Literacy China Statistics, 2015. U.S
Department of Education, 2016. UK Department for Education National Statistics, 1/15.
KP INTERNET TRENDS 2017 | PAGE 269
India Education Re-Imagined =
Increasingly Accessible (via Mobiles) + Self-Paced + Personalized
THEN
Offline Private 'Tuition' Centers
Mobile Self-Paced Learning
ex. Byju's
Offline lectures + in-person testing
Directly based on income & geography
1:35+ student-teacher ratio
One-size-fits-all approach
Extreme focus on test taking
Math + science with games + videos
Anyone / anywhere with smartphone
40+ minutes average daily usage
Personalized
Learning outcomes* improved 15%+
NOW
Source: Byju's, *data refers to improvements among students who took a test, watched the video and then took another tes
Image: DailyMail
KP INTERNET TRENDS 2017 | PAGE 270
India Healthcare = High (& Rising) Out-of-Pocket Spend
<20% Insurance Penetration
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% of Private Expenditure on HealthIndia Out-of-Pocket Spend
(% of Private Expenditure on Health), 2014
86%
82%
0%
20%
40%
60%
80%
100%
Rural
Urban
% of PopulationPercent of Indian Population Not Covered by
Insurance, 2014
$0
$20
$40
$60
$80
Expenditure per Capita ($)Health Expenditure per Capita in India ($),
2004 - 2014
Source: World Bank 2014 Census.
KP INTERNET TRENDS 2017 | PAGE 271
Offline Labs & Pharmacies
Online Health Hubs
ex. 1Mg, Portea
Long wait times for standard lab tests
Limited drug inventory
Geography dependent
Up to 60-80% price variance for
identical drugs owing to lack of price
transparency

In-home tests ordered online
Access to aggregated inventories of
multiple pharmacies in metro
40-50% lower prices for lab tests

Instant drug price comparisons offer
transparency, saving users 20 - 30% per
prescription
India Healthcare Re-Imagined = Increasingly Accessible (via DIY / Mobile) +
Affordable (via Online Aggregation + Pricing Transparency)
THEN
NOW
Source: 1Mg, Portea, CDSCO Report 2016
KP INTERNET TRENDS 2017 | PAGE 272
India Marketplaces = Organizing the Un-Organizable
Replacing Middlemen with Smartphones + Direct to Consumer Marketplaces
Hyperlocal Offline Markets
ex. Fish Mandis
Mobile / Direct-to-Consumer
Ex. Freshtohome.com
Multiple middlemen
High price variance
No consumer visibility into quality
High quality produce sourced
directly from fishermen
Online distribution allows 20-25%
lower prices for consumers
THEN
NOW
Source: FreshtoHome
Image: TheIndianIris
KP INTERNET TRENDS 2017 | PAGE 273
India Internet Challenges =
Fundraising Environment +
Language
KP INTERNET TRENDS 2017 | PAGE 274
India = Especially High Venture Capital Funding in H2:14 2015
Helped Drive Aggressive Start Up Valuations + Spending + Competition
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
$4,000
Amount Invested ($MM)2013: $1.4B
2014: $5.1B
2015: $7.6B
2016: $4.7B
Source: Tracxn, Inc42
Indian VC Funding by Quarter, Q1:13 Q1:17
KP INTERNET TRENDS 2017 | PAGE 275
India = 29 Languages Spoken by >1MM People6 >50MM (ex-English)
46% of Internet Users Primarily Consume Local Language Content
45
63
86
127
66
86
112
150
41%
42%
44%
46%
37%
38%
39%
40%
41%
42%
43%
44%
45%
46%
47%
0
50
100
150
200
250
300
2012
2013
2014
2015
% of Total Internet UsersInternet Users & Language of Content Consumption (MM)Consumers of Non-Local Language Content
Consumers of Local Language Content
% of Internet Users Consuming Local Language Content
Indian Internet Users & Primary Language for Content Consumption,
2012 2015
Source: IDC New Media Market Model 3/17, Nation Master 2009, Indian Census 2001, CRDDP Survey, (Shariff, 2014), IAMAI 2/16, IAMAI
Reports 2012-2016.
KP INTERNET TRENDS 2017 | PAGE 276
India Macro
Demographics = Bad & Good
Other Challenges =
1) Job Creation
2) Business Basics
3) Education
4) Logistics
5) Gender Disparity
KP INTERNET TRENDS 2017 | PAGE 277
India = Low Relative GDP per CapitaPoverty Levels
While ImprovingRemain High
GDP per Capita ($) Among Countries >50MM in Population,
Current Prices, 2016
$0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
CongoEthiopiaMyanmarBangladeshPakistanIndiaVietnamNigeriaPhilippinesIndonesiaEgyptIranSouth AfricaThailandChinaMexicoBrazilRussiaTurkeyKoreaItalyFranceJapanUKGermanyUSAGDP per Capita ($)Source: IMF, 4/17.
GDP per Capita data based on current prices. Selected for countries with population >50MM.
KP INTERNET TRENDS 2017 | PAGE 278
India = Lots of Young People
64% of Population...72% of Internet Users <35 Years Old...
0%
8%
16%
24%
32%
40%
0
50
100
150
200
250
300
350
400
450
500
0-14
15-34
35-49
50-64
65+
% of Total PopulationPopulation (MM)Age Group
Population by Age Group (MM)
% of Population
India Population by Age Group,
2015
Distribution of India Internet Users
by Age Group, 2017
0%
5%
10%
15%
20%
25%
30%
35%
40%
6-14
15-24 25-34 35-44
45+
Distribution of Internet Users by Age Group (%)Age Group
Internet Users by Age Group
Source: UN Population Division., ComScore, 3/17.
ComScore data based on panel and census and only includes Android.
KP INTERNET TRENDS 2017 | PAGE 279
50%
55%
60%
65%
70%
75%
19551960196519701975198019851990199520002005201020152020E2025E2030E2035E2040E2045E2050EPercent of Population Between Ages 15 -64India
China
More Developed Regions
India = Working Age Population Growth + Millennial Per Capita Income
Compare Favorably with Other Countries
Percent (%) of Population 15 64 Years Old,
India vs. China vs. More Developed Regions,
1950 2050E
0
20
40
60
80
100
120
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465+Index to Highest Income Age Group in Country (100)India
USA
China
Per Capita Income Distribution,
India / USA / China by Age, 2015
(Index to the Highest Income Age Category for Corresponding Country)
Peak Working Age
Population
Source: UN Population Division, Euromonitor, Morgan Stanley.
Projections data based on medium variant estimates. "More Developed Regions" comprised of N. America, Europe, Japan, Australia, New
Zealand. Projections begin after 2015. UN provides projections on a 5-year time frame.
KP INTERNET TRENDS 2017 | PAGE 280
India = 'Consumption Class' Growing Rapidly
@ 27% of Households (66MM) vs. 7% Ten Years Ago
India Households by Income Bracket, 2005 vs. 2015
(in constant 2015 dollars)
0
50
100
150
200
250
300
2005
2015
Households (MM)<$3K
$3K-$7K
$7K-$17K
$17K-$34K
>$34K
14M
66M
Consumption Class = income levels at which
consumers start to spend beyond basic
necessities
Source: Kalaari Capital, 3/17, NCAER, McKinsey.
KP INTERNET TRENDS 2017 | PAGE 281
India Consumption = Mostly Focused on Basics"Roti, Kapda Aur Makaan"
@ 54% of Personal Consumption Expenditure
Personal Consumption Expenditure by Category, 2016
Basics
Clothes and footwear (ex-
sportswear)
Clothes and footwear (ex-
sportswear)
Clothes and footwear (ex-
sportswear)
Clothes and footwear (ex-sportswear) Clothes and footwear (ex-sportswear)
Cosmetics and personal care
Cosmetics and personal care
Cosmetics and personal care
Cosmetics and personal care
Cosmetics and personal care
Jewelry
Jewelry
Packaged food
Packaged food
Packaged food
Packaged food
Packaged food
Fresh food
Fresh food
Fresh food
Fresh food
Fresh food
Non-alcoholic beverages
Non-alcoholic beverages
Non-alcoholic beverages
Non-alcoholic beverages
Non-alcoholic beverages
Alcoholic beverages
Alcoholic beverages
Alcoholic beverages
Alcoholic beverages
Alcoholic beverages
Tobacco
Tobacco
Tobacco
Tobacco
Tobacco
Housing
Housing
Housing
Housing
Housing
Financial services
Financial services
Financial services
Financial services
Financial services
Utilities
Utilities
Utilities
Utilities
Utilities
Household appliances
Household appliances
Household appliances
Household appliances
Other household goods
Other household goods
Other household goods
Other household goods
Other household goods
Ground transportation/services
and automobiles
Ground transportation/services
and automobiles
Ground transportation/services
and automobiles
Ground transportation/services
and automobiles
Ground transportation/services
and automobiles
Handset and telecom services
Handset and telecom services
Handset and telecom services
Handset and telecom services
Handset and telecom services
Food services
Food services
Food services
Food services
Food services
Out of town trips
Out of town trips
Out of town trips
Out of town trips
Healthcare
Healthcare
Healthcare
Healthcare
Healthcare
Education
Education
Education
Education
Education
Insurance and social protection
Insurance and social protection
Insurance and social protection
Insurance and social protection
Insurance and social protection
Others
Others
Others
Others
Others
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
India
US$1,034
China
US$3,136
Korea
US$12,687
Japan
US$20,785
USA
US$38,293
Source: Euromonitor, Goldman Sachs Investment Research.
KP INTERNET TRENDS 2017 | PAGE 282
India Job Creation = Employment Levels @ 55% of Working Age Population...
Employment Trending Slower than Population Growth
India Working Age (15-64 Years Old) Population vs. Employment,
1995 2050E
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1995
2000
2005
2010
2015
2020E
2025E
2030E
2035E
2040E
2045E
2050E
Population Between Ages 15 64and Employment Level (MM)India Working Age Population
Employment
+280MM
Working-Age Population
Source: UN Population Division, Planning Commission of India, National Sample Survey, International Labor Organization.
Population projections based on medium variant estimates. Projections begin after 2015.
Working age population defined as ages 15-64.
KP INTERNET TRENDS 2017 | PAGE 283
India Business Basics =
Ease-of-Doing Business Lags Behind Many Countries
Topics
India
China
USA
OECD
Overall Ease of Doing Business
(Rank out of 190)
130
78
8
--
Ease of Starting a Business
(Rank out of 190)
155
127
51
--
# Procedures to Register Business
(Number)
14
9
6
5
Time to Register Business (Days)
26
28
4
8
Cost to Register Business
(% of Income Per Capita)
16.5%
0.6%
1.3%
3.1%
Source: The World Bank, 2017 (http://www.doingbusiness.org/rankings). Rankings apply to 190 countries.
Number of procedures, time to register, and cost as % of income per capita reported here based on statistics that apply to men.
KP INTERNET TRENDS 2017 | PAGE 284
India Education =
Average Years of Schooling Lags Peers
Average Years of Schooling Among Selected Medium Human Development Countries,
2015
0
2
4
6
8
10
12
14
BhutanNepalCambodiaMyanmarCabo VerdeMoroccoPakistanBangladeshLaoHondurasKenyaCongoIndiaGuatemalaNicaraguaEl SalvadorIraqNamibiaVanuatuZambiaGhanaEgyptIndonesiaViet NamParaguayGabonBoliviaGuyanaBotswanaPhilippinesTurkmenistanSouth AfricaTajikistanKyrgyzstanChinaUSAAverage Years of SchoolingAverage Years of Schooling Among Medium
Human Development Countries
Source: Human Development Report, 2016
Mean years of schooling defined as average number of years of education received by people ages 25 and older, converted from education
attainment levels using official durations of each level.
KP INTERNET TRENDS 2017 | PAGE 285
India Logistics =
Low Infrastructure Competitiveness
Source: The World Bank Global Competitiveness Index, 2016-2017. Population data per CIA World Factbook. Numbeo Traffic Estimates.
*The World Bank Global Competitiveness Report (GCR) is a yearly report published by the World Economic Forum. Since 2004, the Global
Competitiveness Report ranks countries based on the Global Competitiveness Index, developed by Xavier Sala-i-Martin and Elsa V. Artadi.
Infrastructure Rankings Across Asia, 2016
Rank
City
Country
Traffic
Index
2015
Population
(MM)
1
Kolkata
India
337
12MM
2
Dhaka
Bangladesh
317
18MM
3
Mumbai
India
308
21MM
4
Sharjah
UAE
298
1MM
5
Nairobi
Kenya
295
4MM
6
Manila
Philippines
283
13MM
7
Jakarta
Indonesia
280
10MM
8
Tehran
Iran
272
8MM
9
Mexico City
Mexico
272
21MM
10
Istanbul
Turkey
263
14MM
Top 10 Most Congested Cities Globally, 2016*
4.03
0
2
4
6
8
Nepal
Pakistan
Bangladesh
Myanmar
Mongolia
Cambodia
Philippines
Vietnam
India
Indonesia
China
New Zealand
Malaysia
Australia
Taiwan
Korea, Rep.
Japan
Singapore
Hong Kong
Average
Most
Least
World Bank Infrastructure Competitiveness Score
KP INTERNET TRENDS 2017 | PAGE 286
India Gender Disparity =
Female Labor Participation Rate @ 27%...Below World Average
0%
10%
20%
30%
40%
50%
60%
70%
2008
2009
2010
2011
2012
2013
2014
2015
2016
Labor Participation Rate (%)Female Labor Force Participation Rate, 2008 - 2016
India
USA
China
Brazil
Russia
World Average
Source: International Labor Organization, 2016
Note: ILO defines female labor force participation rate as the proportion of the female population of age 15 and older that is economically active:
all people who supply labor for the production of goods and services during a specified period.
KP INTERNET TRENDS 2017 | PAGE 287
1) Economy = Strong Growth
2)
Internet Users = Solid Growth
3) Mobiles = Choppy GrowthRecent Acceleration
4)
Internet = Fierce Global Battleground (Hardware / Carriers / Software /
Commerce)
5)
Internet Usage = Rising Owing to Cheaper / Faster Access
6) Leadership = Focused Pro-Digital Policies
7)
Internet Innovation =
Leapfrogging = MobileIdentityBandwidthPayments
Re-Imagining = EntertainmentEducationHealthcareMarketplaces
8)
Internet Challenges = Financing EnvironmentLanguage Diversity
9)
India Macro = Demographics = Bad & GoodChallenges = Job
CreationBusiness BasicsEducationLogisticsGender Disparity
India Internet =
Competition Continues to IntensifyConsumers Winning
KP INTERNET TRENDS 2017 | PAGE 288
HEALTHCARE @
DIGITAL INFLECTION POINT
NOAH KNAUF @ KLEINER PERKINS
KP INTERNET TRENDS 2017 | PAGE 289
Healthcare @ Digital Inflection Point
Source: History of Nephrology, Welch Allyn, Medisave, Kinsa
100 Years Ago
Human Touch
25 Years Ago
Machine Assisted / Analog
Today
Technology Enabled / Digital
KP INTERNET TRENDS 2017 | PAGE 290
1) Digital Inputs = Rapid Growth in
Sources of Digital Health Data
2) Data Accumulation = Proliferation
of Digitally-Native Data Sets
3) Data Insight = Generated Following
Accumulation & Integration of Data
4) Translation = Impact on
Therapeutics & Healthcare Delivery
Digitization of Healthcare =
Virtuous Cycle of Innovation
5) Outcomes =
Measure Outcomes &
Iterate
Innovation Cycle Times
Compressing
KP INTERNET TRENDS 2017 | PAGE 291
Digital Inputs =
Rapid Growth in Sources of
Digital Health Data
KP INTERNET TRENDS 2017 | PAGE 292
Measurement =
Most Widely Used Medical Technology Now Digital / Connected
2D / Analog
3D / Digital
Paper-Based / Analog Wearable / Digital
Automatic / Digital
X-Ray
ECG
Blood
Pressure
Manual / Analog
2000's
2017
2000's
2017
Hospital
Monitoring
In-Room / Analog
Source: Medisave, GE Healthcare, iRhythm Technologies, Welch Allyn
Remote / Digital
KP INTERNET TRENDS 2017 | PAGE 293
Diagnostic Technology =
Measured / Monitored Data Attributes Rising Rapidly
13
59
0
10
20
30
40
50
60
70
1993199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017**Lab Tests with Waived Status Under CLIA* (K)Commercially Available Lab Tests, 1993-2017
Source: CLIA/FDA Database of Waived Tests and Database of Analytes (5/17)
* Lab Tests are considered to be CLIA waived if the test is simple and accurate enough that it is impossible to product incorrect results
conducting them and does not do any harm to the human body. Tests become CLIA waived automatically if the FDA approves it for at-home use
** 2017 as of 5/17.
Amylase
.
.
.
.
.
.
.
.
.
.
988 Distinct
Analytes
.
.
.
.
.
.
.
.
Zinc
KP INTERNET TRENDS 2017 | PAGE 294
Wearables =
Consumer Health + Wellness Data Capture Rising Rapidly
Source: Rock Health 2016 Consumer Survey (12/16), IDC, Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous
and Multiple-User Scenarios (9/16)
* Based on analysis of 140 different wrist wearable devices
Sensors in Wrist Wearables, 9/16
26
82
102
0
20
40
60
80
100
120
2014
2015
2016
Global Wearable Shipment Volumes (MM)13%
5%
6%
6%
7%
12%
18%
19%
26%
28%
33%
86%
Others
Thermometer
Camera
Altimeter
Barometer
Ambient Light
Microphone
Compass
Gyroscope
GPS
Heart Rate
Accelerometer
% of Wrist Wearables*
Global Wearable Shipments
Wearables = Gaining Adoption
~25% of Americans own a Wearable, +12% Y/Y, 2016
KP INTERNET TRENDS 2017 | PAGE 295
60%
56%
54%
50%
39%
39%
37%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Google
Microsoft
Samsung
Apple
Amazon
Facebook
IBM
% of Consumers Willing to Share Health DataConsumers =
Willing to Share Health Data
Leading Tech Brands Positioned Well for Digital Health, 2016
With which tech company would you share your data?
Source: Rock Health 2016 Consumer Survey
Note: Based on consumer survey with 4,015 participants; as % of respondents willing to share their health data with tech company at all.
KP INTERNET TRENDS 2017 | PAGE 296
Data Accumulation =
Proliferation of
Digitally-Native
Health-Related Data Sets
KP INTERNET TRENDS 2017 | PAGE 297
Proliferation of Health Apps =
Rapid Rise of Empowering Data in Consumer Hands
Health & Fitness App Downloads*,
Per App Annie
+5% Y/Y in US, +15% Y/Y in ROW
0
200
400
600
800
1,000
1,200
1,400
2015
2016
Downloads (MM)USA
Rest of World
36%
17%
12%
24%
11%
Fitness
Lifestyle & Stress
Diet & Nutrition
Disease & Treatment
Other
Health Apps by
Category, Global, 2015
Source: App Annie, IMS Health (6/15)
Note: Due to focus on iOS App Store and Google Play, Rest of World in the App Annie chart does not capture China's downloads on other app
stores. The IMS chart includes iOS App Store and Google Play as of 6/15.
* App downloads captures iOS App Store and Google Play
KP INTERNET TRENDS 2017 | PAGE 298
Electronic Health Record (EHR) Adoption =
Broad + Centralized Accumulation of Data
Source: Office of the National Coordinator for Health Information Technology (12/16), Galen Healthcare (8/16)
*Estimated per year clinical data element collection based on data elements collected over 6 years for 165,399 patients, average 49yrs old
EHR Adoption Among Office-Based
Physicians, USA 2004-2015
21%
87%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
EHR Adoption (%)Average Amount of Clinical Data
Elements per Patient per Year*, 8/16
5.5
2.9
3.2
4.1
10.5
26.3
0
5
10
15
20
25
30
Unique Data Elements Per PatientClinical Results
Scanned Images
Vital Signs
Problems
(historical, current)
Other (e.g.
medications,
allergens, etc.)
KP INTERNET TRENDS 2017 | PAGE 299
Hospitals Providing Digital Access to Healthcare Information =
+7x Since 2013
Source: ONC/AHA Annual Survey Information Technology Supplement: 2012-2015 (9/16)
Note: Percentage of non-federal acute care hospitals that provide patients with the capability to electronically view, download, and transmit their
health information
24%
14%
40%
28%
91%
82%
95%
87%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
View
Download
% of Non-Federal Acute Hospitals2012
2013
2014
2015
Hospitals that Enable Patient Digital Data Access, 2012 - 2015
KP INTERNET TRENDS 2017 | PAGE 300
Increasing Digitization of Inputs =
Healthcare Data Growing at 48% Y/Y
153
Exabytes
0
20
40
60
80
100
120
140
160
180
200
Worldwide Healthcare Data (2013)
Exabytesof Healthcare DataGrowth in Healthcare Data
Source: IDC & EMC (12/13)
Note: 1 Exabyte = 1B Gigabytes, 1 Petabyte = 1M Gigabytes
Data Drivers
Typical 500 Bed
Hospital

500 Beds

8,000 Employees

400 Applications

500 Databases

1,000 Interfaces

10,000 Desktops

500 Owned/Controlled
Tablets

2,000
Owned/Controlled
Mobile Devices
50
Petabytes
of Data per
Hospital
KP INTERNET TRENDS 2017 | PAGE 301
Data Insight + Translation =
Early Innings of Impact on
Therapeutics
KP INTERNET TRENDS 2017 | PAGE 302
Rise in Inputs + Data =
Medical Research / Knowledge Doubling Every 3.5 Years
Cumulative PubMed Scientific Article Citations*
0.06
27
0
5
10
15
20
25
30
1907 1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 2017
Annually Published Medical Citations (MM)Source: National Institutes of Health, U.S. National Library of Medicine (4/17), "Challenges and Opportunities Facing Medical Education"
(Densen, Peter) Transactions of the American Clinical and Climatological Association (1/10)
*Based on cumulative number of published medical citations on PubMed, **Based on peer-reviewed article on challenges in medical education
Years to Double
Medical
Knowledge**
1950
50 years
1980
7 years
2010
3.5 years
KP INTERNET TRENDS 2017 | PAGE 303
Clinical Trials = Follow Expansion of Research Insight But
Clinical Impact Lags Owing to Length of Trials...
0
50
100
150
200
250
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Total Number of Registered Clinical Trials (K)Growth in Clinical Trials
Average Clinical Trial Duration
Phase 0
~3.5 Years
Phase 1
1.8 Years
Phase 2
2.1 Years
Phase 3
2.5 Years
~12 Years
Average Time to Market
(New Drug)
Source: ClinicalTrials.gov database (5/17), FDAReview.org (2016)
Number of Registered Clinical Trials posted on ClinicalTrails.gov.
KP INTERNET TRENDS 2017 | PAGE 304
New Data Streams =
Enhancing & Perhaps Accelerating Clinical Trials
63%
28%
55%
83%
8%
76%
46%
76%
94%
26%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Phase I to Phase II Phase II to Phase
III
Phase III to
NDA/BLA
NDA/BLA to
Approval
Phase I to
Approval
Probability of SuccessWithout Biomarkers
With Selection Biomarkers
Source: Biotechnology Innovation Group, Biomedtracker, Amplion (5/16)
Note: Based on 9,985 phase transitions of trials between 2006 2015. 512 phase transitions incorporated selection biomarkers for patient
stratification; phase transitions identified by mapping NCT numbers from ClinicalTrials.gov with Amplion's BiomarkerBase and Biomedtracker's
transition database.
Selection Biomarkers (Enabled by DNA Sequencing) for Enrolling
Patients in Clinical Trials Improves Probability of Success
KP INTERNET TRENDS 2017 | PAGE 305
Data Silos = Breaking Down Owing to Broad Efforts to
Share Data Among Scientific Community
1.9
25.4
0
5
10
15
20
25
30
2009 2010 2011 2012 2013 2014 2015 2016
Total Number of Registered Clinical Trials with Posted Results (K)Growth in Publically-Available Clinical
Trial Results
Source: ClinicalTrials.gov database (5/17), Nature (7/14)
Number of Registered Studies with Public Results posted on ClinicalTrials.gov. ClinicalTrials.gov launched results database in September 2008
so earliest available full year is 2009.
In 2014, Nature launched a peer reviewed open-
access scientific journal focused on publishing
datasets in machine-readable format for sharing
across the natural sciences. Nature encourages
authors to submit to Scientific Data in parallel but
requires authors to enter the following data in
community-endorsed, public repository prior to
publishing in Nature:
+
Mandatory deposition
Suitable repositories
Protein sequences
Uniprot
DNA and RNA sequences
Genbank
DNA DataBank of Japan
EMBL Nucleotide Sequence Database
DNA and RNA sequencing data
NCBI Trace Archive
NCBI Sequence Read Archive
Genetic polymorphisms
dbSNP
dbVar
European Variation Archive
Linked genotype and phenotype data dbGAP
The European Genome-phenome Archive
Macromolecular structure
Worldwide Protein Data Bank
Biological Magnetic Resonance Data Bank
Electron Microscopy Data Bank
Microarray data
Gene Expression Omnibus
ArrayExpress
Crystallographic data for small
molecules
Cambridge Structural Database
KP INTERNET TRENDS 2017 | PAGE 306
As Data Accumulates & Silos Breakdown
Research Insights Could Accelerate
Source: Wired (11/09), National Academy of Engineering (David Eddy, 2015)
Note: The UK Department of Health launched a trial study, Collaborative Atorvastatin Diabetes Study (Cards), and the American Diabetes
Association asked David Eddy to conduct a simulation addressing the same issues before the UK results were released.
Growing Evidence That Data =
Cheaper + Faster Clinical Trials
Traditional Trial vs. Simulation
Traditional UK
Department
of Health Study
Archimedes Data
Simulation
Number of
Patients
2,838
50,000
Years of Data
7 Years
30 Years
Length of
Study
7 Years
2 Months
Conclusion
Out of 4 principal findings Archimedes predicted
2 exactly right, 1 within the margin of error, and 1
slightly below.
Archimedes Simulation = a mathematical model to simulate (1) human
physiology and disease, (2) care process models, and (3) healthcare system
resources. Ran virtual trials of large, simulated populations in a fraction of the
time and cost of a traditional study.
KP INTERNET TRENDS 2017 | PAGE 307
Data Insight + Translation =
Healthcare Delivery
Could Change Faster With
Consumer Engagement &
Faster Innovation Cycles
KP INTERNET TRENDS 2017 | PAGE 308
40%
48%
34%
42%
26%
38%
21%
31%
10%
23%
8%
56%
0%
10%
20%
30%
40%
50%
60%
Own a Wearable
Go Online to Find
Physician
Select Provider Based
on Online Reviews
Have Sought Remote
Medical Care / Advice*
% of RespondentsMillennial
Gen X
Baby Boomer
Consumers = Increasingly Expect Digital Health Services
Especially Millennials
Source: Rock Health Digital Health Consumer Adoption (12/16)
*Represents % of Millennials that have sought medical care/advice over live video, % of Gen X that have over text message, and % of Baby
Boomers who have over phone
Millennials include 18-34 year olds; Gen X include 35-54 year olds; Baby Boomers include 55+ year olds
Digital Health Adoption Across Generations
KP INTERNET TRENDS 2017 | PAGE 309
Consumers = Increasingly Use Digital Health Tools
Consumers Using Digital Health Tools (Telemedicine, Wearables, etc.)
88% Using at Least One Tool, 1 in 10 are Super Adopters
Source: Rock Health Digital Health Consumer Adoption (12/16)
Based on consumer survey of n=4,015; number of digital health categories used by respondent
20%
28%
32%
11%
6%
2%
12%
19%
23%
23%
13%
10%
0%
5%
10%
15%
20%
25%
30%
35%
40%
0
1
2
3
4
5+
% of Respondents2015
2016
Non-Adopter
Super Adopter
KP INTERNET TRENDS 2017 | PAGE 310
Healthcare Practices = Being Re-Imagined
Leveraging Data to Optimize Outcomes
Source: PBS, Propeller Health, TechCrunch, Livongo, Ayasdi, Flatiron, Xconomy, Kinsa, Omada
Patient Empowerment
& Health Management
Propeller Health + Bluetooth
Inhaler Sensor = Improved
Medication Adherence +
Insights
Livongo + Connected Glucose
Meter = Personalized Coaching
+ $100/Month Savings for
Payers
Improvements to
Clinical Pathways /
Protocol
Ayasdi AI + Mercy Health
System Patient Data = Clinical
Anomaly Detection + Improved
Clinical Pathway Development
Flatiron + Foundation Med (FMI)
= 20,000 Liked Cancer Patients
Records + Personalized
Medicine
Preventative Health
Kinsa + Crowdsourced
Temperature Data = Local Flu
Predictions + Proactive
Treatments for Populations
Omada + Preventative Program
= 4-5% Body Weight Reduction
+ Reduced Risk for Stroke and
Heart Disease
KP INTERNET TRENDS 2017 | PAGE 311
Digital Health =
Could It Follow Tech-Like Rapid Adoption Curves?
Source: The Economist (12/15), Pew Research Center (1/17)
*Social Media Adoption based on founding date of MySpace (2003) and Social Media Penetration calculated by Pew Research Center
Acceleration of Technological Adoption Curves 1867-2017
Electricity (46)
Telephone (35)
Radio (31)
Television (26)
PC (16)
Cellphone (13)
Internet (7)
Social
Media (5)
0
5
10
15
20
25
30
35
40
45
50
1867 1877 1887 1897 1907 1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 2017
Years until used by 25% of American Population
KP INTERNET TRENDS 2017 | PAGE 312
Evolution of Genomics =
Case Study in
Virtuous Cycle of Innovation
InputData Accumulation
InsightTranslation
KP INTERNET TRENDS 2017 | PAGE 313
Genomics Digitizes = Gets Faster / Better / Cheaper
Introduction of Digital Technology Accelerates Cost
Reduction Faster Than Moore's Law
Source: National Institute of Health, National Human Genome Research Institute (7/17), Biology Reference, Illumina
$1K
$10K
$100K
$1M
$10M
$100M
Cost to Sequence (per Genome)2007: Digital Technology Leads To Cost
Reduction
Illumina (Solexa) Launches the Genome Analyzer
Time to sequence a genome: 10 Months
Moore's Law
2015: Step Function Reduction In Cost
Illumina Launches the X10
Time to sequence a genome: 27 hours
KP INTERNET TRENDS 2017 | PAGE 314
Accumulation of Genomic Data Leads to
19x Increase in Genomic Knowledge
Source: PloS Biology (7/15), SNPedia (5/17)
SNPs (Single Nucleotide Polymorphisms) represent nucleotides where the DNA of different people vary; variants can be predictive of disease
risk, drug efficacy, and phenotypic differences
4.5
88
2
422
0
20
40
60
80
100
120
1
10
100
1K
10K
100K
1MM
Known SNPs (Variants) in SNPedia(K)Cumulative Number of Human Genomes (log)SNPs
Number of Human Genomes
Insight (Measured in Known Variants) Tracks
Number Of Genomes Sequenced
KP INTERNET TRENDS 2017 | PAGE 315
Genomics Research & Insights Lead to Rapid Increase in
Available Genetic Tests
Source: Genetests (5/17)
Genetic Disorders with Diagnostic Tests Available, 5/29/2017
114
5,007
0
1,000
2,000
3,000
4,000
5,000
6,000
Number of Disorders
KP INTERNET TRENDS 2017 | PAGE 316
Genomics Insight Translates to Therapeutics
Source: Personalized Medicine Coalition (2017)
*Number of personalized medicines calculated based on PMC's Case for Personalized Medicine and the FDA's Table of Pharmacogenomic
Biomarkers in Drug Labeling
Number of Personalized* Medicines Up
From Almost None in 2008, 2008-2016
5
36
81
106
132
0
20
40
60
80
100
120
140
2008
2010
2012
2014
2016
Number of Personalized Medicines
KP INTERNET TRENDS 2017 | PAGE 317
Evolution of Genomics Technologies Enable Deeper Research
Consumer Genomics Evolving Similarly
Source: PubMed, Helix
Based on PubMed queries for peer-reviewed articles on genotyping and sequencing
SNP Arrays and
Genotyping (v1.0)
Identifies variations in
specific, pre-defined single
letters within a gene
Next Generation
Sequencing (v2.0)
Looks for variations
throughout the entire gene
Research
Consumer
844
0
200
400
600
800
1000
PubMed Genotyping Articles 8,904
0
2000
4000
6000
8000
10000
PubMed Sequencing Articles
KP INTERNET TRENDS 2017 | PAGE 318
Digitization = Democratization
Source: Helix (5/17)
Digitization = Enabling New Business Models in Genomics
More Empowered +
Informed Consumers
Query Often: Ecosystem of
Products from Partner
Organizations
DNA Sequenced Once
KP INTERNET TRENDS 2017 | PAGE 319
Healthcare @ Digital Inflection Point
Source: History of Nephrology, Welch Allyn, Medisave, Kinsa
100 Years Ago
Human Touch
25 Years Ago
Machine Assisted / Analog
Today
Technology Enabled / Digital
KP INTERNET TRENDS 2017 | PAGE 320
GLOBAL PUBLIC / PRIVATE
INTERNET COMPANIES =
IT'S BEEN A GOOD TIME TO BE A
LEADER / INNOVATOR
KP INTERNET TRENDS 2017 | PAGE 321
Global Internet Companies =
An Epic Half-Decade for
Public + Private
Internet Companies
KP INTERNET TRENDS 2017 | PAGE 322
2017 Global Internet Market Capitalization Leaders = Most Extending Leads
Apple / Google-Alphabet / Amazon / Facebook / Tencent / Alibaba
Rank Company
Region
Current Market
Value ($B)
1
Apple
USA
$801
2
Google - Alphabet
USA
680
3
Amazon
USA
476
4
Facebook
USA
441
5
Tencent
China
335
6
Alibaba
China
314
7
Priceline
USA
92
8
Uber
USA
70
9
Netflix
USA
70
10
Baidu
China
66
11
Salesforce
USA
65
12
Paypal
USA
61
13
Ant Financial
China
60
14
JD.com
China
58
15
Didi Kuaidi
China
50
16
Yahoo!
USA
49
17
Xiaomi
China
46
18
eBay
USA
38
19
Airbnb
USA
31
20
Yahoo! Japan
Japan
26
Total
$3,827
Source: CapIQ, CB Insights, Wall Street Journal, media reports. Market value data as of 5/26/17.
Note: For public companies, colors denote current market value relative to Y/Y market value. Green = higher. Red = lower. Yel low = private companies, where market
value represents latest publicly announced valuation. Ant Financial and Didi Kuaidi valuation per latest media reports as of 6/16 and 4/17 respectively. Xiaomi valuation
per latest media reports as of 4/17 Ant Financial treated separately from Alibaba as Alibaba retains no control of Ant and will receive a capped lump sum payment in the
event of an Ant liquidity event. Cash includes cash and equivalents and short-term marketable securities plus long-term marketable securities where deemed liquid.
KP INTERNET TRENDS 2017 | PAGE 323
Global Public Companies =
An Epic Half-Decade for
Internet Companies
KP INTERNET TRENDS 2017 | PAGE 324
2017 Global Market Capitalization Leaderboard =
Tech = 40% of Top 20 Companies100% of Top 5
Rank Company
Region
Industry
Segment
Current Market
Value ($B)
2016
Revenue ($B)
1
Apple
USA
Tech Hardware
$801
$218
2 Google / Alphabet
USA
Tech Internet
680
90
3 Microsoft
USA
Tech Software
540
86
4 Amazon
USA
Tech Internet
476
136
5
Facebook
USA
Tech Internet
441
28
6 Berkshire Hathaway
USA
Financial Services
409
215
7
Exxon Mobil
USA
Energy
346
198
8
Johnson & Johnson
USA
Healthcare
342
72
9
Tencent
China
Tech Internet
335
22
10 Alibaba
China
Tech Internet
314
21
11 JP Morgan Chase
USA
Financial Services
303
90
12
ICBC
China
Financial Services
264
85
13 Nestl
Switzerland
Food / Beverages
263
88
14 Wells Fargo
USA
Financial Services
262
85
15 Samsung Electronics
Korea
Tech Hardware
259
168
16 General Electric
USA
Industrial
238
120
17 Wal-Mart
USA
Retail
237
486
18 AT&T
USA
Telecom
234
164
19 Roche
Switzerland
Healthcare
233
51
20 Bank of America
USA
Financial Services
231
80
Total
$7,207
$2,497
Source: CapIQ. Market value data as of 5/26/17
Note: For public companies, colors denote current market value relative to Y/Y market value. Green = higher, red = lower.
KP INTERNET TRENDS 2017 | PAGE 325
2012 Global Market Capitalization Leaderboard =
Tech = 20% of Top 20 Companies40% of Top 5
Rank Company
Region
Industry
Segment
5/31/2012
Value ($B)
2011
Revenue ($B)
1
Apple
USA
Tech Hardware
$540
$128
2
Exxon Mobil
USA
Financial Services
368
434
3
PetroChina
China
Energy
267
318
4 Microsoft
USA
Tech Software
245
72
5
ICBC
China
Financial Services
227
70
6 Wal-Mart
USA
Retail
224
447
7
IBM
USA
Tech Hardware
223
107
8 China Mobile
China
Telecom
203
84
9 General Electric
USA
Industrial
202
143
10 AT&T
USA
Telecom
200
127
11 Royal Dutch Shell
Netherlands
Energy
197
470
12 Berkshire Hathaway
USA
Financial Services
196
141
13 Chevron
USA
Energy
194
236
14 Google / Alphabet
USA
Tech Internet
189
38
15 Nestl
Switzerland Food / Beverages
180
90
16
China Construction
Bank
China
Financial Services
173
58
17 Johnson & Johnson
USA
Healthcare
171
65
18 Procter & Gamble
USA
Consumer Goods
171
84
19 Wells Fargo
USA
Financial Services
170
73
20 BHP Billiton
Australia
Metals / Mining
170
75
Total
$4,512
$3,257
Source: CapIQ. Market value data as of 5/31/12.
Note: For public companies, colors denote current market value relative to Y/Y market value. Green = higher, red = lower.
KP INTERNET TRENDS 2017 | PAGE 326
Big Get Bigger =
& Go After Other Bigs
Often Led by Founder-Driven
Innovation / Seeing Around Corners
KP INTERNET TRENDS 2017 | PAGE 327
Internet Bigs Expansion / Growth =
A Long Way from Where They Started
Company
Founding
Year
Original
Business
Current
Businesses
Apple
1976
Personal Computer Maker
Smartphone / Computer / Tablet MakerContent / Media
MarketplaceCloud Services
Google - Alphabet
1998
Online Search Engine
Online Search EngineAd EcosystemWeb BrowserMobile
Operating System(s)Digital Video PlatformContent
MarketplaceMobile + IoT / OTT Device MakerNavigation
ToolsProductivity SoftwareCloud ServicesAR / VR Software
+ HardwareMoonshot Chaser
Amazon
1994
Online Bookseller (USA)
Global B2B B2C / C2C CommerceContent EcosystemDigital
Video / Music PlatformeReader / Tablet / IoT / OTT Device
MakerCloud ServicesLogisticsAd Ecosystem
Facebook
2004
Social Network (USA)
Global Social NetworkInstant Messaging PlatformImage
Sharing PlatformAR / VR Software / HardwareAd Ecosystem
Tencent
1998
Instant Messaging Platform
(China)
Instant Messaging PlatformGamingContent
EcosystemSocial NetworkAd EcosystemPaymentsDigital
Video / Music PlatformCloud Services
Alibaba
1999
B2B Commerce Platform
(China)
Global B2B / B2C / C2C Commerce PlatformNew RetailAd
Ecosystem PaymentsCloud ServicesLogistics Data
PlatformDigital Media & Entertainment PlatformContent
EcosystemContent CreatorWeb Browser
Source: Company filings
KP INTERNET TRENDS 2017 | PAGE 328
Global Technology Financings =
Strong Relative to History
Slowing @ Margin
KP INTERNET TRENDS 2017 | PAGE 329
Global Technology Financings =
Strong Relative to HistorySlowing @ Margin
$3 $3
$8 $7 $5
$14
$26
$19
$28
$89
$157
$58
$28
$22
$36 $40 $36
$42
$34
$25
$33
$48 $50 $44
$107
$96
$89
$30
$0
$50
$100
$150
$200
Technology IPO Volume
($B)
Technology Private
Financing Volume ($B)
NASDAQ
Annual Technology IPO and Technology Private Financing Volume ($B)Global USA-Listed Technology IPO Issuance &
Global Technology Venture Capital Financing, 1990 2017YTD
VC Funding per
Company ($MM)
$3
$3
$2
$5
$4
$4
$5
$5
$6
$8 $14 $18 $11 $8
$8
$9
$8
$9
$8
$9
$7
$7 $10 $8
$9 $13 $15 $18 $19
Source: Morgan Stanley Equity Capital Markets, 2017YTD as of 5/12/17, Thomson ONE 2017YTD as of 5/12/17. All global U.S.-listed technology
IPOs over $30MM, data per Dealogic, Bloomberg, & Capital IQ. VC Funding per Company ($MM) calculated as total venture financing per year
divided by number of companies receiving venture financing.
*Facebook ($16B IPO) = 75% of 2012 IPO $ value. **Alibaba ($25B IPO) = 69% of 2014 IPO $ value. ***Snap ($4B IPO) = 74% of 2017 YTD $
value.
KP INTERNET TRENDS 2017 | PAGE 330
Global Technology
Mergers & Acquisitions =
Robust Relative to History
KP INTERNET TRENDS 2017 | PAGE 331
Global Technology Merger & Acquisition Volume =
Robust Relative to History
Global Technology M&A Deals, 2010-2016
$100
$138
$72
$145
$179
$365
$336
273
331
229
245
356
414
439
0
100
200
300
400
500
600
$0
$50
$100
$150
$200
$250
$300
$350
$400
$450
2010
2011
2012
2013
2014
2015
2016
Number of TransactionsM&A Volume ($B)M&A Volume
Number of Transactions
Source: Morgan Stanley, Thomson Research
KP INTERNET TRENDS 2017 | PAGE 332
There are pockets of Internet
company overvaluation but there are
also pockets of undervaluation...
Very few companies will win
those that do can win big...
Over time, best rule of thumb for
valuing companies =
value is present value of future cash flows.
Value of a Business
KP INTERNET TRENDS 2017 | PAGE 333
Global Public / Private Internet Companies =
It's Been a Good Time to be a Leader / Innovator
1) Global Internet Companies = An Epic Half-Decade for Public + Private Internet
Companies
2) Global Public Companies = An Epic Half-Decade for Internet Companies
3) Big Get Bigger = & Go After Other BigsOften Led by Founder-Driven
Innovation / Seeing Around Corners
4) Global Technology Financings = Strong Relative to HistorySlowing @ Margin
5) Global Technology Mergers & Acquisitions = Robust Relative to History
6) Value of a Business
KP INTERNET TRENDS 2017 | PAGE 334
SOME MACRO THOUGHTS
KP INTERNET TRENDS 2017 | PAGE 335
USA, Inc.* =
Understanding Where Your
Tax Dollars Go
* USA, Inc. Full Report: http://www.kpcb.com/blog/2011-usa-inc-full-report
KP INTERNET TRENDS 2017 | PAGE 336
USA Income Statement =
-19% Average Net Margin Over 25 Years
USA Income Statement, F1986 F2016
Source: Congressional Budget Office, White House Office of Management and Budget
Note: USA federal fiscal year ends in September. Non-defense discretionary includes federal spending on education, infrastructure, law
enforcement, judiciary functions.
* Individual & corporate income taxes include capital gains taxes.
F1986
F1991
F1996
F2001
F2006
F2011
F2016
Comments
Revenue ($B)
$769
$1,055
$1,453
$1,991
$2,407
$2,303
$3,267
+5% Y/Y average over 25 years
Y/Y Growth
5%
2%
7%
-2%
12%
7%
1%
Individual Income Taxes*
$349
$468
$656
$994
$1,044
$1,091
$1,546
Largest driver of revenue
% of Revenue
45%
44%
45%
50%
43%
47%
47%
Social Insurance Taxes
$284
$396
$509
$694
$838
$819
$1,115
Social Security & Medicare payroll tax
% of Revenue
37%
38%
35%
35%
35%
36%
34%
Corporate Income Taxes*
$63
$98
$172
$151
$354
$181
$300
Fluctuates with economic conditions
% of Revenue
8%
9%
12%
8%
15%
8%
9%
Other
$73
$93
$115
$152
$171
$212
$316
Estate & gift taxes, duties / fees
% of Revenue
10%
9%
8%
8%
7%
9%
10%
Expense ($B)
$990
$1,324
$1,560
$1,863
$2,655
$3,603
$3,854
+4% Y/Y average over 15 years
Y/Y Growth
5%
6%
3%
4%
7%
4%
4%
Entitlement / Mandatory
$416
$597
$787
$1,008
$1,412
$2,026
$2,429
Risen owing to rising healthcare costs +
% of Expense
42%
45%
50%
54%
53%
56%
63%
aging population
Non-Defense Discretionary
$165
$214
$267
$343
$497
$648
$600
Education / law enforcement /
% of Expense
17%
16%
17%
18%
19%
18%
16%
transportation / general government
Defense
$274
$320
$266
$306
$520
$699
$584
2006 increase driven by War on Terror
% of Expense
28%
24%
17%
16%
20%
19%
15%
Net Interest on Public Debt
$136
$194
$241
$206
$227
$230
$241
Recent benefit of historic low interest rates
% of Expense
14%
15%
15%
11%
9%
6%
6%
Surplus / Deficit ($B)
($221)
($269)
($107)
$128
($248)
($1,300)
($587)
-19% average net margin, 1991-2016
Net Margin (%)
-29%
-26%
-7%
6%
-10%
-56%
-18%
KP INTERNET TRENDS 2017 | PAGE 337
USA Income Statement =
What Net Losses in 45 of 50 Years Look Like
USA Annual Profits & Losses, 1967 2016
($1,600)
($1,400)
($1,200)
($1,000)
($800)
($600)
($400)
($200)
$0
$200
$400
USA Inc. Annual Net Profit / Loss ($B)Source: Congressional Budget Office, White House Office of Management and Budget
Note: USA federal fiscal year ends in September.
* Individual & corporate income taxes include capital gains taxes. Non-defense discretionary includes federal spending on education,
infrastructure, law enforcement, judiciary functions.
KP INTERNET TRENDS 2017 | PAGE 338
When Spending > Income Debt Rises =
Net Debt / GDP @ 77%Higher than 97% of USA's History
USA Net Debt / GDP Ratio, 1790 2016
0%
20%
40%
60%
80%
100%
120%
1790
1815
1840
1865
1890
1915
1940
1965
1990
2015
USA Net Debt / GDP (%)Historical Net Debt / GDP (%)
World War II =
~105%
World War I =
~30%
Civil War =
~30%
2016 =
77%
Source: Congressional Budget Office Long-Term Outlook (3/17), Wall Street Journal
KP INTERNET TRENDS 2017 | PAGE 339
@ Current Course / Speed (& If Government Projections are Correct)
USA Net Debt / GDP Ratio Will Break WWII Record by 2035
USA Net Debt / GDP Ratio, 1790 2047E
0%
20%
40%
60%
80%
100%
120%
140%
160%
1790
1815
1840
1865
1890
1915
1940
1965
1990
2015
2040
USA Net Debt / GDP (%)Historical Net Debt / GDP (%)
Projected Net Debt / GDP (%)
1946 =
~105%
2034E =
~105%
Source: Congressional Budget Office Long-Term Outlook (3/17), Wall Street Journal
KP INTERNET TRENDS 2017 | PAGE 340
USA = 9th Highest Public Debt / GDP Level
Relative to Other Major Economies
Rank Country
% of GDP
2015 Public
Government
Debt ($B)
1
Japan
248%
$10,083
2 Greece
177
347
3
Lebanon
138
68
4
Italy
133
2,342
5
Portugal
129
257
6
Jamaica
120
20
7
Cyprus
109
20
8
Belgium
106
478
9
United States
105
18,870
10 Singapore
105
302
11 Spain
99
1,124
12 France
96
2,236
13
Jordan
93
33
14 Canada
91
1,335
15 United Kingdom
89
2,458
16 Egypt
89
280
17 Croatia
87
40
18 Austria
86
302
19 Slovenia
83
30
20 Ukraine
80
37
Source: IMF
Note: Ranking excludes countries with public debt less than $10B in 2015. Public debt includes federal, state and local government debt but
exclude unfunded pension liabilities from government defined-benefit pension plans and debt from public enterprises and central banks.
KP INTERNET TRENDS 2017 | PAGE 341
45%
63%
24%
15%
16%
16%
15%
6%
0%
20%
40%
60%
80%
100%
1991
2016
US Mandatory Entitlements (%)Entitlements / Mandatory
Defense
Non-Defense Discretionary
Net Interest Cost
USA Entitlements = 63% of Spending vs. 45% 25 Years Ago
Interest Expense Down as % Owing to Interest Rate Declines
USA Expenses by Category, 1991-2016
$1.3T
$3.9T
10%
8%
6%
4%
2%
0%
USA 10Y Treasury Yield (%)Change by
Category,
1991-2016
Debt:
+$11T / +427%
Entitlements:
+$1.8T / +307%
Non-Defense
Discretionary:
+$387B / +181%
Defense:
+$264B / +83%
Net Interest Cost:
+$46B / +24%
10Y Treasury
Source: Congressional Budget Office, White House Office of Management and Budget, US Treasury
Note: Yellow line represents yield on 10-year US Treasury bill from 12/31/91 to 12/31/16.
KP INTERNET TRENDS 2017 | PAGE 342
USA Entitlements = +$1.8 Trillion Over 25 Years
Paced by Medicare + Medicaid Growth
$267
$910
$114
$692
$53
$368
$163
$459
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
1991
2016
USA Mandatory Entitlements ($B)Social Security
Medicare
Medicaid
Income Security
USA Mandatory Outlays by Category ($B), 1991-2016
15%
19%
28%
45%
19%
9%
27%
37%
$597B
45% of
Expenses
$2.4T
63% of
Expenses
Source: Congressional Budget Office, White House Office of Management and Budget
Note: Numbers may not sum due to rounding.
KP INTERNET TRENDS 2017 | PAGE 343
0%
20%
40%
60%
80%
100%
1990
2016
% of Median Household IncomeRemaining Household Median Income
Entitlements / Household
$6K
$18K
$23K
$38K
Entitlements =
20% of median household income
USA Entitlements = Equivalent to
32% of Average Annual Income per Household vs. 20% 25 Years Ago
Median Household Income vs. Effective Entitlement $ Paid per Household,
USA, 1990-2016
Entitlements =
32% of median household income
Source: Congressional Budget Office, US Census Bureau
Note: Based on median income math. Median income in current $ as of year specified. Effective entitlement dollars per household represents
total entitlements over total US households (current $ as of year specified).
KP INTERNET TRENDS 2017 | PAGE 344
Household Debt = Back @ Peak (Q3:08) Level & Rising
Now vs. Q3:08 = Mortgage Debt (-7%) / Student Loans (+120%) / Auto Loans (+44%)
0%
5%
10%
15%
20%
$0
$3
$6
$9
$12
$15
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
U6 Unemployment Rate* (%)Total Household Debt ($T)Mortgage
Home Equity Revolving
Auto
Credit Card
Student Loan
Other
U6 Unemployment*
$13T
$13T
Household Debt By Category ($T) & U6* Unemployment (%), USA, 2003-2017
Source: Federal Reserve Bank of New York Consumer Credit Panel / Equifax, Quarterly Household Debt and Credit Report, Q1:17; St. Louis
Federal Reserve FRED Database
* U6 Unemployment Rate defined as total unemployed persons plus all marginally attached workers plus persons employed part time for
economic reasons.
KP INTERNET TRENDS 2017 | PAGE 345
USA Rising
Debt Commitments =
Non-Trivial Challenges that
Need to Be Addressed
KP INTERNET TRENDS 2017 | PAGE 346
Immigration =
Important for USA
Technology Job Creation
Immigration Full Report: http://www.kpcb.com/blog/immigration-in-america-the-growing-shortage-of-high-skilled-workers
KP INTERNET TRENDS 2017 | PAGE 347
USA = 60% of Most Highly Valued Tech Companies Founded By
1st or 2nd Generation Americans1.5MM Employees, 2016
Immigrant Founders / Co-Founders of Top 25 USA Valued Public
Tech Companies, Ranked by Market Capitalization
Source: CapIQ as of 5/31/17. "The 'New American' Fortune 500" (2011), a report by the Partnership for a New American Economy, as well as
"Reason for Reform: Entrepreneurship" (10/16); "American Made, The Impact of Immigrant Founders & Professionals on U.S. Corporations."
*While Andy Grove (from Hungary) is not a co-founder of Intel, he joined as COO on the day it was incorporated.
**Francisco D'souza is a person of Indian origin born in Kenya.
***Max Levchin / Luke Nosek / Peter Thiel's startup Confinity merged with Elon Musk's startup X.com to form Paypal in March 2000.
Rank
Company
Mkt Cap
($MM)
LTM Rev
($MM)
Employees
1st or 2nd Gen Immigrant
Founder / Co-Founder
Generation
1 Apple
$800,898
$220,457
116,000
Steve Jobs
2nd-Gen, Syria
2 Alphabet / Google
$679,533
$94,765
73,992
Sergey Brin
1st-Gen, Russia
3 Microsoft
$540,127
$87,247
114,000
--
--
4
Amazon.com
$475,958
$142,573
341,400
Jeff Bezos
2nd-Gen, Cuba
5 Facebook
$440,900
$30,288
18,770
Eduardo Saverin
1st-Gen, Brazil
6 Oracle
$186,230
$37,429
136,000
Larry Ellison /
Bob Miner
2nd-Gen, Russia /
2nd-Gen, Iran
7
Intel
$170,748
$60,481
106,000
--*
--
8 Cisco
$157,502
$48,510
73,390
--
--
9
IBM
$143,264
$79,390
380,300
Herman Hollerith
2nd-Gen, Germany
10 Priceline
$91,597
$11,014
20,500
--
--
11 Qualcomm
$84,982
$23,243
30,500
Andrew Viterbi
1st-Gen, Italy
12 NVIDIA
$84,395
$7,542
10,299
Jensen Huang
1st-Gen, Taiwan
13 Texas Instruments
$80,822
$13,764
29,865
Cecil Green /
J. Erik Jonsson
1st-Gen, UK /
2nd-Gen, Sweden
14 Adobe Systems
$70,193
$6,153
15,706
--
--
15 Netflix
$70,007
$9,510
3,300
--
--
16 Salesforce.com
$64,611
$8,863
25,000
--
--
17 PayPal
$61,492
$11,273
18,100
Max Levchin /
Luke Nosek /
Peter Thiel /
Elon Musk***
1st-Gen, Ukraine /
1st-Gen, Poland /
1st-Gen, Germany /
1st-Gen, South Africa
18 Applied Materials
$48,896
$12,942
15,600
--
--
19 Yahoo!
$48,570
$5,409
8,500
Jerry Yang
1st-Gen, Taiwan
20
Automatic Data
Processing
$45,345
$12,213
57,000
Henry Taub
2nd-Gen, Poland
21 Activision Blizzard
$43,923
$6,879
9,400
--
--
22 VMware
$39,538
$7,093
18,905
Edouard Bugnion
1st-Gen, Switzerland
23 Cognizant Technology
$39,339
$13,831
261,200
Francisco D'souza /
Kumar Mahadeva
1st-Gen, India** /
1st-Gen, Sri Lanka
24 eBay
$37,774
$9,059
12,600
Pierre Omidyar
1st-Gen, France
25
Intuit
$35,501
$5,089
7,900
--
--
KP INTERNET TRENDS 2017 | PAGE 348
USA = ~50% of Most Highly Valued Private Tech Companies Founded By
1st Generation Immigrants...>48K Jobs, 5/17
Source: Based on analysis by National Foundation For American Policy, "Immigrants and Billion Dollar Startups", Stuart Anderson, 2016,
subsequently updated by Aimee Groth, Quartz, 4/17. Valuation data from Wall Street Journal, CB Insights, headcount from LinkedIn (5/17).
Note: Due to varying definitions of unicorns, may not align with various unicorn lists. As of 5/17 there are 100 US-based, venture-backed unicorns
(including rumored valuations), 50 of which have at least one first-generation immigrant founder.
Company
Immigrant
Founder / Co-Founder
Country of
Origin
Market
Value ($B)
Uber
Garrett Camp
Canada
$68
Palantir
Peter Thiel
Germany
20
WeWork
Adam Neumann
Israel
17
SpaceX
Elon Musk
South Africa
12
Stripe
John Collison,
Patrick Collison
Ireland
9
Slack
Stewart Butterfield,
Serguei Mourachov,
Cal Henderson
Canada /
Russia / UK
4
Credit Karma
Kenneth Lin
China
4
Tanium
David Hindawi
Iraq
4
Instacart
Apoorva Mehta
India
3
Wish
(ContextLogic)
Peter Szulczewski,
Danny Zhang
Canada
3
Moderna
Therapeutics
Noubar Afeyan,
Derrick Rossi
Armenia /
Canada
3
Bloom Energy
KR Sridhar
India
3
Oscar Health
Mario Schlosser
Germany
3
Houzz
Adi Tatarko, Alon Cohen
Israel
2
Avant
Al Goldstein,
John Sun, Paul Zhang
Uzbekistan /
China / China
2
Zenefits
Laks Srini
India
2
ZocDoc
Oliver Kharraz
Germany
2
AppNexus
Mike Nolet
Holland
2
Sprinklr
Ragy Thomas
India
2
The Honest
Company
Brian Lee
South Korea
2
Zoox
Tim Kentley-Klay
Australia
2
Jawbone
Alexander Asseily
UK
2
JetSmarter
Sergey Petrossov
Russia
2
Quanergy
Louay Eldada,
Tianyue Yu
Lebanon /
China
2
Mu Sigma
Dhiraj Rajaram
India
2
Company
Immigrant
Founder / Co-Founder
Country of
Origin
Market
Value ($B)
Razer
Min-Liang Tan
Singapore
$2
Unity Technologies
David Helgason
Iceland
2
FanDuel
Nigel Eccles,
Tom Griffiths,
Lesley Eccles
UK
1
Medallia
Borge Hald
Norway
1
Apttus
Kirk Krappe
UK
1
Robinhood
Baiju Bhatt,
Vlad Tenev
India /
Bulgaria
1
Rubrik
Bipul Sinha
India
1
Infinidat
Moshe Yanai
Israel
1
Warby Parker
Dave Gilboa
Sweden
1
Actifio
Ash Ashutosh
India
1
Anaplan
Guy Haddleton,
Michael Gould
New Zealand /
UK
1
Gusto
Tomer London
Israel
1
Proteus Digital
Health
Andrew Thompson
UK
1
AppDirect
Daniel Saks,
Nicolas Desmarais
Canada
1
Carbon3D
Alex Ermoshkin
Russia
1
CloudFlare
Michelle Zatlyn
Canada
1
Compass
Ori Allon
Israel
1
Eventbrite
Renaud Visage
France
1
Evernote
Stepan Pachikov,
Phil Libin
Azerbaijan /
Russia
1
Offerup
Arean Van Veelen
Netherlands
1
Tango
Uri Raz, Eric Setton
Israel / France
1
Udacity
Sebastian Thrun
Germany
1
Zscaler
Jay Caudhry
India
1
Zoom Video
Eric Yuan
China
1
ForeScout
Noga Alon, Hezy Yeshurun,
Oded Comay,
Doron Skikmoni
Israel
1
KP INTERNET TRENDS 2017 | PAGE 349
High Level,
For All the Angst,
Consider This
KP INTERNET TRENDS 2017 | PAGE 350
World = Getting Better in Many Ways
Down = Poverty + Child MortalityUp = Democracy + Literacy
0%
20%
40%
60%
80%
100%
1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Extreme Poverty
Not in Extreme Poverty
% of People in Extreme Poverty, Global,
1820-2015
0%
20%
40%
60%
80%
100%
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Mortality Rate by Age 5
Survival Rate by Age 5
Child Mortality Rates, Global,
1800-2015
0%
20%
40%
60%
80%
100%
1816 1836 1856 1876 1896 1916 1936 1956 1976 1996
No Democracy
Democracy
% of People Living in Democracy, Global,
1816-2015
0%
20%
40%
60%
80%
100%
1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000
Illiterate Population
Literate Population
Literacy Rate, Global, 1800-2014
Source: Max Roser, Our World in Data; World Bank; Bourguignon and Morrison, "Inequality Among World Citizens", American Economic Review
92.4, 2002; Gapminder; Polity IV; UN Population Division; Wimmer and Min, "From empire to nation-state: Explaining war in the modern world,
1816-2001," American Sociological Review 71.6, 2006; OECD; UNESCO
Note: Extreme poverty defined as income level below $1.90 (int'l dollars) / day. Child mortality rates measured before and after 5 years old.
Democracy based on Polity IV database. Literacy rate based on ages 15+ globally.
KP INTERNET TRENDS 2017 | PAGE 351
Some Macro Thoughts
1) USA, Inc.* =
Understanding Where Your Tax Dollars Go
2) Immigration =
Important for USA Technology Job Creation
3) High Level =
For All the Angst, Consider This
** USA, Inc. Full Report: http://www.kpcb.com/blog/2011-usa-inc-full-report
** Immigration Full Report: http://www.kpcb.com/blog/immigration-in-america-the-growing-shortage-of-high-skilled-workers
KP INTERNET TRENDS 2017 | PAGE 352
CLOSING THOUGHTS
KP INTERNET TRENDS 2017 | PAGE 353
Century Economic Growth Drivers
Pre-18th
Cultivation & Extraction
19th-20th
Manufacturing & Industry
21st
Compute Power + Human Potential
Economic Growth Drivers =
Evolve Over Time
KP INTERNET TRENDS 2017 | PAGE 354
Internet Trends 2017
1) Global Internet Trends = SolidSlowing Smartphone Growth
4-9
2) Online Advertising (+ Commerce) = Increasingly Measurable + Actionable
10-80
3)
Interactive Games = Motherlode of Tech Product Innovation + Modern Learning
80-150
4) Media = Distribution Disruption @ Torrid Pace
151-177
5) The Cloud = Accelerating Change Across Enterprises
178-192
6) China Internet = Golden Age of Entertainment + Transportation
193-231
(Provided by Hillhouse Capital)
7)
India Internet = Competition Continues to IntensifyConsumers Winning
232-287
8) Healthcare @ Digital Inflection Point
288-319
9) Global Public / Private Internet Companies
320-333
10) Some Macro Thoughts
334-351
11) Closing Thoughts
352-353
KP INTERNET TRENDS 2017 | PAGE 355
This presentation has been compiled for informational purposes only and should not be
construed as a solicitation or an offer to buy or sell securities in any entity, or to invest in
any KPCB entity or affiliated fund.
The presentation relies on data and insights from a wide range of sources, including
public and private companies, market research firms and government agencies. We cite
specific sources where data are public; the presentation is also informed by non-public
information and insights. We disclaim any and all warranties, express or implied, with
respect to the presentation. No presentation content should be construed as
professional advice of any kind (including legal or investment advice).
We publish the Internet Trends report on an annual basis, but on occasion will highlight
new insights. We may post updates, revisions, or clarifications on the KPCB website.
KPCB is a venture capital firm that owns significant equity positions in certain of the
companies referenced in this presentation, including those at www.kpcb.com/companies.
Any trademarks or service marks used in this report are the marks of their respective
owners, who are not participating partners or sponsors of the presentation or of KPCB or
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Disclaimer