http://www.techcelerate.ventures
Your trusted advisor for raising Series A equity investment in the UK
Prepared by Andrew Chen for
"The red flags and magic numbers that investors look for in your growth metrics (80 slide pdf). Notes live here. I created this deck as part of my interview process at Andreessen Horowitz. I talk through Growth Accounting, why lagging indicators aren't that useful, and how to evaluate Acquisition and Engagement loops"
About Techcelerate Ventures
Tech Investment and Growth Advisory for Series A in the UK, operating in £150k to £5m investment market, working with #SaaS #FinTech #HealthTech #MarketPlaces and #PropTech companies.
Hi there!
Thanks for reading this - I originally published this deck with the note below on my blog - you can read the details here:
https://andrewchen.co/investor-metrics-deck/
Hope you enjoy :)
Andrew
San Francisco, CA
--
Earlier this year, I joined Andreessen Horowitz as a General Partner, where I focus on a broad spectrum of consumer startups: marketplaces, entertainment/media, and social platforms. This
was a big moment for me, and the result of a long relationship that began a decade ago, when Horowitz Andreessen Angel Fund funded a (now defunct) startup I had co-founded. One of the
reasons I've been excited about being a professional investor is the ability to apply my skills as an operator. The same skills needed to grow new products can be used both to evaluate new
startups to invest in, and once we've invested; to help them grow.
The reason for this is that the steps for starting and scaling a new startup share many of the same skills as investing in a new startup: 1) First, we seek to understand the existing state of
customer growth including growth loops, the quality of acquisition, engagement, churn, and monetization. 2) Then, to identify potential upside based learnings from within the company as
well as across benchmarks from across industry. 3) And finally, to prioritize and make decisions that impact the future. Of course, as an investor you can't run A/B tests or analyze results
directly, but you can form hypotheses, ideate, and apply the same type of thinking.
As part of my interview process at a16z, I eventually put together an 80 slide deck on how to use growth ideas to evaluate startups. In the spirit that this perspective can help others in the
ecosystem, and to share my my thinking, I'm excited to publish the deck below.
Disclaimer: This was just one presentation in a 10 year relationship
But before I fully share, I have a disclaimer. This is one presentation I made within a series of dozens of meetings and interactions I had with the Andreessen Horowitz team. It was just one
ingredient. I've been asked by friends and folks on the best path into venture capital. From my experience, it's a long, windy experience others have written about their processes as well.
My journey took a while too:
10 years in the Bay Area (and blogging, building my network, etc)
Dozens of angel investments and advisory roles in SaaS, marketplaces, etc
Once kicked off, 6 months of interviews (dinners, sitting in pitches, analyzing startups)
100+ hours of interviewing and prep
This deck was just one step, but one that I'm proud of, and want to show y'all.
Growth Hacking for
Startups / Venture Capital
Andrew Chen
Prepared for Andreessen Horowitz
"growth hacking"
0 results
"Growth Hacker is the new VP Marketing"
Published April 2012
Years later, the Growth function has
taken off across the industry...
Growth has evolved:
Facebook app growth
Email address book virality
Hacks, tips, and tricks
into a much bigger umbrella
"growth team"
"new user experience"
"user engagement metrics"
"customer acquisition cost"
660+ essays over 10 years
Selection of work
How To (Actually) Calculate CAC
What does a growth team work on?
What's your viral loop?
When and why do apps "jump the shark?"
Losing 80% of mobile users is normal
60% of users opt-out of push notifications
What factors drive DAU/MAU?
Audience
100k email/RSS subscribers
110k Twitter followers
Front page of YC Hacker News
Front page of Google:
growth hacking
product market fit
user growth
growth team
customer acquisition cost
user engagement metrics
viral loops
viral coefficient
push notification click through rate
...
Next step: Pulling together the
top-end of the professional network
Week 1
Growth Models
Week 2
Channels and Loops
Week 3
Growth Roadmap
Week 4
Engagement and Retention
Week 5
Viral Growth
Week 6
Paid Marketing
Week 7
Growth Teams
Week 8
Future of Growth
Growth professional education: 8-Week Agenda
1500+ mid-career professionals from across tech
Personal goals for the future:
Stay ahead of the curve
Bring people and networks together
Put more ideas on paper :)
Let's use frameworks
to assess startup growth!
Growth Frameworks + Startups
Questions
Is it working?
Will it sustain?
Can it improve?
+ New+Reactivated
5,000
-
Inactive
1,000
= Net MAU
4,000
+ Engaged
10,000
= MAU
14,000
The Growth Accounting Framework
New+Reactivated
Tends to look linear or S curve
Only a few loops scale:
Virality, Paid, SEO
Most lack a strong reactivation
strategy
Inactive
Also an S-curve, but lags MAUs
% of Active Users
Sometimes hard churn, usually
lack of frequent use case
Very hard to move this curve!
New + Reactivated - Inactive = 0
Peak MAUs
Problem: Growth Accounting gives lagging metrics
It's just the current snapshot!
You wouldn't invest based on a startup's P&L, Balance Sheet, etc.
Same with Growth Accounting - it talks outputs but not inputs
Not actionable for product teams
+New
+Reactivated
-Inactive
Engaged
Acquisition
Loop
Engagement
Loop
Leading indicators, not lagging
Start with the product's Acquisition and Engagement Loops
How defensible/proprietary?
How scalable and repeatable?
How much upside?
We need to understand the quality of growth
Use Loops to drive the discussion, not Growth Accounting
User Acquisition Loop
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Acquisition Loop
How does a cohort of new users lead to more new users?
Durable, scalable sources of new users are built on loops
Loops are built on existing platforms and networks
(Buy / Build / Partner)
Acquisition Loop: User generated content + SEO
New users find
content
% signup and
create content
Google
indexes
unique content
People search
for content
Acquisition Loop: Paid marketing
New users
click an ad
% sign up to try
product
% convert to
paid features
Budget used to
buy ads
Acquisition Loop: Viral
New users
sign up
Invites /
content sent to
friends
Some % click
on the links
Engage with
invite/content
Measuring loops - and why there's a multiplier
New users
sign up
% import their
contacts
Invites links
sent
Some % click
on the links
30%
10X
40%
50%
Growth Factor = 0.6
1000 signups create +666 more
Other loops are the same:
Spend $5 CAC
Get $10 in profit
Write 1 wiki page
Get 1.5 pages written
Etc
Linear channels are helpful, but don't scale
New users click
an ad
% sign up to try
product
% convert to
paid features
Budget used to
buy ads
PR
Conferences
Content mkting
Partnerships
App Store
features
(Aren't repeatable, don't scale!)
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Example: App Ratings
>50% dropoff at the App Store detail page
#deleteuber
1.7 stars :(
iOS 10.3
Inline app review
modal rolled out
4.7 app rating
(4.4 overall)
*Public App Store data from Appbot
New iOS 10.3 inline review modal
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Example: Mobile Phone # Verification
10-40% dropoff at mobile phone # verification step
Optimizations:
Voice OTP
Android auto-read SMS code
Carrier direct verification (Danal)
Partner<>Carrier deliverability tracking
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Example: Landing Page Optimization
80%+ dropoff on landing pages
A/B testable best practices:
Minimal design with strong CTA
Remove unnecessary form fields
Personalized (to add, inviter, etc.)
Rich media, but no links! (carousel, GIF, video)
Mobile optimized web
Redirect to App Store when mobile
Smart app banner META tag
...
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Loops/Channels Mix
Signups broken down by:
Channels and Loops
Time period
Quality indicators
Proprietary channels and loops
Repeatable/scalable loops
Low platform risk
33/33/33 on organic plus two loops
Red flags
New, unsustainable traffic
Spiky acquisition - ads?
Brittle dependence on one loop
Loops that are actually linear channels
Dec
Jan
Feb
Mar
Apr
brand / Google
1,000
non-brand / Google
10,000
10,000
seo / Google
10,000
10,500
11,025
11,576
12,155
homepage / Organic
2,000
2,100
2,200
2,300
2,400
product hunt / Partner
25,000
2,000
1,000
500
Acquisition Loop Quality
Sources broken down:
Signups, Cost per Signup
Activated, Activation %, CPAU
LTV
MoM increase %
Quality indicators
Steady growth on scalable loops
$ spent on quality signups
Steady growth with high activation
Red flags
Spikes of $ on low quality signups
Signups without activation
CPAU > CPSU > LTV
Source
Signups CPSU Activated CPAU Activation % LTV MoM
brand /
google
non-brand /
google
display /
facebook
feed /
facebook
homepage /
organic
detail page /
organic
seo / google
Platform Dependency
Growth <> Platforms
Loops depend on existing platforms
Build/Buy/Partner
Look at CTR and conversion rates
on-platform over time
Indicators
Stable performance
Durable real estate
Proprietary Product<>Channel fit
$1B versus $10B co - multiple loops
Red flags
Decreasing conversion rates
Easily fast followed
Unstable or shrinking platform
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Applying our acquisition framework
Baseline forecast
Linear and non-linear
Flat on linear channels
Nonlinear projection for loops
Project out to the next financing
MAU and Activated, not just signups!
Dec
Jan
Feb
Mar
Apr
brand / Google
1,000
non-brand / Google
10,000
10,000
seo / Google
10,000
10,500
11,025
11,576
12,155
homepage / Organic
2,000
2,100
2,200
2,300
2,400
product hunt / Partner
25,000
2,000
1,000
500
Bottoms Up Roadmap
Factor in improvements
Bottoms-up roadmap to next
funding round
+5%-10% for minor upgrades
+25-50% for new loops
Share this with the entrepreneurs
afterwards!
Iterate the forecast
Rebuild forecast + risk analysis
Build into Net MAU model
Need Engagement Loop too...
Qualitative risks
Platform + competitive risks
What if a loop goes to zero?
Can this team execute?
but Acquisition's only half the picture!
Let's talk about the Engagement loop
User Engagement Loop
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Engagement Loop
For social apps:
How does one engaged user cause another to be more engaged?
For utility apps:
How does engagement in an app cause future engagement?
Prefer organic, natural use cases over notifications, which should
just be an accelerant
Engagement Loop: Social feedback
User creates
content
Content viewed
by other users
Social
feedback given
on content
Notification
sent to content
creator
Engagement Loop: Personalized content
Users
subscribe / add
New content
comes up
Users are
alerted by
notification or
feed
Users view and
like content
Linear channels for engagement
User creates
content
Content viewed
by other users
Social
feedback given
on content
Notification
sent to content
creator
PR
Promotions
Holiday
New features
...
(Aren't repeatable, don't scale!)
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Kicking off the engagement loop
Activation bends the cohort curve early
Examples from Pinterest's growth team:
"Save" instead of "Pin It"
Interstitial from Mobile web to app
Pin Education
Simplifying Home Feed
+100% lift to activation
(Weekly repinners / Signups)
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Building social graphs
Social feedback loops are dependent on a network
Bootstrap on a pre-existing graph:
"Find friends"
30% will sign in via FB/Google
95% connection rate by layering value props
Other proven tactics:
Reverse addressbook lookup
"Your friend X just joined - add them?"
People You May Know
Post-content creation sharing prompt
After a connection, cross-sell to adding more - build a loop
Red flags
Viral factor > 1 based on spam
Select all on contacts, SMS spam, No skip buttons
Engagement that's all connecting, no core actions
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Inactive users trying to engage
Reactivating users is a huge non-obvious opportunity
for late stage startups
~50-75% of registered users are inactive
They face challenges with trying to engage:
Need to reinstall app
Forgot their username or password
Using a new phone #
Solutions
Treat "Forgot password" as a key funnel
"Looks like you're trying to login" email
Android Smartlock, iCloud keychain
1-click sign-in for app constellations (EATS/Uber)
Active users engaging inactive users
Cross-sell login when a user's signing up with an
existing email/username
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Cohort Retention
Loops versus Linear
Don't want one-time spikes in retention
What value is created on each visit?
Are the loops improving over time?
Actions, not just sessions
Not just a session!
D1/D7/D30 and month-to-month
Segment by acq source, geo, etc
What I'm looking for:
Active/Reg flattens out to >20%
TAM * 2y cohort * ARPU
Inactives aren't viral! Key to acquisition too
Notifications analysis
List of notifications
Volume and how they're triggered
Company initiated versus UGC
CTR decay over time
Quick spam check - "[company] spam" on Twitter,
Google, Reddit
Notifications are key to many engagement loops
Notifications as accelerant, not foundational
High organic versus notification-triggered visits
Stable CTRs >25%
Platform dynamics
Upside in adding more personalized channels
Frequency and Loops
Frequency segmentation
Channel and Time period
DAU/MAU
Multiple engagement loops
Users often come for one, stay for another
High frequency, strong loops are social
versus lower-frequency utility
"Come for the tool, stay for the network"
What I'm looking for:
Frequency that matches value prop
Actions/Use cases for HFU vs LFU
Key attributes (Geo, age, etc.)
Upside opportunity to upsell/cross-sell to
move metrics
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Baseline Forecast
Prior work on Acquisition loops plugs in!
Acquisition <> Engagement <> MAU
Acquisition drives cohort Day 0
Activated users, not signups!
Use MAU / Activated
Forecast MAUs
MAU based on retention curves
2y Signups * Activated/Signups * % Retained
No credit for notif-driven spikes :)
Bottoms Up Roadmap
Retention curves are hard to move!
Never seen a leaky product fix itself by
adding more notifications :)
Biggest levers
Activating new users to engage
Adjusting mix of High Freq vs Med Freq
Usage intensity - Actions/MAU
Adjust cohort curves to reflect potential
improvements
+New
+Reactivated
-Inactive
Engaged
Acquisition
Loop
Engagement
Loop
Now we understand both loops - these are the inputs...
which means we understand and trust the outputs
We can have a granular, data-driven analysis of risks...
Quality?
Risks?
Upside?
+ New
+ Reactivation
- Inactivity
Engagement
and answer the questions that matter!
Is it working?
Will it sustain?
Can it improve?
Thanks for reading this - I originally published this deck with the note below on my blog - you can read the details here:
https://andrewchen.co/investor-metrics-deck/
Hope you enjoy :)
Andrew
San Francisco, CA
--
Earlier this year, I joined Andreessen Horowitz as a General Partner, where I focus on a broad spectrum of consumer startups: marketplaces, entertainment/media, and social platforms. This
was a big moment for me, and the result of a long relationship that began a decade ago, when Horowitz Andreessen Angel Fund funded a (now defunct) startup I had co-founded. One of the
reasons I've been excited about being a professional investor is the ability to apply my skills as an operator. The same skills needed to grow new products can be used both to evaluate new
startups to invest in, and once we've invested; to help them grow.
The reason for this is that the steps for starting and scaling a new startup share many of the same skills as investing in a new startup: 1) First, we seek to understand the existing state of
customer growth including growth loops, the quality of acquisition, engagement, churn, and monetization. 2) Then, to identify potential upside based learnings from within the company as
well as across benchmarks from across industry. 3) And finally, to prioritize and make decisions that impact the future. Of course, as an investor you can't run A/B tests or analyze results
directly, but you can form hypotheses, ideate, and apply the same type of thinking.
As part of my interview process at a16z, I eventually put together an 80 slide deck on how to use growth ideas to evaluate startups. In the spirit that this perspective can help others in the
ecosystem, and to share my my thinking, I'm excited to publish the deck below.
Disclaimer: This was just one presentation in a 10 year relationship
But before I fully share, I have a disclaimer. This is one presentation I made within a series of dozens of meetings and interactions I had with the Andreessen Horowitz team. It was just one
ingredient. I've been asked by friends and folks on the best path into venture capital. From my experience, it's a long, windy experience others have written about their processes as well.
My journey took a while too:
10 years in the Bay Area (and blogging, building my network, etc)
Dozens of angel investments and advisory roles in SaaS, marketplaces, etc
Once kicked off, 6 months of interviews (dinners, sitting in pitches, analyzing startups)
100+ hours of interviewing and prep
This deck was just one step, but one that I'm proud of, and want to show y'all.
Growth Hacking for
Startups / Venture Capital
Andrew Chen
Prepared for Andreessen Horowitz
"growth hacking"
0 results
"Growth Hacker is the new VP Marketing"
Published April 2012
Years later, the Growth function has
taken off across the industry...
Growth has evolved:
Facebook app growth
Email address book virality
Hacks, tips, and tricks
into a much bigger umbrella
"growth team"
"new user experience"
"user engagement metrics"
"customer acquisition cost"
660+ essays over 10 years
Selection of work
How To (Actually) Calculate CAC
What does a growth team work on?
What's your viral loop?
When and why do apps "jump the shark?"
Losing 80% of mobile users is normal
60% of users opt-out of push notifications
What factors drive DAU/MAU?
Audience
100k email/RSS subscribers
110k Twitter followers
Front page of YC Hacker News
Front page of Google:
growth hacking
product market fit
user growth
growth team
customer acquisition cost
user engagement metrics
viral loops
viral coefficient
push notification click through rate
...
Next step: Pulling together the
top-end of the professional network
Week 1
Growth Models
Week 2
Channels and Loops
Week 3
Growth Roadmap
Week 4
Engagement and Retention
Week 5
Viral Growth
Week 6
Paid Marketing
Week 7
Growth Teams
Week 8
Future of Growth
Growth professional education: 8-Week Agenda
1500+ mid-career professionals from across tech
Personal goals for the future:
Stay ahead of the curve
Bring people and networks together
Put more ideas on paper :)
Let's use frameworks
to assess startup growth!
Growth Frameworks + Startups
Questions
Is it working?
Will it sustain?
Can it improve?
+ New+Reactivated
5,000
-
Inactive
1,000
= Net MAU
4,000
+ Engaged
10,000
= MAU
14,000
The Growth Accounting Framework
New+Reactivated
Tends to look linear or S curve
Only a few loops scale:
Virality, Paid, SEO
Most lack a strong reactivation
strategy
Inactive
Also an S-curve, but lags MAUs
% of Active Users
Sometimes hard churn, usually
lack of frequent use case
Very hard to move this curve!
New + Reactivated - Inactive = 0
Peak MAUs
Problem: Growth Accounting gives lagging metrics
It's just the current snapshot!
You wouldn't invest based on a startup's P&L, Balance Sheet, etc.
Same with Growth Accounting - it talks outputs but not inputs
Not actionable for product teams
+New
+Reactivated
-Inactive
Engaged
Acquisition
Loop
Engagement
Loop
Leading indicators, not lagging
Start with the product's Acquisition and Engagement Loops
How defensible/proprietary?
How scalable and repeatable?
How much upside?
We need to understand the quality of growth
Use Loops to drive the discussion, not Growth Accounting
User Acquisition Loop
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Acquisition Loop
How does a cohort of new users lead to more new users?
Durable, scalable sources of new users are built on loops
Loops are built on existing platforms and networks
(Buy / Build / Partner)
Acquisition Loop: User generated content + SEO
New users find
content
% signup and
create content
indexes
unique content
People search
for content
Acquisition Loop: Paid marketing
New users
click an ad
% sign up to try
product
% convert to
paid features
Budget used to
buy ads
Acquisition Loop: Viral
New users
sign up
Invites /
content sent to
friends
Some % click
on the links
Engage with
invite/content
Measuring loops - and why there's a multiplier
New users
sign up
% import their
contacts
Invites links
sent
Some % click
on the links
30%
10X
40%
50%
Growth Factor = 0.6
1000 signups create +666 more
Other loops are the same:
Spend $5 CAC
Get $10 in profit
Write 1 wiki page
Get 1.5 pages written
Etc
Linear channels are helpful, but don't scale
New users click
an ad
% sign up to try
product
% convert to
paid features
Budget used to
buy ads
PR
Conferences
Content mkting
Partnerships
App Store
features
(Aren't repeatable, don't scale!)
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Example: App Ratings
>50% dropoff at the App Store detail page
#deleteuber
1.7 stars :(
iOS 10.3
Inline app review
modal rolled out
4.7 app rating
(4.4 overall)
*Public App Store data from Appbot
New iOS 10.3 inline review modal
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Example: Mobile Phone # Verification
10-40% dropoff at mobile phone # verification step
Optimizations:
Voice OTP
Android auto-read SMS code
Carrier direct verification (Danal)
Partner<>Carrier deliverability tracking
Paid Marketing Loop - in more detail
New users
click an ad
% sign up
on landing
screen
Budget
used to buy
ads
% who
install from
App Store
page
% who
mobile
verify
% who see
an item
detail page
% who add
item to cart
% who
checkout
% who add
payment
% who
complete
purchase
Example: Landing Page Optimization
80%+ dropoff on landing pages
A/B testable best practices:
Minimal design with strong CTA
Remove unnecessary form fields
Personalized (to add, inviter, etc.)
Rich media, but no links! (carousel, GIF, video)
Mobile optimized web
Redirect to App Store when mobile
Smart app banner META tag
...
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Loops/Channels Mix
Signups broken down by:
Channels and Loops
Time period
Quality indicators
Proprietary channels and loops
Repeatable/scalable loops
Low platform risk
33/33/33 on organic plus two loops
Red flags
New, unsustainable traffic
Spiky acquisition - ads?
Brittle dependence on one loop
Loops that are actually linear channels
Dec
Jan
Feb
Mar
Apr
brand / Google
1,000
non-brand / Google
10,000
10,000
seo / Google
10,000
10,500
11,025
11,576
12,155
homepage / Organic
2,000
2,100
2,200
2,300
2,400
product hunt / Partner
25,000
2,000
1,000
500
Acquisition Loop Quality
Sources broken down:
Signups, Cost per Signup
Activated, Activation %, CPAU
LTV
MoM increase %
Quality indicators
Steady growth on scalable loops
$ spent on quality signups
Steady growth with high activation
Red flags
Spikes of $ on low quality signups
Signups without activation
CPAU > CPSU > LTV
Source
Signups CPSU Activated CPAU Activation % LTV MoM
brand /
non-brand /
display /
feed /
homepage /
organic
detail page /
organic
seo / google
Platform Dependency
Growth <> Platforms
Loops depend on existing platforms
Build/Buy/Partner
Look at CTR and conversion rates
on-platform over time
Indicators
Stable performance
Durable real estate
Proprietary Product<>Channel fit
$1B versus $10B co - multiple loops
Red flags
Decreasing conversion rates
Easily fast followed
Unstable or shrinking platform
Examples of
Acquisition Loops
Acquisition Loop
Metrics
Acquisition Loop
Improvements
Applying the
Frameworks
Applying our acquisition framework
Baseline forecast
Linear and non-linear
Flat on linear channels
Nonlinear projection for loops
Project out to the next financing
MAU and Activated, not just signups!
Dec
Jan
Feb
Mar
Apr
brand / Google
1,000
non-brand / Google
10,000
10,000
seo / Google
10,000
10,500
11,025
11,576
12,155
homepage / Organic
2,000
2,100
2,200
2,300
2,400
product hunt / Partner
25,000
2,000
1,000
500
Bottoms Up Roadmap
Factor in improvements
Bottoms-up roadmap to next
funding round
+5%-10% for minor upgrades
+25-50% for new loops
Share this with the entrepreneurs
afterwards!
Iterate the forecast
Rebuild forecast + risk analysis
Build into Net MAU model
Need Engagement Loop too...
Qualitative risks
Platform + competitive risks
What if a loop goes to zero?
Can this team execute?
but Acquisition's only half the picture!
Let's talk about the Engagement loop
User Engagement Loop
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Engagement Loop
For social apps:
How does one engaged user cause another to be more engaged?
For utility apps:
How does engagement in an app cause future engagement?
Prefer organic, natural use cases over notifications, which should
just be an accelerant
Engagement Loop: Social feedback
User creates
content
Content viewed
by other users
Social
feedback given
on content
Notification
sent to content
creator
Engagement Loop: Personalized content
Users
subscribe / add
New content
comes up
Users are
alerted by
notification or
feed
Users view and
like content
Linear channels for engagement
User creates
content
Content viewed
by other users
Social
feedback given
on content
Notification
sent to content
creator
PR
Promotions
Holiday
New features
...
(Aren't repeatable, don't scale!)
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Kicking off the engagement loop
Activation bends the cohort curve early
Examples from Pinterest's growth team:
"Save" instead of "Pin It"
Interstitial from Mobile web to app
Pin Education
Simplifying Home Feed
+100% lift to activation
(Weekly repinners / Signups)
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Building social graphs
Social feedback loops are dependent on a network
Bootstrap on a pre-existing graph:
"Find friends"
30% will sign in via FB/Google
95% connection rate by layering value props
Other proven tactics:
Reverse addressbook lookup
"Your friend X just joined - add them?"
People You May Know
Post-content creation sharing prompt
After a connection, cross-sell to adding more - build a loop
Red flags
Viral factor > 1 based on spam
Select all on contacts, SMS spam, No skip buttons
Engagement that's all connecting, no core actions
Social Feedback Loop - in more detail
Notif
opened and
CTR
User
creates
content
Notif sent to
content
creator
User views
notif
User hits
publish
# of
connections
Notifs sent
with new
content
Notif
opened and
clicked
through
Recipient
logs into
website
Recipient
gives
feedback
on content
Inactive users trying to engage
Reactivating users is a huge non-obvious opportunity
for late stage startups
~50-75% of registered users are inactive
They face challenges with trying to engage:
Need to reinstall app
Forgot their username or password
Using a new phone #
Solutions
Treat "Forgot password" as a key funnel
"Looks like you're trying to login" email
Android Smartlock, iCloud keychain
1-click sign-in for app constellations (EATS/Uber)
Active users engaging inactive users
Cross-sell login when a user's signing up with an
existing email/username
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Cohort Retention
Loops versus Linear
Don't want one-time spikes in retention
What value is created on each visit?
Are the loops improving over time?
Actions, not just sessions
Not just a session!
D1/D7/D30 and month-to-month
Segment by acq source, geo, etc
What I'm looking for:
Active/Reg flattens out to >20%
TAM * 2y cohort * ARPU
Inactives aren't viral! Key to acquisition too
Notifications analysis
List of notifications
Volume and how they're triggered
Company initiated versus UGC
CTR decay over time
Quick spam check - "[company] spam" on Twitter,
Google, Reddit
Notifications are key to many engagement loops
Notifications as accelerant, not foundational
High organic versus notification-triggered visits
Stable CTRs >25%
Platform dynamics
Upside in adding more personalized channels
Frequency and Loops
Frequency segmentation
Channel and Time period
DAU/MAU
Multiple engagement loops
Users often come for one, stay for another
High frequency, strong loops are social
versus lower-frequency utility
"Come for the tool, stay for the network"
What I'm looking for:
Frequency that matches value prop
Actions/Use cases for HFU vs LFU
Key attributes (Geo, age, etc.)
Upside opportunity to upsell/cross-sell to
move metrics
Examples of
Engagement Loops
Engagement Loop
Metrics
Engagement Loop
Improvements
Applying the
Frameworks
Baseline Forecast
Prior work on Acquisition loops plugs in!
Acquisition <> Engagement <> MAU
Acquisition drives cohort Day 0
Activated users, not signups!
Use MAU / Activated
Forecast MAUs
MAU based on retention curves
2y Signups * Activated/Signups * % Retained
No credit for notif-driven spikes :)
Bottoms Up Roadmap
Retention curves are hard to move!
Never seen a leaky product fix itself by
adding more notifications :)
Biggest levers
Activating new users to engage
Adjusting mix of High Freq vs Med Freq
Usage intensity - Actions/MAU
Adjust cohort curves to reflect potential
improvements
+New
+Reactivated
-Inactive
Engaged
Acquisition
Loop
Engagement
Loop
Now we understand both loops - these are the inputs...
which means we understand and trust the outputs
We can have a granular, data-driven analysis of risks...
Quality?
Risks?
Upside?
+ New
+ Reactivation
- Inactivity
Engagement
and answer the questions that matter!
Is it working?
Will it sustain?
Can it improve?