2020
Killing The Focus
Group: The Disruption
Of Market Research
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3
Killing The Focus Group: The Disruption Of Market Research
Table of Contents
What is market research?
The impact of technology on market research across
the product lifecycle
• Development: Early-stage market research is
becoming more efficient
• Launch: Faster and cheaper consumer feedback
• Growth: New ways to crunch data will boost
performance tracking
The future of market research
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Killing The Focus Group: The Disruption Of Market Research
Understanding what people think and how they’ll behave is difficult
— just look at the ongoing challenges faced by election pollsters.
But as shopping activity increasingly moves online, market
research — which refers to the ways a company identifies and
analyzes consumer needs — is being reimagined by tapping into
new datasets of consumer behavior that are vast, high-quality, and
updated in real time.
Adding to this, emerging technologies like artificial intelligence (AI),
chatbots, and virtual reality are disrupting antiquated data collection
processes like in-person focus groups and telephone interviews.
In this report, we look at what market research does, how it’s
changing amid massive technology breakthroughs, and what the
future of the industry holds.
Market research is changing as emerging
tech enables new ways to gather and
analyze consumer data. We dig into the
industry’s transformation and look at what
comes next.
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Killing The Focus Group: The Disruption Of Market Research
Companies look to market research to understand the preferences
and needs of their customers.
These efforts can include identifying a target market for new
products or services, understanding the efficacy of a company’s
current brand campaigns, and keeping track of rivals and the price
of competing products.
Over the years, researchers have identified various ways to capture
quantitative data for market research. The earliest instances of
market research can be traced back to the 1920s, when a group
of researchers, led by psychologist Daniel Starch, approached
people in the street to understand the effectiveness of an ad being
displayed in a print publication. They asked people to recall if they
had seen certain ads in magazines and newspapers, and then
compared the recall value with the publication’s circulation. This
came to be known as the Starch Test.
In the 1930s, George Gallup created a polling technique — still
widely used today — to judge the attitudes of a large population
from a small sample.
After collecting quantitative data on their customers, market
researchers turned their focus onto qualitative research in the
1940s. This helped researchers get an insight into why and how
people were making purchases. Researchers did this by collecting
data through in-person interviews, as well as focus groups and
research panels.
What is market research?
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Killing The Focus Group: The Disruption Of Market Research
The next major wave of change in market research methodologies
came with the internet. A milestone in marketing research was
the development in 1995 of Analog, software that allowed website
owners to track their usage patterns. The software gave market
researchers access to data on how users were engaging with a
website, product, or service. Analog is considered to be a
precursor to Google Analytics, a current market leader among
analytics software.




A sample report created by Analog. Source: Web Archive


The internet changed the manual process of conducting market
research. In-person and telephone interviews were replaced with
online surveys, while online data aggregation took the place of
focus groups and research panels.
Then came the smartphone — another game-changer for market
research. With these communication devices now in the hands of
almost half of the world’s population, it has become that much
easier for market researchers to get data on customers.
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Killing The Focus Group: The Disruption Of Market Research


Source: B2B International
In the past, market research datasets tended to be small, low-
quality, and manually created based on information from surveying
subsets of customers. Now, researchers are shifting from this
often inefficient approach to analyzing consumer behavior
passively by tapping into massive, constantly updating datasets
generated directly from consumer behavior. Netflix, for instance,
is able to capture the viewing habits of all its users and adapt to
changes as they happen.
These deep wells of customer data — much of it garnered
automatically from sources like purchase history, sentiment
analysis, and social media mining — can provide a more holistic
picture of a customer’s preferences.
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Killing The Focus Group: The Disruption Of Market Research
The goal of market research hasn’t changed much since Starch
first went out to discover the effectiveness of print advertisements.
Researchers still want to know what consumers think.
Market research has been integrated into every step of a product’s
lifecycle, which encompasses 3 broad stages: development,
launch, and growth.
At the development stage, companies are looking to bring a new
product or service to market, and are considering how best to
sell it. Here, market researchers identify potential customers and
distribution channels. Additionally, researchers analyze customer
trends and create models to forecast usage of a product or service
by the target audience.
Once companies have identified their target market, they want to
launch a product and measure how intended consumers react to
it. Market researchers help with collecting and analyzing feedback
from pilot schemes and initial customers.
Market research also plays a role in supporting the growth of a
product. After the launch of a product or service, researchers may
help companies keep track of competing products, tweak offerings
to align with shifting consumer trends, and assess how advertising
campaigns are performing.
Below, we look at how technology is disrupting market research at
each stage of the product lifecycle.
The impact of technology on market
research across the product lifecycle
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Killing The Focus Group: The Disruption Of Market Research
DEVELOPMENT: EARLY-STAGE MARKET RESEARCH IS
BECOMING MORE EFFICIENT
AI applications like natural language processing (NLP) — software
for automatically understanding the context of words — and
machine learning are helping to reduce the human effort expended
on early-stage market research. Additionally, these advances are
making forecasting models more accurate and delivering better
shortlists for research candidates.
Voice assistants are changing how shortlists are used
During the development stage of market research, a researcher
is still identifying potential customers and the composition of
the target market. One part of identifying potential customers is
creating a shortlist.
Automation tools are reducing the effort it takes to create a
shortlist. Where once market researchers had to manually
create shortlists of potential customers, AI algorithms are being
developed to parse through databases larger than a human could
manage and at a faster rate.
Armed with a shortlist, market researchers are also employing
NLP-enabled voice assistants — with similar interfaces to Siri or
Alexa — to conduct surveys instead of using paper-based or digital
forms. NLP helps these digital voice assistants “understand”
human responses in those surveys and allows them to follow up
with relevant questions.
This approach is quickly gaining traction. Research from Qualtrics,
a US-based experience management company, suggests that a
fourth of all surveys will be conducted through digital assistants
within the next 5 years.
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Killing The Focus Group: The Disruption Of Market Research
Automation tech is helping researchers parse unstructured data to
create consumer profiles
AI applications like machine learning have also allowed
researchers to tap into massive amounts of semi-structured and
unstructured data coming from sources like emails, social media,
and photos. For example, algorithms are being designed to pick
up on words and phrases relevant to a marketer’s research while
parsing through a customer’s public online presence — like the
pictures and comments they leave on websites they visit.
MonkeyLearn, an AI-powered text analysis platform, claims that its
data analytics tool can parse unstructured data such as emails or
customer service tickets 1200x faster than a human.



Source: MonkeyLearn

Researchers can create predictive models for building customer
profiles by combining this unstructured data — which accounts for
an estimated 90% of all data generated — with structured data, like
purchase history.
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Killing The Focus Group: The Disruption Of Market Research
Appier, a Taiwan-based data and AI company, says that it helped
CommonWealth, an economics-focused magazine, increase
its subscriptions and purchases by 404% after leveraging
unstructured data for predictive modeling. Appier first predicted
consumers likely to subscribe to CommonWealth and then
scoped for other users based on specific patterns picked from its
predictive model.
Sentiment analysis is allowing researchers to gather more
authentic customer feedback
Beyond profiling customers, market research is also concerned
with understanding how they behave when shopping or using
a service.
Sentiment analysis, which seeks to understand someone’s
emotional response to something, is one way that market
researchers are now looking to analyze customer behavior.
For example, eye-gaze tracking tech, like that offered by Karna AI’s
SmartGaze, uses cameras to measure the effectiveness of in-
store campaigns and packaging design, as well as a consumer’s
reception to a brand. The company claims that its software takes
85% less time to produce insights than if humans were tracking
these eye movements — while costing 40% less.
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Killing The Focus Group: The Disruption Of Market Research
Source: Karna AI
Travel booking website Expedia has deployed similar sentiment
analysis technology to track a consumer’s emotions while using
its website. At its Usability Lab in Washington, the company brings
in customers and then records biometric information through eye
trackers and face sensors while they make a booking.
Natural language generation is being used to create research
reports
Producing literature on how competitors or a product are operating
in the industry is an essential part of market research. Aiming to
increase efficiency, some in the space are beginning to use natural
language generation (NLG), an application of AI for representing
data as easy-to-understand text, to generate business insights.
For example, NLG platform Wordsmith generates business
intelligence reports like marketing analysis and narratives from
basic input data. Currently, these types of reports are mostly
limited to a few paragraphs, but the potential is likely to increase
in the near future.
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Killing The Focus Group: The Disruption Of Market Research
Brand image tracking is being automated
Another function of market research is tracking how a brand is
being represented in the media and on social media. However, it’s
a time-consuming effort to manually track brand mentions across
the web while also disregarding irrelevant keyword mentions. New
services aim to speed this process up.
For example, Talkwalker claims it can quickly help brands filter out
irrelevant data — like differentiating between mentions of Apple
(the company) and apple (the fruit). The AI company also says that
its technology can detect visual mentions of a brand and conduct
sentiment analysis to understand the context in which a brand is
being mentioned.
Meanwhile, platforms like Mentionlytics work on “social listening”
to help brands manage their reputation. Companies offering this
service aim to analyze data like a brand’s social media mentions,
customer reviews, and customers’ questions.

Source: Mentionlytics
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Killing The Focus Group: The Disruption Of Market Research
LAUNCH: FASTER AND CHEAPER CONSUMER FEEDBACK
The next step in market research after gathering data on potential
customers and preferences is to test a company’s products
or services in the run-up to and during launch. Tech is making
this easier.
AR and VR reduce piloting costs in some cases
Market researchers tend to test a product or service among a
smaller group of customers before a company launches it to the
entire market. Augmented reality and virtual reality (AR/VR) are
making this research faster and easier — though associated costs
currently limit use cases.
For example, if a company wants customer feedback on a new
store layout, it would traditionally survey customers to see if
they like the proposed changes. Or it may arrange a section of an
existing store according to the new layout and record customers’
feedback to it. This process can be time-consuming and costly.
But by using VR, the company can bring in a group of customers
and let them experience the new layout by strapping on VR
headsets. This is a more reliable and authentic way of recording
respondents’ reactions compared with asking them to recall their
last visit to a similar store or to imagine how they would feel if they
were in such a store.
UK-based System 1 Research conducted an experiment for
various brands to test out a customer’s shopping choices with
respect to variables like shelf displays, pricing, and packaging.
Tesco, one of the UK’s largest grocery store chains, employed a
similar technique by creating a virtual shopping experience to
gauge customer feedback before deciding how best to build a
new store.0.
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Killing The Focus Group: The Disruption Of Market Research
Screenshot from System 1 Research’s VR shopping tool. Source: Martech Today
AI is enabling new forms of sentiment analysis and observational
research
Market researchers are applying AI-powered tools to observational
research, which looks at how a customer actually uses a product.
For example, Karna AI’s Perceptron parses through videos of
users interacting with a product and generates insights based on
nuanced details that would be challenging for humans to notice. In
an experiment to understand which beard trimmer worked best for
a user, the data Perceptron collected included total time spent on
trimming, the beard density in each part of the face, and the facial
expressions of the user while operating the trimmers.
Source: Karna AI
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Killing The Focus Group: The Disruption Of Market Research
Tracking real-time usage data is helping researchers collect better
customer feedback
Analyzing the usage of a product or service can help market
researchers gain insights into consumer behavior on a
continuous basis.
San Francisco-based InterQ says that “capturing a customer’s
feedback in the moment yields the most honest data.” For
example, if a company wants to see how a consumer interacts
with its mobile app, tracking real-time usage data will likely offer
more authentic results compared to asking a consumer to recall an
experience in a survey.
This is another area where unstructured data can help marketers
gauge a customer’s reaction to a product or service.
Take retail stores as an example. Stores have CCTV footage
for security purposes, but this is also being used to capture
customers’ reactions to changes in store layout and different
products. In addition, retailers are using this approach to help
understand customer flow in relation to weather, the time of day, or
during cultural or sporting events.
Some are taking this approach even further. Microsoft-backed
startup Cooler Screens, for example, offers fridges that detect
shopper movement, serve up ads, and monitor inventory to
measure sales results.
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Killing The Focus Group: The Disruption Of Market Research
GROWTH: NEW WAYS TO CRUNCH DATA WILL BOOST
PERFORMANCE TRACKING
Once a product or service is launched, market researchers track
how it is performing in relation to competitors’ products in the
market. This is done through brand tracking and comparing
product performance.
Businesses are automatically tracking competitors to dynamically
adjust prices
Companies often adjust their prices to stay competitive with rivals,
but this process can be time- and effort-intensive. However, some
companies are offering tools that aim to automate this legwork.
Turkey-based Prisync, for example, is a subscription-based
service that helps e-commerce businesses track pricing. The
company’s tool scrapes selected URLs and lets businesses check
a competitor’s price, know when a competitor’s product goes out
of stock, and adjust product prices.
Advertising is being revamped by AI-supported techniques
Market researchers keep track of how the advertising for a
company’s product is performing among its target audience. For
example, AI company Affectiva relied on sentiment analysis to
track the effectiveness of an ad campaign by Mars. The company
used participants’ webcams to track their facial and emotional
responses while they viewed Mars ads — data that was used to
inform sales predictions.
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Killing The Focus Group: The Disruption Of Market Research
Companies also use natural language processing to identify
celebrities and social media influencers who may be suited to
promote products. For its Super Bowl campaign in 2016, carmaker
Kia used IBM’s AI software Watson to identify influencers to be
part of its campaign. Watson analyzed the language that social
media influencers used on their profiles to identify those who
demonstrated characteristics that Kia wanted to be associated
with its brand — in this case, “openness to change,” “artistic
interest,” and “achievement-striving.”
Direct-to-consumer models are changing data collection
Direct-to-consumer (D2C) brands have become increasingly
popular over the last decade. Companies like Casper, Allbirds, and
Everlane have pioneered new ways to reach customers, and this
approach has allowed brands to build an even closer relationship
with customers — and their data.
Incumbent companies, especially those in consumer packaged
goods (CPG), are now also launching D2C stores. Pepsi, for
instance, started selling its branded products on its own D2C
platforms in May 2020, while brewery group AB InBev is piloting an
online store in Europe.
While these moves are partly a response to the surge in online
shopping that accompanied the pandemic, they mainly represent a
way for these companies to gather better data on their customers
and experiment with new products.
This D2C approach could prove to be much faster in comparison to
waiting to measure the performance of new products across retail
partners, helping brands to be nimbler as they adapt to emerging
consumer trends.
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Killing The Focus Group: The Disruption Of Market Research
Chatbots are helping to gather more consumer data
A new wave of chatbots is helping market researchers engage
users and collect information more effectively than alternatives.
A survey conducted by CONVRG found that up to 80% of chatbot
users answered questions, including open-ended ones — 3x higher
than the responses received through email surveys.
Questions that a business may ask through chatbots range from
the problems a customer is trying to solve to their location. This
is all useful data for a company to understand how customers are
responding to its products and services.
For example, data insights company Kantar uses NLP to conduct
market research through conversational chatbots on platforms
like WhatsApp and Facebook, as well as through voice assistants.
Meanwhile, Sweden-based furniture company IKEA is using a
chatbot called ORC to collect feedback from customers.

Source: Smart Insights
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Killing The Focus Group: The Disruption Of Market Research
Market research will keep evolving as emerging technology
enables new ways to collect consumer data.
As people’s attention spans continue getting shorter, micro-
surveys that are conducted through messages and chatbots are
likely to take precedence over approaches like emailed surveys.
The demand for gathering data from video will also become
increasingly important, given that over 82% of consumer internet
traffic is expected to be in video form by 2022, a 15x increase
compared to 2017, according to Cisco. Additionally, market
researchers could soon rely heavily on voice-enabled devices and
virtual assistants to conduct research.
Despite the promise of efficiency and new insights from these tech
applications, challenges loom on the horizon.
As improving AI tech enables market researchers to crunch more
data, they will also need to reckon with identifying biases in their
data and taking steps to ensure that automated approaches to
analysis hold up against the real world. Additionally, growing
moves from regulators around the world to give consumers
more control over their data — through privacy protection rules
like Europe’s GDPR — may prove to be a hurdle for the market
research industry.
But what could threaten incumbents even more is that these
new tech-driven approaches to market research often require
completely new skillsets. This could make some of the industry’s
big players more vulnerable to tech-savvy startups, or cause a
boom in M&A as incumbents scramble to keep pace with emerging
tech and the talent needed to leverage it.
The future of market research
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Killing The Focus Group: The Disruption Of Market Research
Market research companies are experts in understanding others.
However, now more than ever, they will have to make sure that they
understand their own blind spots to avoid being left behind.
Clients can view 3500+ adtech startups in this Expert Collection.
Expert Intelligence clients can check out our report on targeted
marketing companies here.
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Killing The Focus Group: The Disruption Of Market Research
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Additional reading