The Digital Transformation Playbook: Rethink Your Business for the Digital Age

Insights: Revealing the Invisible
The first template for value creation is insights. By revealing previously 
invisible relationships, patterns, and influences, customer data can provide 
immense value to businesses. Data can provide insights into customer psy-
chology (How are my brands or products perceived in the marketplace? 
What motivates and influences customer decisions? Can I predict and 
measure customer word of mouth?). Data can reveal patterns in customer 
behavior (How are buying habits shifting? How are customers using my 
product? Where is fraud or abuse taking place?). Data can also be used 
to measure the impact of specific actions on customers’ psychology and 
behavior (What is the result of my change in messaging, marketing spend-
ing, product mix, or distribution channels?).
Today, many businesses have access to large quantities of customer 
data in the form of online conversations about their products and brands. 
A good example is automobile manufacturers. My colleague Oded Netzer 
of Columbia Business School, along with three research coauthors,
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has 
dug into the data created by discussion forums to explore what it reveals 
about the automotive market structure and consumer behavior. Netzer’s 
team applied a variety of text-mining tools—algorithms that are trained on 
human language and apply formulas to detect patterns in huge quantities 
of unstructured text from online conversations. One area of their research 
looked at how customers perceive brands. By examining patterns of statisti-
cal “lift,” they could identify which specific attributes are more frequently 

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associated with one auto brand versus its closest competitors. The patterns 
revealed opportunities in terms of audiences to target, content for messag-
ing, and ideas for product development.
Netzer’s team also used the data to investigate the impact of long-term 
advertising efforts. They focused on a period when Cadillac had spent 
millions on brand advertising to shift customers’ perception of Cadillac 
from “classic American car” (like Lincoln) to “luxury brand” (like Lexus 
and Mercedes). A textual analysis of the conversations over several years 
showed that, consistent with the campaign objective, the Cadillac brand 
was gradually moving—in customers’ associative perceptions—from the 
first group (classic American brands) to the second (luxury brands). When 
the researchers compared this with public data on dealer trade-ins, they 
confirmed that the shift in perception was also a leading indicator of pur-
chase behaviors. Rather than trading between Lincolns and Cadillacs, more 
and more customers were exchanging their luxury cars for Cadillacs.
In another case, Gaylord Hotels used insights from customer data to 
sharpen its referral strategy. The business has a few large hotel properties 
that are well suited for major events as well as personal stays. With a limited 
advertising budget, it knew that referrals (word of mouth from happy guests) 
were the biggest source of new customers. So management set a priority to 
increase that word of mouth by improving the already good guest experi-
ence. The first step was an internal review of operations that identified eighty 
areas of focus that might help inspire customers not only to be pleased but 
also to actually mention Gaylord to others. The obvious next challenge was 
prioritization: Which items on this long list were most important? To help, 
the company undertook an analysis of social media data, looking at every 
instance where the hotel’s name was mentioned by customers in public plat-
forms like Twitter. Customer recommendations and praise were examined 
for any clues as to what had spurred them and at what point in the custom-
er’s stay. The results were illuminating. A short list of just five elements of the 
guest experience seemed to have the greatest influence in sparking word of 
mouth, and all of them took place in the first twenty minutes after arrival.
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