What Is the Future of Data Sharing?

What Is the Future
of Data Sharing?
CONSUMER MINDSETS AND THE POWER OF BRANDS
Matthew Quint and David Rogers
October 2015

WHAT IS THE FUTURE OF DATA SHARING? © 2015
Page 2
Aimia is a data-driven marketing and loyalty analytics company. We
provide our clients with the customer insights they need to make
smarter business decisions and build relevant, rewarding, and long-
term one-to-one relationships, evolving the value exchange to the
mutual benefit of both our clients and consumers.
Aimia partners with groups of companies (coalitions) and individual
companies to help generate, collect, and analyze customer data and
build actionable insights.
We do this through our own coalition loyalty programs such as
Aeroplan in Canada and Nectar in the UK, and through provision of
loyalty strategy, program development, implementation, and
management services underpinned by leading products and
technology platforms such as the Aimia Loyalty Platform and Smart
Button, and through our analytics and insights business, including
Intelligent Shopper Solutions.
In other markets, we own stakes in loyalty programs such as Club
Premier in Mexico, Air Miles Middle East, and Think Big, a partnership
with Air Asia and Tune Group. Our clients are diverse, and we have
industry-leading expertise in the fast-moving consumer goods, retail,
financial services, and travel and airline industries globally to deliver
against their unique needs.
Columbia Business School’s Center on Global Brand Leadership
creates, gathers, and shares insights on how to build and manage
strong brands.
Combining the research and intellectual capital of academia's
foremost thinkers on branding with real-world business cases, we
show how all elements of an organization — from marketing and
communications to supply chain and operations — can affect brands
and their relationships with stakeholders.
The Center fosters a community of researchers, alumni, students,
and business leaders to advance new knowledge, promote
widespread learning, and serve as a forum to address the many
challenges of brand building, brand management, and strategic
marketing.
The Center on Global Brand Leadership was founded in 1999 at
Columbia Business School under the direction of Professor Bernd
Schmitt, a world authority on marketing and branding. The Center
has global partnerships with leading business schools — in China,
Germany, Korea, Spain, and Singapore — providing an unmatched
resource for researchers and practitioners.
Aimia has been a sponsor of the Center on Global Brand Leadership since 2012. Columbia Business School's Center on Global
Brand Leadership and Aimia collaborate to provide primary research and gather insights on consumer behavior.

Page 3
Table of Contents
Who and What We Studied
Findings
1. People Are Concerned about How Their Personal Data Is Handled
2. Consumers Are More Savvy than We Think
3. Brand Trust Does Influence Consumers to Share Data
4. Offers Have Impact and Should Be Used Strategically
5. Future Trends
Strategic Recommendations
Appendix: Authors, Acknowledgments, and Methodology

Page 5
Every day we face many moments where we choose whether or not to
share a piece of personal information with a company, from using a
credit card or cash to buy lunch, to allowing location services on an app
for easier directions, to browsing the web in private mode.
The massive gathering of consumers’ personal data has led the World
Economic Forum to research its potential as a new asset class.
Companies see great potential in mining this data to better understand
and reach both their existing and prospective customers, and consumers
have shown a desire to exchange data to receive more personalized
experiences from companies.
But at the same time, consumers are concerned that they are losing
control over their personal data. Consumers understand that sharing
data is a necessary part of doing business with many companies (e.g.
opening a bank account), but they are making decisions about what they
will share in exchange for getting back something of value.
To better understand these complex consumer decisions, the Center on
Global Brand Leadership at Columbia Business School, in conjunction
with Aimia, surveyed over 8,000 consumers in five countries — the US,
Canada, the UK, France, and India — to examine their attitudes towards
personal data sharing and privacy.
Understanding how and why
consumers are willing to share data
The goal of the research was to go beyond generalized attitudes and
examine:
• How consumers think about specific types of personal data (e.g.
sharing their name vs. their purchase history),
• How they share data with different industries (e.g. retail vs.
telecommunications companies), and
• How a trusted relationship with a brand might impact a person’s
decision to share data.
In addition, the research examined what kinds of benefits a company
might use to drive people to share their data. Alongside an appraisal of
traditional loyalty offers (e.g. discounts, rewards points, and exclusive
invitations), consumers were also asked to consider new kinds of value
that companies are beginning to offer—security, recommendation tools,
and even societal benefits. Together, these benefits revealed the
emerging opportunity for companies to create new value with consumer
data.

Page 6
Who we asked:
2,004
2,111
2,036
1,007
1,002
8,000+ survey
respondents
Across four generations:
Millennials: born 1984 to 2002
Generation X: born 1964 to 1983
Baby Boomers: born 1943 to 1963
Silent Generation: born 1925 until 1942

Page 7
What we asked about:
• General attitudes towards personal data and privacy
• How consumers think about specific types of personal data
• Opinions about privacy, comfort, and brand trust in six industries:
Financial services | Retail | Telecommunications | Airlines | E-commerce | Web services
• What influences consumers’ willingness to share data

Page 8
Highlights of what we found:
Consumers understand which data are most sensitive,
but they are willing to share it with companies in
exchange for a product or service they value.
• People rated their address, mobile phone number,
name, and date of birth as the four most sensitive
pieces of personal data.
• But more than 70% of consumers will consider
sharing that same data even when they are not
required to.
Brand trust positively impacts consumers’ willingness to
share data.
• Over 75% of people are more willing to share
various types of personal data with a brand they
trust.
Traditional offers and new, data-enabled benefits can
be used strategically to influence people to share
various types of data.
• 80% of consumers will share a non-required piece
of data for rewards points, and a majority will share
data for more experiential benefits like product
recommendations or a tool to help them with
complex decisions.

Page 9
Highlights of what we found
(continued):
There are four Data-Sharing Mindsets which can help
predict certain attitudes towards data sharing. These
mindsets demonstrate that some of the same
consumers who take action to protect their data are
still happy to share it for relevant offers and services.
To maximize the potential of using consumer data to
build meaningful relationships, it will be crucial for
businesses to deploy relevant offers for consumers, to
develop new types of value exchanges to benefit
individuals and society, and simultaneously help
individuals gain more control over their own data and
provide greater transparency on how it is used.
43% 24%
10%23%
DEFENDERS SAVVY AND IN CONTROL
HAPPY GO LUCKYRESIGNED
Data-Sharing Mindsets

C H A P T E R 1
People are concerned
about how their personal
data is handled

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People want more information and
control over their personal data
86% Want to exercise greater control over the data companies hold about them
85% Want to know more information about the data companies collect
75% Are worried sharing data makes them targets for marketing campaigns
80% Will only give data to a limited number of companies they trust
34% Have provided made-up personal details to avoid giving away personal data
59% Have taken steps to limit companies from tracking and advertising to them

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35%
31% 29% 27%
20% 21%
22%
15%
14%
12%
12% 9%
Financial services Telecom Retail Airlines Web services E-commerce
Somewhat comfortable Very comfortable
For most industries, few consumers are comfortable
with how companies handle their data
Q: For each of the following categories, how comfortable do you feel
about a company in that category handling your personal data?
57%
46%
43%
39%
32%
30%

Page 13
Except in India, most consumers are not comfortable
with how companies handle their data
45%
38% 35% 34%
65%
Percent very or somewhat
comfortable, averaged
across all six categories

Page 14
…and the differences in comfort among
countries also depend on the industry
Q. For each of the following categories, how comfortable do you feel about
a company in that category handling your personal data?
62%
49%
47%
42%
35%
33%
59%
39%
30%
35%
21% 21%
53%
43% 43%
37%
28%
24%
36% 37%
45%
29% 29%
34%
74%
68%
59%
61%
66%
58%
1 2 3 4 5 6
Series1 Series2 Series3 Series4 Series5US Canada UK France India
Financial services Telecom Airlines Web services E-commerceRetail
Percentages represent respondents that are very or somewhat comfortable

Page 15
Younger generations show greater comfort with
how companies handle their data…
Millennials Generation X Boomers Silent
Generation
44%
35% 35%
51%
Percentages very or
somewhat comfortable
averaged across all six
categories

Page 16
65%
52% 52% 51%
45%
42%
59%
48%
45%
43%
35% 35%
53%
41%
37%
32%
25%
23%
54%
43%
36%
31%
26%
19%
1 2 3 4 5 6
Series1 Series2 Series3 Series4
…and these generational differences in
comfort are consistent across industries
Q. For each of the following categories, how comfortable do you feel
Percentages represent respondents that are very or somewhat comfortable
Millennials Generation X Boomers Silent Generation
Financial services Telecom Airlines Web services E-commerceRetail

C H A P T E R 2
Consumers are more
savvy than we think

Page 18
We asked consumers about their willingness to share
specific data with different types of companies
• Respondents were asked to rank various pieces of data, from those they feel are most sensitive to least
sensitive.
• In addition, respondents were asked to report which pieces of data they felt required to share when
considering doing business in each of our six industries. Then they noted how they would consider sharing
non-required data points — willing to share, unlikely to share, would never share.
• The charts that follow show results in which all “required to share” responses have been removed, thus
allowing an examination of sharing attitudes towards data points people felt were optional to share when
considering purchasing a product or service.

Page 19
People are most sensitive about
personal identifying information…
Q. Please compare and rank the following types of personal data in terms of how sensitive you
believe them to be, from the most sensitive to the least sensitive
17%
17%
21%
23%
32%
42%
45%
46%
58%
Lifestyle info
Purchase history
Website history
Email
Social network access
Date of birth
Name
Mobile phone
Address
Percentages represent how often that data point was marked as one of the three most sensitive

Page 20
14%
19%
26%
30%
35%
45%
45%
65%
65%
38%
44%
44%
42%
38%
34%
35%
23%
24%
48%
37%
30%
28%
27%
21%
20%
12%
11%
Website history
Purchase history
Lifestyle info
Mobile phone
Date of birth
Address
Name
Email
Willing to share
Not likely to share
Would never share
… and yet personal identifying data is also what
people are most willing to share
Q. Please indicate how you would plan or expect to share the following types
of your personal data in order to purchase products/services?
NOTE: All ‘required
to share’ responses
were removed
Percentages averaged across all six industries

Page 21
People understand that
not all data are the same
• Consumers made distinctions between personal identifying information (PII) — including name, address,
mobile phone, data of birth, and email — as compared to other types of information.
• But consumers also clearly understand that sharing data, especially sensitive, personally-identifying
information can help businesses create value for them.

Page 22
Different industries use data
differently to create value for
consumers
• Financial services, airlines, and telecommunications firms are more likely to require that consumers
provide PII data to sign up for a service, and also routinely use this data to provide additional value.
For example, firms might use it to notify customers of fraudulent credit card activity or a delay in the
departure time of a flight.
• Retail, e-commerce, and web services, on the other hand, generate more willingness to share non-
PII data such as hobbies, lifestyle, and social information to provide more interesting product offers,
coupons, recommendations, or networked connections. In contrast, financial services, airlines, and
telecommunications companies are not historically good at using non-PII data for added value.

Page 23
Consumers consider the industry when they
choose to share different types of data
0%
10%
20%
30%
40%
50%
60%
70%
80%
Social network accessWebsite historyPurchase history Lifestyle info Hobbies Mobile phone Date of birth Address Name Email
Financial services
Airlines
Telecom
FIN/AIR/TEL AVERAGE
Web services
Retail
E-commerce
WEB/RTL/ECOM AVERAGE
Q. Please indicate how you would plan or expect to share the following
types of your personal data in order to purchase products/services?
FIN/AIR/TEL AVERAGE
Percentages represent respondents “willing to share”

Page 24
Consumers’ willingness to share
personal data varies by country…
48%
41%
38% 36%
33%
Percentage who
are willing to share
Q : Please indicate how you would plan or expect to share the following types
of your personal data in order to purchase products/services?”
Percentages represent respondents “willing to share” averaged across all data points

Page 25
…but these country differences
vary depending on the data type
Q. Please indicate how you would plan or expect to share the following types
71% 71%
50%
43%
40%
32%
27%
21%
15%
62%
64%
40%
36%
28%
25%
19%
13%
9%
67%
65%
46%
48%
37%
28%
24%
17%
12%
51%
57%
39%
55%
33%
27%
30%
20%
12%
71%
65%
46%
54%
46% 45% 45%
32%
27%
1 2 3 4 5 6 7 8 9
Series2 Series5 Series3 Series4 Series1
Percentages represent respondents “willing to share”
Canada UK France IndiaUS
Name Email Address Date of birth Mobile phone Lifestyle info Purchase history Website history Social network
access

Page 26
Generations only differ slightly in
their willingness to share data…
Generation
39%
35% 35%
43%
Percentage who
are willing to share
Q : Please indicate how you would plan or expect to share the following types
Percentages represent respondents “willing to share” averaged across all data points

Page 27
…but for some data types, the difference
between generations is more pronounced
Q. Please indicate how you would plan or expect to share the following
types of your personal data in order to purchase products/services?
68%
66%
42%
53%
42%
37%
32%
23%
20%
65%
67%
44% 45%
37%
30% 29%
21%
16%
63% 64%
46%
42%
32%
22% 22%
16%
10%
64%
62%
51%
53%
26%
21% 20%
14%
8%
1 2 3 4 5 6 7 8 9
Series1 Series2 Series3 Series4
Name Email Address Date of Birth Mobile Phone Lifestyle Info Purchase History Website History Social Network
Access
Percentages represent respondents “willing to share” averaged across all industries

C H A P T E R 3
Brand trust does influence
consumers to share data

Page 29
We asked consumers about
brands they trusted
• People were asked to note, within an industry, a brand with which they have had a trusted
relationship for at least 12 months.
• They were provided a list of leading brands and were asked to write in the name of their trusted
brand if it was not listed, or to note if there was no brand they trusted in that industry.
• In some industries, there was a well distributed mix of trusted brands, in others just one or two
brands dominated the category.

Page 30
Almost all people have at least one
brand they trust in each industry
Q. Select a company you have had a trusted relationship with for at least 12 months,
or add the name of a company you trust in this category at the end of the list.
89% 87%
84% 82%
71%
58%
Financial services Telecom Retail E-commerce Web services Airlines
I have a trusted brand in this category

Page 31
Chase Bank of America Wells Fargo13% 12% 10%
Top trusted financial services
brands (in five countries)
RBC Royal Bank TD Canada Trust Desjardins17% 16% 11%
Lloyds Bank Barclays NatWest and HSBC12% 11% 9%
Crédit Agricole La Banque Postale Caisse D’Epargne15% 14% 13%
State Bank of India ICICI Bank HDFC Bank32% 19% 14%

Page 32
Southwest Delta United and American
Airlines
17% 12% 7%
Top trusted airline brands
(in five countries)
Air Canada WestJet Air Transat27% 21% 6%
British Airways easyJet RyanAir18% 8% 5%
Air France easyJet RyanAir33% 7% 4%
Air India IndiGo Jet Airways30% 18% 17%

Page 33
AT&T Verizon T-Mobile28% 25% 9%
Top trusted telecommunications
Bell Rogers Telus25% 21% 16%
O2 EE Vodafone16% 12% 10%
Orange Free Airtel30% 29% 21%
Airtel Vodafone Idea34% 18% 17%

Page 34
Walmart Kroger Target and Costco21% 8% 6%
Top trusted retail
Costco Shoppers Drug Mart Canadian Tire12% 12% 10%
Tesco ASDA Sainsbury’s21% 9% 9%
Carrefour Auchan Intermarche20% 15% 9%
Big Bazaar Reliance Fresh Tanishq33% 11% 10%
´

Page 35
Facebook Google Yahoo31% 15% 15%
Top trusted web services
Facebook Google LinkedIn27% 22% 6%
Facebook Google LinkedIn31% 14% 4%
Facebook Google Twitter31% 22% 3%
Google Facebook LinkedIn47% 39% 6%

Page 36
Amazon Walmart Ebay57% 6% 6%
Top trusted e-commerce
brands (in five counties)
Amazon Costco Ebay24% 11% 10%
Amazon Ebay Tesco42% 13% 8%
Amazon Cdiscount Fnac.com35% 12% 9%
Flipkart.com Amazon Snapdeal.com46% 13% 8%

Page 37
We asked if this trust influences
consumers’ willingness to share data
• After identifying a trusted brand, consumers were asked to consider what influence that trust
would have on the specific data points that they previously noted they would be “willing to share” or
“unlikely to share” with a firm in that industry.

Page 38
Brand trust strongly influences the level at which
consumers are willing to share their data…
Q: How does your relationship with [your trusted company] influence the likelihood that you would
share the following pieces of data that you identified as being willing to share?
27%
28%
29%
31%
40%
39%
44%
44%
45%
51%
51%
50%
49%
41%
43%
40%
41%
40%
Website history
Purchase history
Lifestyle info
Mobile phone
Date of birth
Address
Name
Email
Much more likely to share Somewhat more likely to share
85%
85%
84%
82%
81%
80%
79%
79%
78%

Page 39
…and even influences the data they
say they are not likely to share
Q: How does your relationship with [your trusted company] influence the likelihood that you
would share the following pieces of data you indicated you would not be likely to share?
4%
4%
4%
6%
12%
12%
20%
21%
22%
24%
25%
30%
29%
37%
40%
43%
48%
48%
Website history
Lifestyle info
Purchase history
Mobile phone
Date of birth
Address
Email
Name
Much more likely to share Somewhat more likely to share
70%
69%
63%
52%
49%
35%
34%
29%
28%

Page 40
Impact of brand trust on willingness to share
varies by country, primarily for PII data types…
50%
46% 45%
38%
34%
Percentage "much more
willing to share"
would share the following pieces of data you indicated you would not be likely to share?
Percentage of respondents that were “much more willing to share” averaged across all five PII data types

Page 41
…but these country differences do vary
depending on the data type
would share the following pieces of data that you identified as being “willing to share”?
31%
34%
33% 33% 33%
40%
42%
45%
47%
50%
26%
31%
29%
25%
31%
42% 42%
50%
47%
50%
23%
24%
27%
23%
27%
34%
31%
35%
36%
35%
29% 29%
28%
27%
30%
39%
34%
37%
38%
40%
24%
34%
29%
30%
34%
50%
48%
49%
54%
49%
1 2 3 4 5 6 7 8 9 10
Series3 Series2 Series5 Series4 Series1UK IndiaFranceCanadaUS
Social network
access
Website
history
Purchase
history
Lifestyle info Hobbies Mobile phone Date of birth Address EmailName
Percentage of respondents “much more willing to share”

Page 42
Brand trust matters more to older generations in ‘traditional’
industries, but has a higher impact for Millennials in new industries
Q. How does your relationship with [your trusted company] influence the
likelihood that you would share the following pieces of data?
40%
34%
38%
29%
35%
44%
38%
32%
35%
32%
27%
36%
45%
36%
40%
36%
23%
38%
58%
46%
48%
37%
35%
40%
1 2 3 4 5 6
Series1 Series2 Series3 Series4Millennials Generation X Boomers Silent Generation
Financial Services Telecom Airlines Web Services E-commerceRetail
20th CENTURY 21st CENTURY
Percentage “much more likely to share” a data point they were generally “willing to share” in the industry

Page 43
Companies benefit most from brand trust when people are more
comfortable with how the industry handles data, with one exception…
Q. How does your relationship with [your trusted company] influence the
likelihood that you would share the following pieces of data?
CATEGORY
IMPACT OF BRAND ON
PII DATA
IMPACT OF BRAND ON
NON-PII DATA
REPORTED COMFORT
IN INDUSTRY
Financial services 48%-54% 28%-45% 57%
E-commerce 37%-50% 25%-35% 31%
Retail 37%-46% 30%-37% 43%
Telecom 37%-46% 23%-32% 46%
Airlines 36%-42% 23%-30% 40%
Web services 25%-35% 18%-29% 33%
Percentages reflect “much more likely to share” responses

Page 44
…The Amazon Effect
• The e-commerce category shows the most impactful influence of trust in what we call “The Amazon Effect.”
• E-commerce is an outlier among the six industries because of its extremely strong category leader, Amazon.
Even though people reported the lowest comfort with how e-commerce companies handle their personal data
in comparison to other industries, the Amazon brand had such a strong positive impact that it led to a 6 to 19
percentage point boost in willingness to share PII data.

C H A P T E R 4
Offers are impactful, but
should be used strategically

Page 46
We asked which offers would influence people to supply
each of these, generally non-required, data points
Q: Please indicate whether you would be willing to share each of the specific types of information
in order to benefit from each of the following offers. [CHECK ALL THAT APPLY]
 Email address
 Mobile phone number
 My purchase history
 Social network permissions
 My household income

Page 47
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Tools for decision making
Recommendations
Exclusive customer service
Less spam
Special event invite
Coalition rewards
Location-based discounts
Coupon for future
Cash back
Rewards from company
Willing to share any of the five data points Willing to share email only
Offers do influence how people share
these non-required data points
Q: Please indicate whether you would be willing to share each of the specific
types of information in order to benefit from each of the following offers.
80%
79%
77%
69%
66%
63%
62%
61%
56%
53%

Page 48
We found that the influence of offers
depended on two strategic dimensions
The variety of offers can be viewed along two axes as follows:
• How direct or indirect the offer is
For example, can the offer be used immediately, is it valid within the store providing the offer, is it offering a specific
value or something more general?
• How financial or experiential the offer is
For example, is the offer providing a mostly financial incentive or a more experiential incentive?
We then mapped the 10 offer types by their influence on consumers’ willingness to share data.

Page 49
Strategic map of offer influence
Q. Please indicate whether you would be willing to share each of the specific
types of information in order to benefit from each of the following offers
FINANCIAL
EXPERIENTIAL
INDIRECT DIRECT
Rewards from
the company
Rewards from
a coalition
Fewer
marketing
messages
Recommendations
~70% ~80%
~60%~55%
Discounts based
on location
Tools to manage
complex decisions
Special event
invitations
Exclusive customer service
Coupon
for future
purchase
Cash back
Percentage of responses with any of the five data types chosen

Page 50
Younger generations show a much higher interest in
sharing non-email data types across all offers
53%
23%
21%
13% 12%
22%
53%
16%
18%
10% 9%
27%
52%
11% 12%
6%
4%
36%
47%
8%
12%
5% 4%
39%
Email Mobile phone Purchase history Household income Social network access None
Percentages represent the average across all 10 types of offers

Page 51
The influence of offers on data sharing
does also vary by country
Q: Please indicate whether you would be willing to share each of the specific types of
information in order to benefit from each of the following offers.
54%
16%
18%
11%
9%
29%
55%
10%
12%
6% 5%
34%
52%
13% 14%
7% 6%
34%
45%
13%
16%
9%
7%
35%
50%
31%
21%
13% 13%
11%
Email Mobile phone Purchase history Household income Social network access None
US Canada UK France India
Percentages represent the average across all 10 types of offers

Page 52
The influence of offers
varies by gender
Women are roughly 10% more likely
to share their email for all offers.
Men are roughly 4% more likely to share
non-email data points — particularly mobile
phone, household income, and purchase
history — for many offers.

C H A P T E R 5
Future Trends
A. THE DATA-SHARING MINDSETS OF CONSUMERS
B. NEW, DATA-ENABLED BENEFITS
C. PERSONAL INFORMATION MANAGEMENT SYSTEMS

C H A P T E R 5 : F U T U R E T R E N D S
A. The Data-Sharing
Mindsets of Consumers

Page 55
We identified four ‘Data-Sharing Mindsets’
To examine how consumer attitudes and behaviors might be changing, we looked at two key attitudes to help
profile different ways people perceive and act on sharing their personal data.
Defensive attitude axis
This categorized consumers according to whether or not they had: 1) made up personal details to avoid giving away real
information, or 2) had taken steps to limit companies from tracking them online.
Sharing attitude axis
This categorized consumers according to their attitude towards being happy to share personal information to receive
relevant offers and discounts.
This permitted a segmentation of consumers into four Data-Sharing Mindsets.

Page 56
The Data-Sharing Mindsets of Consumers
LOW
DEFENSIVE
HIGH
DEFENSIVE
NOT HAPPY TO SHARE HAPPY TO SHARE
43% 24%
10%23%
DEFENDERS SAVVY AND IN CONTROL
HAPPY GO LUCKYRESIGNED

Page 57
What the Data-Sharing Mindsets indicate
• These mindsets indicate that even though people may be concerned and want control of their information,
that does not prohibit them from wanting to share data.
70% of respondents who have a positive attitude toward sharing data also take defensive actions with their data.
• In addition, a majority of consumers are either happy about sharing data or display low defensive behavior.

Page 58
34%
36%
20%
10%
26%
41%
22%
11%
18%
48%
24%
10%
12%
46%
29%
13%
Savvy and In Control Defender Resigned Happy Go Lucky
Each generation is divided differently
among the Data-Sharing Mindsets
Percentages show the portion of respondents within the generation with the Mindset indicated

Page 59
A consumer’s Sharing Mindset predicts their
comfort with how businesses handle their data
52%
38%
33% 33%
22% 23%
49%
37% 37%
32%
27%
22%
66%
59%
57%
50%
45%
42%
70%
61%
59%
55%
51%
48%
Financial services Telecommunications Retail Airlines Web services E-commerce
Defender Resigned Happy Go Lucky Savvy and In Control
Percentage of respondents reporting they would be very or somewhat comfortable

Page 60
Data-Sharing Mindsets also predict a consumer’s
willingness to share all data types
46%
45%
35% 34%
Happy Go Lucky Savvy and In
Control
Resigned Defenders
Percentage
willing to share
Q. Please indicate how you would plan or expect to share the following types of
your personal data in order to purchase their products/services.
Percentages represent averages of “willing to share” responses across all data points and industries

Page 61
20%
25%
26% 26%
27%
37%
35%
39%
42%
44%
17% 17% 17%
23%
21%
34% 34%
38%
39% 39%
27%
23%
27%
28%
32%
40%
38%
40%
42%
43%
34%
36% 36%
39% 39%
44%
46%
49%
52%
51%
Social network
access
Website history Purchase history Lifestyle
information
Hobbies Mobile phone Date of birth Address Name Email
‘Savvy and In Control’ consumers are
impacted most by brand trust
Q. How does your relationship with [your trusted company] influence the likelihood that you
would share the following pieces of data that you identified as being willing to share?
Percentages represent respondents indicating they are "much more willing to share" averaged across all six industries

Page 62
51%
12% 12%
6% 5%
35%
49%
12%
14%
8%
6%
35%
58%
21%
24%
13%
11%
24%
55%
20% 20%
13%
11%
19%
Email Mobile phone Purchase history Household income Social network None of these
Data-Sharing Mindsets also predict how much offers
influence a consumer’s willingness to share data
Percentage of respondents that selected any of the five data types averaged across all 10 offers

Page 63
How the mindsets drive sharing
• The sharing attitude axis is a strong driver of comfort with companies handling data, and a willingness
to share a range of data types.
• Those who are happy to share data do not report reduced comfort or willingness to share, even if they
take defensive actions with their data.
• Importantly, this means that an urge for control over one’s data does not preclude a consumer’s
interest in sharing it as well.

Page 64
Data-Sharing Mindsets and the future
• We wonder how the Data-Sharing Mindsets would have been divided five years ago.
• Due to increasing attention drawn to data theft, loss, and monitoring, we would expect that many people
with Happy Go Lucky or Resigned mindsets in the past would have become Savvy and In Control or
Defenders.
• We believe that in the future, more and more consumers will likely take defensive actions. Therefore, the
key issue for companies will be driving a value proposition that keeps consumers happy and willing to
share their personal data.

Page 65
How younger consumers will drive future
relationships with marketers
While we are wary of making predictions of generational attitudes into the future, we do believe that the impact
of growing up in a hyper-connected society will remain as generations grow older. Given this, the much larger
percentage of Millennials and Generation X members in the Savvy and In Control mindset should offer
companies hope for building stronger consumer relationships over time.
Those with a Savvy and In Control mindset:
• Are the most influenced by brand trust, demonstrating that investing in brand building will continue to provide value.
• Are more enticed than other mindsets by broader value propositions, indicating that companies can use the vast
streams of data they collect to deliver greater, and potentially unique, consumer value.
• Demonstrate that the desire for data control and an interest in sharing data are not mutually exclusive.

B. New, Data-Enabled Benefits

Page 67
Businesses are beginning to explore
non-traditional, data-enabled benefits
• Netflix and Amazon, for example, spurred the use of aggregated customer data to improve an individual user
experience through product recommendations.
• Energy companies are looking to use and share data with their customers to help them be more efficient,
save money, and improve society.
• Services such as Mint and Billguard are compiling financial information and providing insights back to
consumers in order to help them make better decisions and protect against fraudulent or inappropriate
finance charges.
• Apple is stressing to customers the steps it is taking to avoid keeping or sharing their data.

Page 68
Non-traditional benefits can influence people’s
willingness to share non-required data
7%
8%
10%
17%
19%
22%
27%
30%
Insights
Societal
User experience
Security
Very likely to share Somewhat likely to share
Q: For each example of a data practice, please indicate how likely you would be to share
non-required types of personal data if the company used such a practice
47%
37%
30%
26%

Page 69
The interest in non-traditional, data-
enabled benefits varies by country
60%
33%
26% 26%
25%
Percentage likely to
share data
Q: For each example of a data practice, please indicate how likely you would be to
share non-required types of personal data if the company used such a practice.
Percentage of respondents reporting they would be much more likely or somewhat more likely to share

Page 70
Younger generations show a higher interest in all
types of non-traditional, data-enabled benefits
Generation
33%
25% 25%
43%Percentage likely to
share data

Page 71
Q. Please indicate whether you would be willing to share each of the specific types
of information in order to benefit from each of the following offers
Attitudes towards non-traditional, data-enabled
benefits varies somewhat by gender
Percentage of respondents reporting they would be much more likely or somewhat more likely to share,
averaged across all five data-enabled benefits
Men Women
29%
33%Percentage likely to
share data

Page 72
28%
22%
20%
18%
28%
23%
19% 18%
49%
38%
33% 32%
54%
46%
43%
40%
Provide better customer experience Offer benefits to society Shares insights based on all customers Help me learn more about myself
‘Savvy and In Control’ mindsets show the greatest
affinity towards data-enabled benefits

C. Personal Information
Management Systems (PIMS)

Page 74
A new service: your personal data manager
• We also wanted to look at a new service that would benefit consumers as data collection becomes more
prolific and of greater interest.
• Various types of companies are exploring Personal Information Management Systems (PIMS) that would act
as an intermediary service to store a consumer’s personal data and allow her to decide how to share
different pieces of that data with companies.
• PIMS would allow users to easily control (“turn on and off”) the data they share with different companies to
enable a more explicit value exchange with these companies.

Page 75
25%
21%
32% 33%
15%
19%
8%
8%
15%
23%
5%
6%
Would be willing to consider Believe it would benefit society Would only join if "my" brands are
in system
Would expect additional benefits Would share a wide range of data Would accept offers from new
companies
Somewhat agree Strongly agree
Consumer attitudes towards PIMS
PIMS CONCEPT PIMS FEATURES
33%
29%
47%
56%
20%
25%

Page 76
Attitudes towards PIMS
vary by gender
Q. To what extent do you agree or disagree with the following
statements about [the PIMS] concept?
Men
36%
29%
Consider PIMS See it as a benefit to society
32%
27%
Give up a wider range of data
23%
17%
Accept offers from new
companies
27%
22%
Percentage of respondents that strongly or somewhat agree
Women

Page 77
26%
23%
43%
55%
14%
18%
24% 23%
39%
47%
14%
18%
40%
36%
52%
60%
27%
32%
49%
44%
59%
66%
34%
41%
Willing to consider Believe it would benefit society Only join if "my" brands are in
system
Expect additional benefits Would share a wide range of data Would accept offers from new
companies
Those with ‘Savvy and In Control’ mindsets
show greater interest towards PIMS
PIMS CONCEPT PIMS FEATURES

C H A P T E R 6
Strategic
Recommendations

Page 79
Invest in building both data and customer trust
Treat Data as an Asset
• Customer data is a key intangible asset for your business.
• Plan for how you can build the value of this asset
over time.
Invest in Trust
• Do not assume customers will trust you with their data.
• Invest in brand trust and reputation (via service,
responsibility, transparency) if access to customer data is
vital to your long-term business strategy (and it is!).
• Recognize that firms in your industry may have to
try harder to demonstrate their trustworthiness with
customers’ data than other industries.
• If you do need to offer customers rewards to motivate data
sharing, look to offer them benefits that do not undermine
the perceived value of your offering (e.g. upgrades and
exclusives rather than cash back).

Page 80
Give customers value and control
Use the data customers give you to deliver more
value to them
• Use data as a source of innovation to deliver new value and
enhanced products and services for customers (not just as
a way to increase the efficiency of your advertising spend).
• Do not ask for data unless you need it and can show the
value you will provide to customers with it.
• Design customer experiences so that customers choose to
share data as part of a value-adding experience; that way
you don’t even need to explain or persuade how sharing
data will benefit them.
Understand that customer comfort differs
• Plan for the expectation that some customers will be
more willing than others to share data with you.
• Try to wait to ask for more data from customers after you
have established a trusted relationship.
Put customers in control
• Give customers options and tools for control of their
own data.
• Help your customers to be, and feel, more savvy about
their data and how it is used.

A P P E N D I X
Authors,
Acknowledgments,
and Methodology

Page 82
Authors
Matthew Quint (mq2120@columbia.edu) is the Director of Columbia
Business School's Center on Global Brand Leadership, which creates,
gathers, and shares insights on what it takes to build strong brands. In
this role, Matthew researches, writes, and presents on a wide range of
issues critical to successful brand building and management. He has
particular expertise in marketing ROI, strategies for marketing in the
digital age, and the development of creative and effective brand
communications.
Matthew is the co-producer of the Center's acclaimed BRITE
Conference series on brands, innovation, and technology, now in its 9th
year, which brings together over 500 big thinkers in industry and
academia to discuss how innovation and technology help build strong
brands. He has worked with senior executives from various leading
companies — including Aimia, Coach, Deloitte, Edelman, Lonza, and SAP
— to conduct research, produce events, and promote knowledge sharing
among branding and marketing leaders.
David Rogers (david.rogers@columbia.edu) is a globally recognized
leader on brands and digital business strategy, known for his pioneering
model of customer networks. He is author of three books, most recently,
The Network Is Your Customer: 5 Strategies to Thrive in a Digital Age, as
well as the forthcoming, The Digital Transformation Playbook (2016).
At Columbia Business School, David teaches global executives as the
faculty director of Executive Education programs on Digital Marketing
Strategy. His recent research has focused on in-store mobile shoppers,
big data, and digital marketing ROI. He is also the founder of the Center
on Global Brand Leadership's acclaimed BRITE conference.
David has consulted and developed executive programs for global
companies such as Google, Toyota, Pernod Ricard, Visa, SAP, Lilly,
Combiphar, IBM, China Eastern Airlines, Kohler, Saint-Gobain, and
MacMillan, among many others. He has delivered strategic workshops
for executives in hundreds of companies from 64 countries. David is a
board member of the Marketing Hall of Fame, and is president-elect of
the NY American Marketing Association.

Page 83
Acknowledgments
Deep thanks go to Fatima LaHay and Annie Balant from Vision Critical
for their project management and fielding of the survey. Crucial support,
comments, and questions came from the Aimia Institute team (a sponsor
of the Center on Global Brand Leadership) during the early days of
survey development and in feedback on the data analysis. Thanks
to Aaron Dauphinee, Martin Hayward, Michelle Stern, Nicola Waterman,
and Laura Hewitt.
Finally, special thanks go to Isadora Levy, a graduate student at
Columbia Business School, who supported the data analysis, and
Gabriela Torres Patiño and Allie Abodeely from the Center on Global
Brand Leadership for their research and editing support.

Page 84
Methodology
The online survey was designed by Columbia Business School and
fielded by Vision Critical from February 3-11, 2015. A total of 8,160
respondents completed the survey: 2,004 from the United States;
2,036 from the United Kingdom; 2,111 from Canada; 1,007 from
France, and 1,002 from India. Qualified respondents were age 18 or
older, and resided in the US, UK, Canada, France, or India. The
respondents were closely representative of the general population (not
just the online population) of age 18+ respondents in each country, with
the exception of India, where the respondents slightly over-indexed as
younger and more affluent than the overall Indian population.
For the industry-specific sections — primarily the Findings sections 2 &
3 — each respondent was randomly provided two (of six) industries to
consider. Comfort-related questions used a standard 5-point Likert
Scale from Very Comfortable to Very Uncomfortable. Agreement-related
questions used a standard 5-point Likert Scale from Strongly Agree to
Strongly Disagree. The brand trust section used a 3-point scale: Much
more likely to share, Somewhat more likely to share, No more likely to
share. The data-enabled benefits section used a standard 5-point Likert
Scale from Very Likely to Very Unlikely. A downloadable copy of this
research report and a complete list of the survey questions can be
obtained online at: gsb.columbia.edu/globalbrands or visit Aimia Institute
at aimia.com.

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