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The Consumer
Data Value
Exchange
Building better terms of
engagement for data
(and why the future of
brands depends on it)
Contents
Introduction
3
What is data anyway?
6
The sharing gap
8
Different sharing cultures
9
How data resentment holds brand relationships back
12
A playbook for a value-driven data exchange
16
How to ask for more data – and get the right answer
23
APPENDIX
More on Sharer Profiles
24
The Microsoft Digital Consumer Needs Model
32
Introduction
Data sharing and why it matters
Data is rapidly becoming a fundamental currency for brandconsumer relationships, exchanged at almost every touchpoint with
benefits to both parties. However, it is a currency that only one
participant in the transaction fully understands. The value that data
provides is far less clear to consumers than it is to the brands they
exchange it with. To many of them the data transaction appears
hugely one-sided – brands set the terms and seem to reap most of
the gains.
This matters to brands not just because they increasingly rely on
data to provide high quality products and services and compete
effectively; but also because willingness to share data will
increasingly shape brand perceptions and brand loyalty. The brands
that can unlock deeper consumer relationships will be those that
can help their consumers to understand the mutual benefits of
sharing data. The act of willingly exchanging data is a conscious
investment on the part of consumers – and such an investment can
take brand relationships to a new level.
Beyond privacy: revealing underlying consumer attitudes
towards data
Most studies of the exchange of data between brands and
consumers have focused specifically on the concept of privacy. As a
result, they have tended to draw instinctive, knee-jerk reactions from
consumers regarding an idealized view of privacy and how they
value it. The Microsoft Value Exchange study deliberately goes
deeper. We wanted to understand not just how consumers say they
feel about data, but how their perceptions and emotions towards it
shape their actual behavior.
72
Qualitative interviews: 12 Super Sharers participated in week long blogs followed by small
workshops in New York; 60 mainstream consumers joined in-person interviews (in pairs) in China,
France and the US (with the Future Laboratory)
7,252
Online interviews with mainstream consumers for market deep dives. Incorporated survey, conjoint
and implicit association measurement in China, France and the US (with Sentient Decision Science).
Tradeoff and deep dive responses reported in this report will be noted with a “1” superscript.
16,500
Online survey respondents (A16+) across global markets: Australia, Brazil, Canada, Colombia, Egypt,
Germany, Kenya, Mexico, Nigeria, Spain, South Africa and the UK (with Research Now). Explicit
responses reported in this report will be noted with a “2” superscript.
We designed the research in two
complementary phases. In the first qualitative
phase, we worked with The Future Laboratory
in London to interview consumers in the US,
France and China on their attitudes around
data sharing. We used workshops with super
sharers, weekly diaries and paired interviews
with mainstream consumers to probe
contradictory attitudes about data usage and
reveal deeper motivations behind sharing
behaviors.
In the quantitative phase, we surveyed over
16, 500 global respondents with Research
Now to understand baseline understanding of
data collection and sharing perceptions. We
also measured respondents’ openness to
services from different types of companies
and the services that they look to engage with
across the digital landscape.
We then partnered with Sentient Decision
Science for a deep dive into three types of
sharing markets, France, the US and China.
The approach used a neuroscience-enhanced
conjoint analysis to reveal the impact that
attitudes to data have on consumer decisionmaking.
Measuring the automatic emotional associations people have
when faced with the prospect of sharing their personal
information reveals the implicit emotional weight of responses
Data to be shared appears
as a “prime”
Then an emotion like
anxiety appears that needs
to be sorted into a correct
category
The response time is
recorded as an implicit
measure of the association
between the “prime” and
the emotion
Sentient Decision Science Proportion of Emotions Model
This innovative hybrid approach used priming
techniques that used reaction time to assess
the strength of automatic emotional
responses to data (see illustration).
The result is a far fuller understanding of how
the conceptual System 2 and more automatic
System 1 brain respond to the concept of
sharing data. As a result, our research delivers
a far more predictive basis for understanding
what consumers are willing to share, and what
emotions they feel when doing so. By layering
the insights from each of the phases of the
study, we are able to quantify and go deeper
into how and what consumers truly
understand and feel about data and data
sharing.
What is data
anyway?
Most companies know what they mean
when they refer to consumer data, but far
fewer consumers do. Only a small,
technically savvy minority instinctively
envisage data in the form that it typically
takes: a continuous stream of information
that is generated automatically by digital
activity. Many others assume that data is
information that they consciously share:
personal details such as name, age and
address, or the content that they share with
others.
This matters because consumer perceptions
of what data is have a huge influence over
their sense of ownership towards it and their
expectations of what it can be used for.
Identity, demographics and content have a
significant personal value attached to them.
They are seen as the principle currency in
the data exchange. Much less attention and
much less value is attached to back-end,
behavior-based data, which is actually far
more likely to be used.
Perceptions of data inform what consumers
believe is being asked or taken from them,
but also what they can expect to get in
"It’s like your personal
data….like a
membership card, it’s
your identity online."
- Mainstream Female, Shanghai
return. Those with a less sophisticated
understanding of data types and data usage
find it difficult to see how the shared data
can be used for anything other than selling
to them. Those with a more sophisticated
understanding of data can envisage how it
can enable better, more seamless and more
relevant digital experiences.
We see the impact of these perceptions in
the barriers to data sharing that emerge
from the research: concern about identity
and address information being used to
bombard or spam consumers with irrelevant
marketing; transparency issues with
personal information falling into the wrong
hands; resentment at brands seeking to
hijack their personal networks to share
messages. Underlying this is a lack of
control; a sense that once data is shared it
will be manipulated in ways that consumers
cannot control in an exchange that they do
not fully understand. It is noticeable that the
first three of these barriers envisage
personal data being shared in way that can
be traced back to the person; and the fourth
is a natural reaction to these expectations.
How we
defined
data
types
"It’s unavoidable that the data will be used – I would think they would
be using my data for statistics, they know what I would like, work out
how to show me relevant content and also sell me relevant products
based on what they know.“
- Mainstream Female, Shanghai
Data Types
Data Included
Demographics
Age, Gender, Marital Status
Activities/ Preference
Personal Profile, info on things owned, purchase history,
Search Terms, previous sites visited, physical activity,
preferences
Organization/ Movement
Calendar, Location via GPS
Social Identity
Posts, pictures, videos, list of friends/people known
Communication
Personal and work communications (email, IMs, texts,
newsletters, mail, etc.)
Personal Information
Data of Birth, Personal income, Credit/Debit card number,
Address
Biometrics
Facial Recognition, Fingerprints, physiological
measurements (e.g. Heart Rate)
The sharing
gap
The lack of control that consumers feel
about the use of their data is recorded in
the form of the “Sharing Gap”: a distinct,
measurable divergence between the
types of data that they consciously
share, and the types of data that they
believe brands collect anyway.
Consumers believe that brands in all
categories are collecting more
information than they themselves are
actually sharing and the varying sizes of
the Sharing Gap reflect the different
dynamics involved with different
categories, and different data types.
Consumers tend to recognize that they
are entering a conscious bargain to
share personal information or
demographic data, which usually
involves them entering information
online. They believe that other forms of
data (on their location or social media
activities) are often collected, whether
they have agreed to it or not. Since
many consumers see these latter kinds
of data as personal and specific to them,
perceived usage without tacit permission
is a likely cause of resentment.
% of respondents who say (global avg
across all categories and data types)²
Data is collected
by companies
Data is shared
with companies
Gap by category (% data is perceived
as collected vs actively shared)²
Category
Technology
Financial Services
Travel
Retail
Entertainment
CPG
Auto
Luxury
% Share
63%
59%
44%
43%
36%
27%
22%
21%
Gap
-14
-16
-17
-12
-11
-13
-19
-13
Different
sharing
cultures
Consumer attitudes towards sharing are
shaped by their awareness and appreciation
of different data types and their value, and
also their experience in seeing the benefits
of data sharing first hand. However, they are
also impacted by the national discourse
around privacy and cultural attitudes
towards business in their country.
For these reasons, we see significantly
different attitudes to data sharing emerging
in the three markets that were the primary
focus of this study. These reflect broad
national characteristics. However, the
variation also shows us how attitudes to
data can vary within markets as well.
Different age groups will have different
expectations and attitudes based on the
culture in which they grew up; customers of
brands in different categories will differ in
their view of what data those brands are
likely to collect – and what use they are
likely to put it to. When seeking to build
greater willingness to share data, brands
may find themselves dealing with an
audience that is distinctly ‘French’,
‘American’ or ‘Chinese’ in its characteristics,
no matter which market they are operating
in . A grocery shopper driving to the
supermarket will have very different
attitudes and expectations towards sharing
data with the different businesses involved
in the shopping trip: the auto manufacturer
whose car they are driving, the retailer they
buy from and the bank whose card they use
to pay. A 20-year-old shopper who has
grown up alongside digital channels built
around shared data may have very different
attitudes to a 50-year-old consumer who
has never had a Facebook account.
Of the three countries, France demonstrates
the greatest resistance to sharing data, with
an emphasis on the sanctity of privacy and
the requirement for the consumer always to
remain in control. The predominant belief is
that companies have no right to collect data
without clearly communicated, consumerfocused benefits. This reluctance results in
low numbers of active sharers, and larger
Sharing Gaps. It’s a pattern that we might
expect to see reflected amongst older
demographics across different markets, as
well as consumers dealing with healthcare
or finance brands where private information
is seen as particularly valuable.
Perceived Data Shared vs Collected by Industry¹
Data 'Shared'
Data 'Collected'
France
78%
77%
76%
75%
71%
68%
66%
51%
61%
Financial
Services
52%
57%
Technology
47%
44%
41%
Retail
Travel
CPG
Entertainment
32%
31%
Auto
Grocery Stores
US
88%
86%
85%
83%
80%
81%
80%
75%
76%
73%
75%
66%
62%
64%
56%
64%
Financial
Services
Technology
Retail
Travel
CPG
Entertainment
Auto
Grocery Stores
89%
88%
87%
83%
83%
81%
China
91%
57%
85%
84%
82%
86%
Financial
Services
Technology
Travel
Retail
77%
73%
CPG
Auto
74%
54%
Entertainment Grocery Stores
More Chinese consumers believe they share their data with grocery
stores than believe that data is collected by grocery stores.
US consumers exhibit a more ambivalent
attitude to the exchange of data. There is an
expectation and to some degree, an
acceptance that companies will use data for
commercial gain. This leads to some
concern about appropriate use of data.
However for the most part, consumers trust
businesses to use their data respectfully –
and they expect to receive tangible benefits
in exchange for it . A retailer could satisfy
this ‘improve me’ consumer need by
suggesting relevant promotions when a
customer swipes a loyalty card in store, for
example, or by emailing suggestions for
books or films they might enjoy once they
have shopped online. Such expectations of
tangible benefits from the limited exchange
of data in specific categories are
increasingly typical of mainstream
consumers in general.
With far fewer cultural expectations around
data privacy, China’s attitude to the sharing
of data might best be described as
‘resigned’. Consumers expect data to be
shared as a matter of course, and as an
inevitable result of engaging with brands
online. As a result, China has the lowest
Sharing Gap of all three markets, and in one
category the Gap is actually inverted.
Chinese grocery shoppers believe that they
are sharing more data than grocery brands
are actually making good use of. The
demand here is for better and more relevant
marketing and promotions that reflect the
data they know they are making available.
And this provides an interesting glimpse of
how expectations of brands change once
consumers accept a broader exchange of
data: fewer concerns about whether data is
collected or not; greater emphasis on
whether businesses are able to deliver
tangible consumer benefits using it.
Younger audiences in global markets and
categories such as media and entertainment
increasingly demand that companies both
collect more data and make more visible
and empowering use of it. In part, this is a
result of the vast amount of content that
these audiences consume through digital
channels; they value any use of data to filter
and curate content and ensure relevant,
bespoke experiences.
How data
resentment
holds brand
relationships
back
Persuading consumers to share data willingly
delivers an obvious benefit to brands in
enabling them to make greater use of that
data, deliver improved experiences for their
consumers and strengthen brand
relationships. However, the research also
suggests that the very act of consciously
sharing data strengthens the brandconsumer relationship in itself.
When we cross-referenced these profiles
with characteristics such as willingness to try
new products and services, being an early
adopter and expressing oneself through
brand choices, we found a clear correlation.
People who enter into a willing and wellinformed data sharing relationship with
brands offer those brands far greater value
going forward.
From the research results, we were able to
identify six distinct sharer profiles based on
consumers’ understanding of the concept of
data, combined with their willingness to
share it.
The priority for brands should therefore be
converting Nervous Neophytes, Cautious
Contributors and Observant Objectors into
Satisfied sharers, Enthused Explorers and
Savvy Sophisticates. In order to do so, they
must move consumers from a mindset where
they see themselves as data victims to one
where they have a more intuitive and
emotive relationship to data. Brands can help
people transition from a privacy discourse,
where corporations are thought to reap all
the benefits and control is paramount, to a
sharing landscape where new dynamics
around digital identity shape new
expectations of personal value.
The six sharing segments:
Willing to Share
Not willing to Share
Satisfied Sharers
Nervous Neophytes
Enthused Explorers
Cautious Contributors
Savvy Sophisticates
Observant Objectors
Getting to know the sharing segments:
Willing to Share
Low
awareness
of data
High
awareness
of data
Not willing to share
The Transaction Trap
Thus far, a strategy adopted by many brands
has been to attempt to move consumers
directly from reluctant sharers to willing ones
without updating their understanding of data
in the process. In our segmentation model,
this usually means converting Nervous
Neophytes (the majority of users) directly
into Satisfied Sharers. However, this strategy
follows the path of greatest data resistance.
Amongst consumers with a weak
understanding of what data is and how it is
used, there is extreme reluctance to share. In
fact, this group are four times more likely to
resist sharing data. Trying to increase their
willingness to share without increasing their
understanding of data is a challenging task.
Preferred benefits by market¹
Global
100%
Pays me cash
rewards
France
89%
Offers me
significant
discounts
65%
Loyalty points for
services and
products
US
99%
92%
87%
Pays me cash
rewards
Offers me
significant
discounts
Loyalty points for
services and
products
China
100%
Pays me cash
rewards
77%
Offers me
significant
discounts
68%
Fewer steps to get
things done
Brands seek to overcome this barrier by
incentivizing sharing, usually through
discounts, promotions or offers. Such
inducements have succeeded in establishing
a market for personal data in the minds of
consumers. Cash rewards, significant
discounts and loyalty points are now the top
three benefits that consumers expect data
sharing to provide for them.
The problem is that this encourages
consumers to put a high price on their data
– and to refuse to relinquish it for any
reason other than financial reward. And as
99%
90%
Pays me cash
rewards
Offers me
significant
discounts
68%
Suggestions that
help me improve
we move towards a landscape where datadriven services are essential for most brands’
future competitiveness, that’s unlikely to be
a sustainable strategy.
Convincing consumers that data has a price,
and that they should expect brands to pay
that price, is not an attractive way forward.
But the study also demonstrates that there
are more sustainable strategies for
increasing willingness to share, and
increasing the value of consumers to brands
in the process.
Consumers overwhelmingly prefer to pay no
costs for new digital services¹
If costs are incurred, most would opt to “pay” by seeing more ads, having less control over their
privacy settings or allowing more information about themselves to be known over paying for services.
However, given then right alignment of benefit and data types, consumers, particularly in the US, will
opt to pay.
Preferred costs for new data-driven digital services
92%
No Additional Costs
94%
93%
81%
63%
You will see more ads
66%
60%
62%
62%
More information about you will be shared
52%
48%
82%
52%
You have less control over your privacy
settings
25%
66%
62%
27%
You have to pay a one-time fee for this
service
54%
27%
12%
Global
A playbook
for datadriven
exchanges
Most consumers cannot spontaneously list
what benefits they expect sharing data with
companies to bring to them – and herein
lies the real challenge for brands. Only by
increasing consumer understanding of the
potential value that shared data can bring
can they drive long-term willingness to
share.
In our segmentation map, the sustainable
way forward is not to seek to convert
Nervous Neophytes into Satisfied Sharers,
but to educate Nervous Neophytes to the
point where it is far easier to craft an appeal
focused on converting them to Savvy
Sophisticates.
The reason that Observant Objectors
represent the smallest proportion of
consumers in our segmentation model is
because it’s harder for consumers to resist
the logic of willing data sharing once they
understand more fully what is involved –
and what they stand to gain. Our research
provides a clear indication of the actions
that brands can take to guide consumers
through the stages of this educational
journey.
Stage 1: Promoting data understanding
through visibility and transparency
In the absence of clear, transparent
information about how data is used, the
natural assumption that consumers make is
that it is delivering benefit to the business
they are dealing with rather than to
themselves. However, when consumers are
made aware of the tangible benefits that
data can provide, their attitude to sharing
can change significantly. Calendar or
location data in the US, for example, has
one of the largest Sharing Gaps of all data
types. However, when the concept of
sharing is linked to a clear benefit in terms
of time-saving or more seamless
organization, it becomes one of the types of
data that consumers most prefer sharing.
66%
of US respondents willing to share
calendar/location data in exchange
for new digital services¹
Brands can minimize the sharing gap by
helping people recognize the personal benefits
of data¹
Those who see potential are not only much more likely to know that data is collected, but they also
have a much higher propensity to say they willingly share data with different companies. This
illustrates how knowing that data is collected doesn’t lead to resistance to sharing information.
Sharing Gap by Industry
Data 'Shared'
Data 'Collected'
High-value potential / Positive Willingness to Share
90%
86%
89%
87%
86%
84%
85%
64%
85%
84%
86%
82%
80%
79%
75%
Financial
Services
Retail
Tech
Travel
CPG
Entertainment
Auto
73%
71%
70%
66%
Grocery Stores
Low-value potential / Negative Willingness to Share
82%
66%
Financial
Services
81%
64%
Retail
81%
78%
57%
57%
52%
47%
45%
37%
39%
Tech
Travel
CPG
Entertainment
Auto
Grocery Stores
The more sensitive the data, the clearer
the benefit has to be for the consumer
Ranking of preference to share data types in exchange for new digital services
(from most to least willing - global average across all benefits and costs)¹
Activities/
preferences
Demographics
Social Identity
68%
Organization/Movement
66%
Activities/Preferences
57%
Demographics
56%
Communications
18%
Personal Information
15%
Physiological/Biometrics
11%
Organization
/movement
Social
identity
Communications
Personal
information
"Here, I feel they didn't
just take my data to make
money, but also gave me
something in return."
- Mainstream Female, France, 41
Demographics
59%
Activities/Preferences
84%
Organization/Movement
45%
Communications
77%
Activities/Preferences
44%
Demographics
70%
Social Identity
26%
Organization/Movement
48%
Communications
12%
Social Identity
32%
Personal Information
11%
Personal Information
32%
Physiological/Biometrics
21%
Physiological/Biometrics
8%
Biometrics
Stage 2: Respecting boundaries
Communicating more explicitly about the
nature of data use and the benefits it brings
can promote greater understanding.
However, brands must still respect the
nuances between different consumer groups
when it comes to the data that they are most
comfortable sharing, and what they expect in
return.
Social identity is far more willingly shared in
the US, for example, than in both France and
China. Communications are seen as more
valid data for sharing in China than in either
France or the US. Meanwhile in France, there
is notably greater willingness to share
demographic information than all other data
types. Brands should focus their efforts
around the data that consumers are most
willing to share, and ensure that a clearer
connection to benefits can be established
when asking to share more sensitive types.
At the same time, brands must respect the
underlying benefits that different groups
seek, whether that is to “put me in control”
(the predominant consumer need in France),
to “improve me” (in the US) or to “empower
me”, as with Chinese consumers demanding
more active and visible use of data.
Stage 3: Mapping data value to emotive
needs
Appealing to consumers’ conscious sense of
value and fair exchange can help to build
willingness to share on one level. However, to
promote more effective behavioral change,
brands should also seek to align the benefits
of data with deeper, emotive needs.
Microsoft’s digital needs model quantifies
the motivations that drive digital behavior,
and provides marketers and technologists
with a map for aligning tools, content and
experiences with these emotional drivers. It
captures the two emotional dimensions of
digital experiences: the contrast between
exploring the external world and controlling
internal emotions; intersecting with different
needs regarding focusing on themselves as
individuals, or connecting with others.
Data can play a fundamental role in meeting
three of the emotive needs that emerge from
this model, and aligning messaging with
these needs can significantly accelerate the
process of engaging consumers with the
benefits of sharing data.
Easing mundane tasks through seamless
integration of digital experiences meets
consumer needs for Order and feeling on
top of things;
Global respondents who would share search terms for
a service that enabled fewer steps to get things done
(e.g. automated services)¹
70%
Applications that enhance productivity in
both professional and personal lives deliver a
sense of Achievement through reaching
goals and improving individual performance;
Global respondents who would share activity data for
a service providing suggestions for improvement¹
82%
Enriching lives through enhanced
suggestions and relevant recommendations
encourages a sense of Discovery, and
accessing new experiences both online and
offline.
Global respondents who would share their gender
for a service that inspires something new based on
others like them¹
79%
John Lewis, has announced that it is implementing beacon technology in store.
It could detect when consumers walk into a store, for instance, and automatically trigger
that their Click & Collect order be readied in order to help speed up the checkout process.
Similarly it could help with navigation around the stores based on online wish lists.
Nike’s “Just Find It” campaign links activity to rewards. If you’ve earned 500 or more points
of NikeFuel, you can trade them in at the vending machine for gear such as socks and T
shirts, or even a Nike+ SportWatch. Over time, users get the added benefit of positive
goal reinforcement.
Lancôme allowed consumers to upload a photo and digitally try on makeup (and
share results) … all within the ad… without ever leaving the web page they were
visiting. Personal data is clearly linked to an immediate benefit and helps serve to
reinforce a broader definition of data types.
Order
Cortana gets to
know your social
circle and your
preferences
Achievement
Provides
recommendation
s based on
context
Discovery
Pulls in various data
streams to serve aid
discovery in new
ways
Cortana enables people to have a digital personal assistant that learns as you use it,
offering solutions to problems. Cortana is proactive and stays a step ahead by
providing proactive advice based on your context (device, location, time) and
preferences.
How to ask
for more
data… and
get the right
answer
Brands know that the sharing and use of
data is increasingly fundamental to their
consumer relationships. However, their
efforts to engage consumers with the value
of data sharing often do not reflect this
importance. All too often, the benefits
delivered by shared data are invisible to all
but the savviest consumers – and the uses
to which data are put remain mysterious,
opaque and worrying to many.
Many brands have fallen into the trap of
incentivizing data sharing through discounts
or coupons, persuading consumers that only
financial benefits justify willingly
relinquishing control of their data. Both
brands and consumers deserve better – and
the brands that succeed in building stronger
loyalty and engagement over the near
future will be those that negotiate a better
informed and more willing basis for data
exchange. Our research provides a clear
roadmap for doing so.
Make data meaningful
Don’t hide from a data conversation with
your consumers. Be upfront about the
benefits of sharing data and make it clear
what consumers gain from the exchange. In
the process you will correct outdated
perceptions of what data is and what
advantages sharing it can deliver.
Respect boundaries
Recognize different groups’ needs and
boundaries around data sharing – and craft
your appeal to share data appropriately.
Understanding the market you are dealing
with will inform whether to pitch the
benefits of data sharing around ‘put me in
control’, ‘improve me’ or ‘empower me’.
Focus on personal benefits
Embed the concept of personal value before
negotiating and asking for more data – and
don’t be afraid to link the benefits of data
sharing to deeper motivations and
emotions.
More on
Sharer
Profiles
THE SHARING SEGMENTS
Willing to Share
Low
awareness
of data
High
awareness
of data
Not willing to share
From the research results,
we were able to identify six
distinct sharer profiles
based on consumers’
understanding of the
concept of data, combined
with their willingness to
share it. Find out what kind
of Sharer you are by visiting
the interactive Profiler in:
Chinese
(http://bit.ly/1HOvy1a),
English
(http://bit.ly/1HOxQgP),
French
(http://bit.ly/1QcIvE3) and
Spanish
(http://bit.ly/1RqyyoO).
The Sharer Profiler
identifies your Sharing Type
using both explicit and
subconscious responses to
data, benefits and digital
sharing. It also provides a
visual example of how we
conducted the research and
the types of stimuli our
respondents were exposed
to in order to get at their
underlying reactions to
data and data sharing.
Note, sharer profiles were
identified using quantitative
results with Sentient.
The Reluctant Sharers
31%
of online sharers
2.8
Avg number of connected devices
6%
Own a wearable device
% of Sharers by Country
China
17%
US
26%
France
51%
Trendsetter
5%
Early Adopter
7%
"I don't know how [data collection] works. What
is used and what not and it scares me, because I
don't know if hackers could use it or not.“
Male Nervous Neophyte, France, 48
Nervous Neophytes are careful about sharing
information online, and concerned that
companies take insufficient care to protect
their personal details. They may occasionally
share email details in exchange for discounts
or coupons. The most privacy-conscious
group, Nervous Neophytes can be converted
up the value ladder by providing ways to
easily access privacy controls. Services that do
not require commitment (e.g. digital logins or
memberships) will be most attractive, until
they fully develop trust in the platform/service
through continued use.
The Reluctant Sharers
21%
of online sharers
3.2
Avg number of connected devices
13%
Own a wearable device
% of Sharers by Country
China
15%
US
24%
France
23%
Trendsetter
Early Adopter
10%
12%
"I don’t know what I’m giving up….I mean, I am
getting something for free but I don’t know what
I’m giving up. So if I knew…“
Female Cautious Contributor, US, 55
Determined to remain in control, Cautious
Contributors share data selectively in return for
specific, tangible benefits. They will accept
marketing messages as a reasonable trade for
free online services, for example, or share
specific forms of data in order to optimize
shopping and other online experiences.
Cautious Contributors know enough about
data practices to feel comfortable with most
digital tasks, but can be converted up the value
ladder through more immediate displays of
value and transparency (e.g. apps display link
between usage and data requested at sign on).
The Reluctant Sharers
5%
of online sharers
3.7
Avg number of connected devices
22%
% of Sharers by Country
China
7%
US
5%
France
3%
Trendsetter
22%
Early Adopter
23%
"If they give a benefit, something that will
improve my life, then they can use my data."
Male Observant Objector, France, 23
Own a wearable device
Observant Objectors have a full understanding
of the benefits that data sharing can bring, but
are determined to remain in control of when
and for what benefits they choose to share.
They are savvy about using technology to save
time and money, for example, but minimize
involuntary sharing of their data by
disconnecting from services when they are not
in use. For many Observant Objectors, this is a
matter of principle: they believe that brands
should allow them more control over their
data and privacy settings. Observant Objectors
are the hardest to convert up the ladder.
The Willing Sharers
8%
of online sharers
3.1
Avg number of connected devices
12%
Own a wearable device
% of Sharers by Country
China
8%
US
8%
France
8%
Trendsetter
Early Adopter
16%
16%
"Integration is my favorite - I try to live
efficiently, I want to be able to achieve more and
make the best use of time, and that really helps"
Female Satisfied Sharer, China, 18-20
Satisfied sharers have little sense of what
happens to their data – but are not overly
concerned by this, provided it helps to improve
their digital content and experiences, and
ensure their favorite apps works as seamlessly
as possible. They want data to be used to filter
out irrelevant content and provide inspiration,
but the details of how this happens in the
background do not really matter. Keep
Satisfied Sharers happy by providing new ways
to integrate their data across multiple services.
This will continue to reinforce the convenience
and utility of sharing.
The Willing Sharers
18%
of online sharers
3.6
Avg number of connected devices
24%
% of Sharers by Country
China
28%
US
16%
France
10%
Trendsetter
Early Adopter
28%
28%
'If they use my data to understand general trends
it's fine…."
Female Enthused Explorer, France, 34
Own a wearable device
Enthused Explorers happily allow access to
their online data when they know that doing
so will ensure that apps and digital services
run better. They are knowledgeable about the
potential benefits and will share data in
exchange for a good deal, proactive
recommendations or more seamless services
from the brands that they trust. Encourage
continued sharing with Enthused Explorers by
fulfilling Discovery needs and invitations to
exclusive experiences. While they are not
trendsetters, they act as validators to others
and are an important segment to develop.
The Willing Sharers
17%
of online sharers
4.2
Avg number of connected devices
49%
% of Sharers by Country
China
26%
US
19%
France
5%
Trendsetter
50%
Early Adopter
50%
"They can use my data…if not we go back to the
dark ages.“
Male Savvy Sophisticate, France, 36
Own a wearable device
Savvy Sophisticates willingly and proactively
share data with a broad range of digital apps
and services, recognizing this as an essential
element in exploring new opportunities and
experiences online. They actively seek out
ways to connect their digital activities and
enable more seamless integration and
productivity, valuing more relevant reminders,
content and ideas. They are highly informed
about what happens to their data and use this
knowledge to stay informed and remain
confident about the terms on which they are
sharing.
The Digital Consumer Needs Model
“Digital allows me to explore
the world around me”
EXPLORATION
FUN
TOGETHERNESS
STATUS
INTIMACY
ACHIEVEMENT
BALANCE
CONNECTION
“Digital lets me
focus on myself
as an individual”
PERFORMANCE
DISCOVERY
“Digital enables me
to have shared
experiences with
others”
ORDER
CONTROL
Digital helps me manage
internal needs
Microsoft’s digital needs model quantifies
motivations that drive digital behavior. The
model provides a map for marketers and
technologists as they develop tools, content
and experiences for consumers across digital
devices and platforms. We applied the
Needs framework to identify experiences that
consumers were more likely to engage with
using data.
The model establishes two dimensions in
which digital experiences orient. On one axis,
people move between exploring their
external world versus controlling their
internal emotions. However, they also move
between a focus on themselves as individuals
versus a need to connect with others and
share experiences.
Each of these four dimension establishes
areas of engagement and illuminates eight
different need-states (next page):
 Digital as External Exploration
 Digital as Internal Control
 Digital as Individual Performance
 Digital as Shared Connection
In order to highlight brand opportunities, we
use the lens of the Needs Model to unpack
how each of the trends can be activated. By
focusing on the right need-states, brands can
better serve up what people are seeking
from digital experiences.
For more detail on our Digital Needs Model,
read the whitepaper on
advertising.microsoft.com/research (coming
July 2015).
EXPLORATION
CONTROL
“Digital allows me to
explore the world around
me”
“Digital helps me manage
my internal needs”
DISCOVERY
BALANCE
Searching for new experiences
Seeking equilibrium
Top digital activities: get new ideas
about experiences or products
Top digital activities: music,
streaming content
FUN
ORDER
Looking for pure entertainment
Managing uncertainty
Top digital activities: gaming, short
videos/clips
Top digital activities: online
banking, weather
PERFORMANCE
CONNECTION
“Digital lets me focus on
myself as an individual”
“Digital enables me to have
shared experiences”
STATUS
TOGETHERNESS
Cultivating external image
Feeling part of a bigger whole
Top digital activities: posting
updates on activities
Top digital activities: sharing
opinions
ACHIEVEMENT
INTIMACY
Aiming for personal best
Deepening relationships
Top digital activities: reading about
/recording activities
Top digital activities: email , text,
video calls
Microsoft
Consumer
Insights
While many tech and media companies conduct market research that describes what
consumers are doing, the Microsoft Advertising Consumer Insights team believes
innovation stems from getting to the why. As a result, we take a consumer-centric
approach. We go beyond behavior to focus on why consumers do what they do—
whether that’s choosing one brand over another, or exhibiting a preference for a specific
platform. Our goal is to humanize digital behavior and motivation, enabling brands and
agencies to put consumer needs at the center of their marketing strategies.
Contacts
Natasha Hritzuk
Sr. Director, Head of Global Consumer Insights
[email protected]
Ivy Esquero
Senior Consumer Insights Manager, (Study Lead)
[email protected]
Kelly Jones
Head of Thought Leadership
[email protected]
Esther Burke
Consumer Insights Manager
[email protected]
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Some examples are for illustration only and are fictitious. No real association is intended or inferred.
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