Privacy, threat or opportunity?, Barcelona February 2012

1. Customer in Control –
User Insights and
concepts.
Company name
00.00.2011

2. Privacy: Il buono, il brutto, il cattivo
Angel Eyes, the bad
Tuco, The Ugly
Blondie
The Good
Área
2
Company Name

3. Index
The opportunity of (private) data
01
User is the key: some customer research findings
02
03
1 questions on value
2 examples of what we are doing …
04
A final thought
05

4. 01
The opportunity of
(private) data

5. 01 User data is an opportunity for Telefonica
In a Digital World Customer
Service data:
Data is the new Black Gold
Disclosed data
Entrusted data Network data is a unique telco
asset that must be leveraged to
Incidental data differentiate us from other players
Behavioural data The capability to refine huge
quantities of raw data will be the
Derived data
key differentiator
Área
5
Company Name

6. 01 Competitive landscape is rough
Type Examples Strengths Weaknesses
• Traditional •Nielsen • Customer • No Data
market •ComScore relationships • Weak Big Data
research orgs analytic skills
• Digital natives •Google • World leading • Data not (quite) as
• Analytics start- •Zynga analytics rich as telcos
ups •Ayasdi • Huge consumer
audience
• Incumbent •Telcos • Very rich data •Weak analytic skills
Data owners •Banks • Trusted brands
No one type of player completely dominates (yet)
Área
6
Company Name

7. 01 … and it won’t be easy…
Concerns related to the user privacy, suggest
that it should be approached with care …
(1) Gartner reveals top predictions for IT organizations and Users for 2012 http://www.gartner.com/it/page.jsp?id=1862714
(2) New York Times the: European Commission’s vice president for justice, Viviane Reding, said in a recent telephone interview
Área
7
Company Name

8. 02
User is the key: customer
research findings

9. 02 Gently persuading our customers to join…
Moving to a new world of
join in where 100% of
customers are “in” but
they have choices to
make about how their data
is used for their benefit
Take customers on a
journey to a new world in
which they can engage
with their data and
understand how we use
it to deliver better services
& experiences for them
Área
9
Company Name

10. 02 “Control and transparency” is what all people say
Virtuous circle…?
…while reducing churn
or reputation risks
Increase
acceptance of
Increase new ways of
user trust data sharing
Increase
awareness
Giving
control and transparency
Área
10
Company Name

11. So, shall we put users in the cockpit?
• Users don’t want to spend
time and effort protecting
their data
• It is cumbersome and
does not solve the
perceived problems
related to privacy and
security
• They expect the trusted
agent to provide it.
• Whenever unexpected
consequences
arise, users should be
able to understand them
and know what they
should do in order to
correct them, no matter
their skill level
Área
11
Company Name

12. 02 “Control and transparency” is not what people
actually mean…
Giving
control and transparency
Increase
awareness
Increase
perception
of risk …while putting loyalty or
Decreasing reputation at risk
users’ trust
A vicious circle, indeed
Área
12
Company Name

13. 03 It’s convenience, stupid!
Perception of risk can be overcome by a perception of high value
Identifying cause & effect is key to articulate the value of
exchanging data.
Cause & effect must be clear to the user so he/she can
recognize the value of personalized content
The willingness to give away information is the result of
the user balancing the perceived sensitivity of the data
shared, versus the perceived benefit obtained through
the exchange
Área
13
Company Name

14. 03
The risk – value trade off
User’s motivators and detractors when sharing data
More reluctant to share
More willing to share data when they perceive
data when they expect: a risk to:
• free or discounted services • personal or group intimacy
• faster delivery of service • economic welfare
• to increase social reputation • physical safety
• to socialize & connect • social reputation
Área
14
Company Name

15. 03 Users feel, think and act differently
An analysis of the variables suggests different behavioural patterns
 Need to exchange data (context, work, social).
 Frequency of use of digital services.
 Level of awareness.
 Perception of control.
 Type of reaction to threat/risk.
 Perception of risk.
 Level of media influence.
Those patterns led us to identify four
different profiles…
Área
15
Company Name

16. 03 Users feel, think and act differently.
CONNECTED BEGINNING DIGITAL LIFE
Not a long experience using digital
They are intensive users of digital services.
services most aware profile concerning
privacy and security in the digital world. Main services they use are social
networks and discount services.
They feel unsure about the
They feel in control and work on consequences and have no strategies to
reducing risks, but at the same time, they avoid problems or minimize risk, but they
accept the inherent risk of the digital ask for help when privacy or security
world could be compromised
CONVENTIONAL ENTERTAINMENT SEEKERS
No many skills and much experience in Focus their Internet activity on
digital world. watching videos and playing videogames.
Basic Internet use: checking their bank Little awareness and very carefree.
accounts or the email.
Their disregard about consequences
They use very primary protection make them to assume risky behaviors
strategies and need to help and not have and develop protection
them, conventional delegate complex strategies.
tasks to their helpers.
Área
16
Company Name

17. 03
Value?

18. Is there life beyond advertising?
Information
Market
Gamification
Storage / Vaults
Reputation
Protection
Sell Raw /
Aggregated Data
Área
18
Company Name

19. 04 Successful models are often complex
7% click-through
Rate Referrals
$0.25 to $1
User base Advertisers
Visitors Travel sites
120M $12M/month
35M unique per month
$0.83 per
Visitor
ARPU $350M
Paying user base $0.33/month Recruiters rev/year
Business
per user $20M/month Review contributors
(0.6% of total 3000 contributions subscription
customer base - Source: Linkedin Q earnings Source: HBS case study
Per day service with an
$30/month) annual fee of
Source: O2 as an information company $500 to $10,000
Users Customers Revenue Profit Market Cap ARPU User Value
(m) (m) ($B) ($B) ($B) ($/month) ($)
Telefonica 300 300 80.0 5.3 79.0 22.2 263.8
Facebook 845 ? 3,7 1.0 100.0 0.38 118.3
Google 1600 1 37.9 9.7 190.0 1.97 118.7
Área
19
Company Name

20. 04
2 modest proposals

21. 05 Social Proximity measure for P2P transactions…
1
Joe is selling his car and
has published it on a portal,
David is interested in
buying it, and wants to
know his trust level with
Joe
David SOCIAL
CDRs PROXIMITY
MJ ENABLER
Joe SNs
Kerstin
Others Trust level
79%
3
2 Thanks to SPE, David
discovers that he has a
SPE discovers the
David friend in common with Joe, Trust Path
different paths that MJ Joe
who is MJ, and that their
join David and Joe social proximity (Trust level)
within the Global is very close (79%).
Graph. It returns the David Kerstin Joe David MJ Joe
shortest one.
Área
21
Company Name

22. 05 Data Brokerage: IAMMY
How to become the trustees of our customer’s data?
• Data brokerage is a tangible trend in the market. Still, evidence shows that it
is a market full of uncertainties but open to many opportunities
Users are not capable of assuming the role of
actively negotiate data.
Big companies are debating but not acting
upon this
IAMMY
PDL players have 2 clear weaknesses:
«I AM MY DATA» impact and data
PDL and gamification combination not much
exploited: known ones are having a big impact
Área
22
Company Name

23. 05
A final thought

24. 05
“Give me six lines
written by the hand of
the most honest man, I
would find something in
them to hang him.“
(Cardinal Richelieu)
Área
24
Company Name

25. Área
25
Company Name