Customer in control


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Privacy, threat or opportunity? , Barcelona February 2012

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Customer in control

  1. 1. Customer in Control – User Insights and concepts.Company name00.00.2011
  2. 2. Privacy: Il buono, il brutto, il cattivo Angel Eyes, the bad Tuco, The Ugly Blondie The GoodÁrea 2Company Name
  3. 3. Index The opportunity of (private) data01 User is the key: some customer research findings0203 1 questions on value 2 examples of what we are doing …04 A final thought05
  4. 4. 01The opportunity of(private) data
  5. 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 differentiatorÁrea 5Company Name
  6. 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 6Company Name
  7. 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 New York Times the: European Commission’s vice president for justice, Viviane Reding, said in a recent telephone interviewÁrea 7Company Name
  8. 8. 02User is the key: customerresearch findings
  9. 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 themÁrea 9Company Name
  10. 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 Givingcontrol and transparencyÁrea 10Company Name
  11. 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 levelÁrea 11Company Name
  12. 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, indeedÁrea 12Company Name
  13. 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 exchangeÁrea 13Company Name
  14. 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 reputationÁrea 14Company Name
  15. 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 15Company Name
  16. 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 16Company Name
  17. 17. 03Value?
  18. 18. Is there life beyond advertising? Information Market Gamification Storage / Vaults Reputation Protection Sell Raw / Aggregated DataÁrea 18Company Name
  19. 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 1.97 118.7Área 19Company Name
  20. 20. 042 modest proposals
  21. 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 21Company Name
  22. 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 impactÁrea 22Company Name
  23. 23. 05A final thought
  24. 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 24Company Name
  25. 25. Área 25Company Name