1. Dr. Richard Benjamins Group Director BI & Big Data Telefonica Big Data – From Hype to Reality Telefonica © 2014

2. 2 Telefonica Overview What & Why of Big Data Opportunities of Big Data Privacy challenge Example application: Smart Steps

3. 3 Telefonica What’s the big deal with Big Data? McKinsey Big Data McKinsey Big Deals

4. 4 Telefonica Big Data is a hype

5. 5 Telefonica But what is Big Data? Dave Feinleib, Forbes blog 1.Big Data is Only About Massive Data Volume 2.Big Data Means Hadoop 3.Big Data Means Unstructured Data 4.Big Data is for Social Media Feeds and Sentiment Analysis 5.NoSQL means No SQL

6. 6 Telefonica Where does all the hype come from? Google started it, Yahoo open sourced it, Facebook and others used it, but McKinsey’s report took it to Fortune500 Board meetings… Today, huge marketing budgets are being thrown at those two words, driven by new business… no wonder all the noise! 2004: Google publishes Map Reduce paper (link: here)here 2006: Yahoo’s Doug Cutting open sources Hadoop out of his older search engine project Nutch. (Link: here)here 2011: McKinsey Global Institute publishes report on Big Data’s market potential for business, reaching out of the tech. world (link: here)here

7. 7 Telefonica Where is Big Data coming from? Type of Big Data OTT/TelcoCost of data collection By product/ seeking Batch/real- time Differential? Social mediaOTTLowActiveBothNo Web logsBothLowPassiveBothNo Network data (telco) TelcoHighPassiveBothYes M2M (sensor) data BothHighActiveBothMight Open dataOTTLowBothBatchNo Transact. dataBothMediumPassiveBothNo

8. 8 Telefonica PI EconomyExamples of external useInternal use Several business opportunities with (big) data Different “business” models with different maturities and different risks Leverage data to understand and improve business (x/up sell, churn) and products Data = improved business Recognize that digital data is delicate (privacy) Turn that into an opportunity Data = risk = business Insights that help improve businesses and governments Data = business Leverage data for targeting users with relevant ads and higher CTR and conversion Data = better advertising M2M Smart cities Improve services Advertising Access to insights Become a gatekeeper of personal data

9. 9 Telefonica But Big Data is also good for society and environment H1N1 virus pandemic Telefonica used mobile data to measure the spread of a global epidemic (“swine flu”) in Mexico DF To understand more about human mobility and the spread of epidemics through society, Telefónica Digital’s research team used anonymised and aggregated mobile phone call records to measure numbers of people visiting locations such as airports or universities. The study found successful Mexican Government’s decision to shut down key infrastructures, reducing virus propagation by 10%. 2012 Earthquake in Mexico Dimensioning emergency services in advance for an optimal response to natural disaster situations After the magnitude 7.4 earthquake in Mexico DF, Telefonica researchers captured modile data records that once anonymized and aggregated allowed building visualizations of the density of calls in the differents part of the city, immediately depicting the areas most affected by the earthquake. With Big Data tools like this, it would be possible for authorities to better anticipate contingency plans, dimensioning emergency services and placing them in those points where there is evidence that will be mostly needed in case of catastrophic events. (Click images for more)

10. 10 Telefonica Privacy remains an issue

11. 11 Telefonica There is increasing awareness of what customer data companies store 11

12. 12 Telefonica The industry is learning by doing

13. 13 Telefonica Are you aware where your data is going?

14. 14 Telefonica To the US … Europe’s leading analytics companies call upon European Institutions to replace Google Analytics

15. 15 Telefonica....made better Big decisions….. 1st product – “Smart Steps” for Retailers: Decide on store location Understanding store performance vs footfall Plan local marketing campaigns and track their impact Optimise resource planning – staffing/open hours Smart steps, for retailers

16. 16 Telefonica Retailers have questions... I know the activity that goes on inside my stores. But what % of my target market is walking past outside? What is the opportunity that I am missing? I am a large supermarket owner and one of my competitors has opened up down the road. I need to identify our battleground. Where is my competitor strongest and weakest? Where should I locate my new store? Where should I target loyalty or acquisition marketing campaigns? Where are my customers coming from? I need to manage my resources. When are my peak times? Could I be operationally more effective if I changed my opening times? Strategic Decisions Performance Management Retailers worry about …

17. 17 Telefonica Case study with 4 th largest UK food retailer “Unlike some of our competitors, we don’t have a store card to tell us who our customers are, and how they shop our stores, which means we’re at a disadvantage in targeted marketing. Over-rewarding one loyal customer disadvantages us in investing in the next” 400 stores nation wide Crawford Davidson: Customer Director at Morrisons Supermarkets: “This increase in customers was achieved without any reduction in customer spend, and with an improved new customer activation rate. Overall there was a 150% increase in the amount of new or reactivated customers who visited Morrisons stores. This is a fantastic result.” “Smart Steps identified many more suitable target post code sectors, enabling us to send promotional coupons to double the number of households”

18. 18 Telefonica 39 % 39 2G Network 3G Network 900 MHz 1800 MHz 2100 MHz 2013 4G Network NETWORK DATA The o2 mobile network has hundreds of cells to measure the trends in footfall across the country

19. 19 Telefonica PRIVACY ANONYMISATION Before Telefonica Dynamic Insights (TDI) receives the data, all personal information is removed. The data TDI receives are cryptographically hashed values AGGREGATION The hashed values are aggregated into groups, i.e. gender & age band. At this stage there are only crowds of o2 customers EXTRAPOLATION We take our sample and extrapolate to population totals, using mathematical algorithms. This gives us the grouped values Smart Steps uses. A 3 step process

20. 20 Telefonica 39 % 39 Easier to use Further protecting anonymity Extrapolated to represent local population 200 x 200 GRID Footfall is rendered into 200 x 200 metre grid squares across the country

21. 21 Telefonica Example question of a marketer COUNT What are the profiles of the people in the area of my store? How does the footfall in our area change throughout the day?

22. 22 Telefonica Differential aspect Export data and combine with other sources Today’s data tomorrow. Fastest data delivery in the market Insights 24/7/365. Data every hour, day, week and month. You choose. Intuitive web tool covering the whole of the UK to draw insights from Eliminates retailers’ blind spots. The profile of the footfall in their area Vast sample base based on observed crowd behaviour

24. 24 Telefonica And what about the Semantic Web and Data?

25. 25 Telefonica Semantic web and data trends

26. 26 Telefonica Semantic Web and Gartner’s Hype Cycles

27. 27 Telefonica 2006 – 5 to 10 years for reaching mainstream

28. 28 Telefonica 2009 – more than 10 years to go

29. 29 Telefonica 2012 – more than 10 years to go