Session 2183 Profile hub - The Etisalat Story
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The document discusses the collaboration between Etisalat and IBM to create a 'Profile Hub' for enriching customer profiles utilizing big data and cognitive computing. It outlines the monetization opportunities for telecommunications companies, the pilot projects conducted, and insights into targeted advertising and customer segmentation. Key components include real-time analysis of subscriber data, location-based targeted campaigns, and the impact of enriched consumer profiles on service personalization.
Session 2183 Profile hub - The Etisalat Story
- 1. © 2015 IBM Corporation Session 2183: Creating and Monetizing a Customer Profile Hub – The Etisalat Story Mohamed Hashem, Director Analytics, Etisalat Ken Kralick, IBM Global Solution Executive - Big Data & Analytics Leader Dr. Sambit Sahu, IBM Research Dr. Arvind Sathi, IBM WW Analytics Architect - Communications Sector
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- 3. Overview • Introduction on Etisalat Engagement • Monetization opportunities for Telco • Research FOAK and Etisalat • The Profile Hub Pilot • Results and Current Work 2
- 4. Real Time Actions in the Cognitive Era DECISIONSINSIGHTS OUTCOMES Measure Results Historical Data SUBSCRIBER PROFILING & ENRICHMENT •Hangout •Location •Trends •Behavior •Lifestyle Gotham City Night Owls PREDICTIVE ANALYTICS (SCORES) Sports Fans Lunch Crowd KPI-DRIVEN ACTIONABLE INSIGHTS •NPS •Churn •Upsell •Cross- Sell BUSINESS DECISIONS Upgrade Phone Bad Device Low NPS Wrong Plan DATA SOURCE COLLECTION & EXTRACTION DATA / VALUE SOCIAL NETWORK TROUBLE TICKETSBILLING DEVICES APPs OPERATIONS TRANSFORMATION •Proactive Care •Enhanced Sales & Marketing •Fraud & Security •Revenue Assurance •Customer Data Location Monetization •New Business Models BUSINESS OUTCOMES Business Maturity INDIVIDUAL SUBSCRIBER EXPERIENCE •Device •Usage •Customer type •Network •Service Experience CUSTOMER PROFILE (INSIGHTS) iPhone 5C Congested 3G Cell Heavy Netflix Users
- 5. Background Interest in monetizing Telco data has increased with Telcos’ setting up organizations dedicated for this. Examples include: • Etisalat • StarHub • Qrious • PinSight Media+ The questions these Telcos’ are trying to address internally: • Who are my potential monetization customers and how many are there? • What will they be interested in? • How do I get the insights into something of value to these customer? • How will they get access to the data and how can I respect the privacy of my consumer customer and yet provide value to the enterprise customer? • How do I price this? • How much do I need to invest in this and what sort of returns am I getting? • How do I start small and test waters? Passenger Movement DataTourismLocal Government http://www.qrious.co.nz
- 6. What can CSPs monetize? • Dara • Location data and derived attributes • App and content usage data • Social networks • IoT data • Engagement services • Advertising • Apps • SMS • Orchestration / Business Services • Fraud detection • Marketing
- 7. 6 • IgnitionOne’s Q3 Digital Marketing Report said that Google’s display business dropped 19 percent from last year’s third quarter to this year’s, while Facebook’s share of display advertising spend increased by 40 percent. • With Facebook’s Custom Audiences product, advertisers upload a list of their existing customers from their CRM, then Facebook goes out and finds people with the same demographic and social characteristics. Facebook then delivers ads for the relevant products to these users’ desktop or mobile devices. Monetization Business Models – Custom Audiences from Facebook http://venturebeat.com/2015/10/22/why-google-is-getting-schooled-by-facebook-in-display-ads-and-what-its-doing-about-it/ https://www.facebook.com/business/success/little-passports https://www.facebook.com/business/a/custom-audiences
- 8. IBM Research FOAK Engagement with Etisalat • ProfileHUB: Enriched Consumer Profiles • Monetization Examples • Sample Demos • Business Opportunities and Current Ongoing Work
- 9. 8 Global Telco Operator Etisalat and IBM Research Join Forces to Deliver Personalized Mobile and IPTV Service • First-of-a-kind Project uses Cognitive Computing and Big Data Technologies to Transform the Customer Experience • ProfileHUB: First-Of-A-Kind (FOAK) project demonstrates – Creation of enriched customer segments using attributes derived from Mobile, IPTV, Browsing data, Social Media and Billing Data – Flexible business rule based approach towards customer segmentation • Data monetization demonstration and client pilots – Targeted advertisement delivery on OTT clients for VOD – Predicted location based campaigns • Data driven Audience measurement capability with enriched consumer profiles – Derived from location, web browsing, social and IPTV channel viewing data – Real-time Audience insight for Video streaming services Egyptian Nationality, Regular 9am – 5 pm worker. Interested in sports & entertainment, speaks Arabic/English. Home near Dubai Marina, shops in Dubai Marina Mall during weekdays. Goes to Dubai Mall during Weekends & spends more than 100 mins on average. He uses WhatsApp.
- 10. 9 From Raw Data to Inferred Attributes to Derived Customer Segments Inferred attribute Location Analytics URL AnalyticsIPTV Analytics Call Analytics Luxury Football Fan Travelers Youth Business Home, Work location, Nationality, Preferred Language, Income, Interests, Weekday & Weekend visits and time spent, travel frequency, top TV channels viewed, etc. 70-90% accuracy Billing Analytics Segmentation Rules for Marketing
- 11. 3. Location Based Real-Time Targeted Campaigns in Egypt Pilot: Send real-time promotions to people near a sports store if he/she is a sports lover. 2. Targeted Advertisement on IPTV based on location, web access and viewership data in UAE Pilot: Real-time targeted advertisement on IPTV based on consumer profile Profile HUB: From Raw Data to Inferred Attributes to Derived Customer Segments for Service Personalization 1. Sensing Country-scale People Movement from Telco Data and Application to Transit Pilot: Engaged with 6+ transit authorities and validated results with extreme accuracy 360 degree consumer portraits Example Pilot Engagements
- 12. 1. Sensing UAE Scale People Movement from Telco Data and Application to Smarter Transit and Planning • Derived from Anonymized and Aggregate tower level location data • Location Analytics for deriving UAE scale people movement models • Example models include Origin-Destination (O-D) matrices Time-of-day analysis Footfall analytics by segments Meaningful locations and Point of Interests
- 13. City in Motion – Understanding People Movement & Optimizing Services Network Data (millions of events/day) Transit System & GIS Data Census & Demographics Data Analytics & Models Information Sources Business Services Outcomes Time of Day Density Maps Origin-Destination Traffic Flow Planning Large Scale Events, Emergency Response Transit Planning Location-based Services, Traffic Alerts Reduce Congestion Reduce Journey Time Reduce Carbon footprint Reduce Emergency Response Time
- 14. O-D Spatio-temporal Heatmap Select Origin or Destination Select Time-of-the-day Heat map of origin and destinations A 2nd side-by-side map to compare
- 15. O-D Pair Arc Visualization at different hour-of- the-day Select “hour-of-the-day” Enter the threshold (say, n) for number of trajectories – Only OD pairs which have greater than ‘n’ are displayed OD Pairs displayed as arcs • An arc represent an O-D pair • Begins with green flat slope • Ends as red with sharp turn • Thickness is proportional to number of trajectories Select the date Select the type of the trips. Currently we support analyzing “all trips” only Select the week of Analysis (Ramadan or School Holidays)
- 16. O-D Temporal Trip-Duration Histogram Select Origin or Destination Select Time-of-the-day A 2nd side-by-side map to compare
- 17. Number and origin of daily visitors to top landmarks and segments • Number of people and origin of visitors to landmarks • Example: where visitors coming to Dubai Mall • Illustration
- 18. 17 Customer Profile Profile Hub 3 – Profile Hub catches the new football interest flag and realtime matches Walid’s profile with an offer for 20% off coupon to an Nike store. 4 - Walid is also an existing Etisalat SMS Opt-In mobile cust. 5 - Walid receives and SMS with a promo code for offer on his smartphone. 2 - Walid is channel surfing, mostly sports channels, primarily football games where Nike advertises a lot (FAP enhances his customer profile, after 10 football games viewed in 1st month, with an interest flag as a “football fan”) Enhanced Cust. Profile Interest / Mobile # / Email 1- Walid activates eLife TV service with the Arabic package and adds the Jazeera sports ala carte option (we have an initial customer profile with his fixed # and a mobile#) A la carte option Language Package walid@eim.ae 6 - Walid uses promo code in Nike Store to purchase a pair of Nike football shoes. 2. Monetization Use Case: Targeted Ads over IPTV
- 19. 18 Enriched Consumer Profile from Location, Web and IPTV data for Targeted Campaigns -Real-time targeted advertisement on IPTV based on consumer profiles -Potential of power of micro-segmentation
- 20. 19 19 4 – Profile Hub catches that Mariam is entering a mall, and matches her “Fashion” interest flag and “Perfume” preference, realtime with an offer for 20% off coupon for Byonce fragrance at Sephora in that mall. 5 – Mariam receives an SMS/email/App notification that her mWallet account contains a new offer for Beyonce perfume. 2 - She follows a friend’s post on FB and clicks the Like button on the Beyonce Fan Page. 6 – Mariam uses Etisalat App on her smartphone to purchase some perfume at POS via NFC. 1- Mariam is a mobile subscriber, has Etisalat app and agrees to receive offers related to her interests. Profile Hub Customer Profile Enhanced Cust. Profile Interest & Preference IPTV a la carte option & Mobile Features/AppsIPTV & Mobile Pkg 3. Monetization Use Case: Real time & Targeted offers over Mobile Beyonce Fan Page 3 - Mariam IPTV viewing & mobile clickstream behaviors set her Interest flag to “Fashion” and one preference to “Perfume”.
- 21. 20 Location Based Real-Time Targeted Campaigns
- 22. ProfileHUB for M&E: Real-Time Audience Insights for OTT/TVE Video Streaming (Follow-up ongoing Work) • ProfileHUB for providing real-time Audience Insights capability at scale for OTT/TVE Video streaming services to enable a wide variety of service personalization and data monetization opportunities Real-time dashboard for measuring and understanding audience segments Recommendations and personalization to several systems in order to optimize various business objectives (content recommendations, targeted ad insertions, QOE/QOS optimization, etc). • A data driven approach towards creation of user profiles and insights based on User generated video viewing events Leveraging social media and other third party data source to support enriched profiling of users
- 23. Real-Time Audience Insights Platform • xx • Reactive scalable platform for both batch and real-time audience insights • API based models for quicker integration with a wide variety of OTT/TVE Video Streaming platforms
- 24. • Inferred nationality and ethnicity through Mobile and IPTV data • Segmented top channels by Arabic and Hindi speaking populations. • Uncovering Accurate Actionable Insights • While Kids channel is highest viewership at an aggregate level, ethnicity based segments showed that Kids channel is not the highest rating channel among Arabic and Hindi speaking population segments. • In a multi-ethnic environment, micro-segmentation could uncover accurate, and more actionable insights for improved targeted advertisement. 23 Uncovering Accurate Insights with Audience Micro-Segmentation Kids channel Kids channel
- 25. Overview • Introduction on Etisalat Engagement • Monetization opportunities for Telco • Research FOAK and Etisalat • The Profile Hub Pilot • Results and Current Work 24
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