© 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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Performance is based on measurements and projections using standard IBM benchmarks in a

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Therefore, no assurance can be given that an individual user will achieve results similar to those stated

here.

Please Note:

2

Overview

• Introduction on Etisalat Engagement

• Monetization opportunities for Telco

• Research FOAK and Etisalat

• The Profile Hub Pilot

• Results and Current Work

2

Real Time Actions in the Cognitive Era

DECISIONSINSIGHTS OUTCOMES

MeasureResults

HistoricalData

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

SOCIALNETWORK

TROUBLE TICKETS BILLING

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 SUBSCRIBEREXPERIENCE

•Device •Usage•Customer type•Network •Service Experience

CUSTOMER PROFILE (INSIGHTS)

iPhone 5C

Congested 3G Cell

Heavy Netflix Users

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

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

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

IBM Research FOAK Engagement with Etisalat

• ProfileHUB: Enriched Consumer Profiles

• Monetization Examples

• Sample Demos

• Business Opportunities and Current Ongoing Work

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.

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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 Rulesfor Marketing

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

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

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

ServicesOutcomes

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

O-D Spatio-temporal Heatmap

SelectOrigin or

Destination

SelectTime-of-the-day

Heat map of origin and destinations

A 2nd side-by-sidemap to compare

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)

O-D Temporal Trip-Duration Histogram

SelectOrigin or

Destination

SelectTime-of-the-day A 2nd side-by-side

map to compare

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

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 optionLanguage

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

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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

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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”.

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Location Based Real-Time Targeted Campaigns

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

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

• 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.

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Uncovering Accurate Insights with Audience

Micro-Segmentation

Kids channel

Kids channel

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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