Successful marketing with Big Data AnalyticsA use case from Asia

Johannes Bjelland, Pål SundsøyTelenor Group Research

Digital Winners, Fornebu 08.11.2013

Our customers generate an increasing amount of information in our systems

What’s in it for Telenor?

3

A number - Caller

IMSI: SIM cardCell_ID: Location

TAC: Handset

Type: Call, SMS, Data, etc

For each call, sms and data session: hundreds of data points are stored

Date & time

B number – Receiving party

Data volume

Boosting Mobile Internet uptake in Asia with prediction and SMS marketing

This Pilot was a collaboration with the Mobile Internet Asia project in Digital Services

Motivation

• For many in Asia, the mobile phone is their only gateway to the Web.

• Many customers have internet capable phones, but do not use them

• The business unit is using state of the art Below The Line marketing process

Selecting the right campaign target groups is key to maximize Campaign revenue

• 6000 yearly SMS campaigns effectively boost customer revenues

• Number of campaigns cannot be pushed further• Contact rules: Max 1 offer each 14 days• Efficiency of campaigns can be improved with a big

data approach

Customer attention is valuable and a limited resource!

5 10/04/2023

Machine Learning assists us in selecting optimal target customers from huge data sets

Data sources• Traffic usage data• Subscription data• Handset Features• Location• Handset switching • VAS usage

300 variables

40 000 000 customers

?Who are most profitable targets for SMS campaign

Its impossible for a human to relate to all these data (!)

The predictive model learns from existing cases of data conversion

Non-convertors‘Negatives’

Natural Data Convertors‘Positives’

2-6 months back: Use Historical data

Non Data Customers

today

Create modelFind patterns identifying the data convertors based on historic data

Model deploymentUse the patterns to identify likely adopters

Identify and Run Campaign on

200k most likely adopters

Today: Present time data

*Offers are 15 MB & 99 MB data packages offered for half-price

The prediction model outperforms existing best practice approach – 13 times better than best practice

P7 data pack P9 data pack0.00

1.00

2.00

3.00

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5.00

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7.006.42

3.76

0.500.70

PSPM

Microsegmentation

Hit

rate

15 MB Data Package 99 MB Data Package

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99% Renewal– the algorithm is optimized to avoid ‘freeriders’

Current best practice Microsegmentationapproach

Prediction Model

Telenor Data-Driven Development Using data for social good

• Use mobile phone data to Improve models for Infectious disease spread• Understand the spread of Dengue fever in Pakistan

• Collaboration with epidemiologists from Harvard School of Public Health

• Crisis and Disaster Management• Assessing mobility patterns and changes in economic behavior during the Cyclone Mahasen (May 2013).

• Goal: Improve efficiency of emergency aid measures

• Measuring Socio-economic state based on big data• Collaboration to be set up between UN Global Pulse, World Food Program and Telenor Group.

• Food security - food prices and availability

Detecting signals in the data

A ‘Big Data’ company is distinguished, not by how many terabytes it sits on, but by the way the company exploits the data in Business!

• Answering business questions via data mining and ad hoc analysis

• Using pilots and data driven marketing to let the customers tell us what they want

• Collaborating with world leading research environments within data science

• Petabytes is not a prerequisite - What we need is ‘BIG ENOUGH’ Data for business

Telenor is taking steps toward becoming a Big Data company