Warid Telecom Uganda implemented a big data analytics solution to increase revenue and offer new services. The solution involved segmenting customers based on usage patterns and launching targeted campaigns. This led to dramatic results like doubling data revenues, increasing ARPU by 35%, and reducing churn by over 20%. The big data platform provided insights, recommendations, and allowed for closed-loop and real-time marketing.

1. Warid Telecom Uganda
Increasing Revenue and New
Services through Big Data
0

2. Agenda
• Big data – brief definition
• Uganda Market
• Warid Challenges
• Solution and Approach
• Segmentation
• Key Campaigns
• Dramatic results
• Enabling the Transformation through Big Data Analytics
1

3. Big Data – Definition by IDC
2
Data collected is
more than 100TB
Data is received
via ultra-high
speed streaming
Data generated
is growing at
>60% per year
Deployed on
scale-out
infrastructure
Two or more
data formats
and/or sources
High-speed
streaming data
Source:IDC, 2012
Big Data
Technology
Variety
Velocity
Volume Value

4. Current Applications of Big Data
3
Analysis ranked High, Medium, Low based on relevance to telecom business requirements
Analysis Types High Medium Low
Recommendation Engine
Network Monitoring
Sentiment Analysis
Fraud Detection
Risk Modeling
Customer Experience Analytics
Marketing Campaign Analysis
Customer Churn Analysis
Social Graph Analysis

5. Uganda Market
• Unique demographics dominated by youth
– Population  ~35 Mn
– 49% of population < 14years
– Population growth rate  3.32% (4th fastest growing in
the world)
• Pre-paid dominated telecom market
– 6 Operators  MTN, Warid, Airtel, Orange, UTL, Smile
– Mobile Penetration  45%
– Predominantly a Prepaid market – Weekly/Daily
voice/data/SMS packs are popular.
– 2nd biggest mobile money market
– Compulsory SIM registration
– Multi SIM market
4

6. Warid Uganda – The Youth Brand
• Warid-the youth brand
– Launched GSM operations in 2008
– 3rd operator in Uganda and a new Entrant to the Market with 21% CMS
– Youth brand and Youngest super brand in Uganda
• Full service operations
– Voice, 3G Data, Enterprise Solutions, Mobile Commerce (Warid Pesa)
– Fastest growing Mobile Money Service – Warid Pesa
5

7. Critical Phases in Warid’s Growth Strategy
6
• Network enhancement
• Introduction of high
speed data network
Phase 1 Phase 2
• Strong brand building
Phase 3
• Big Data Analytics

8. Business Objectives
 Penetrate the market despite being a
late entrant
 Enhance reach to the primary target
segment
• Young audience with staggered
income levels
 Enhance yield per minute, caused by
• Lower tariffs set to meet
competition
• Higher % off-net calls
 Convert second simmers- who held
a large share
• Reduce cyclic usage-convert them
into primary users
• Attract, retain and grow revenues
among second simmers

9. Solution: Converting Second Simmers and Enhancing
Consumption through Big Data Analytics
• Creating a multi-phase campaign plan
– Generate interest and create usage
– Upsell and ensure conversion
• Leveraging the power of Big Data
– Usage Analysis to identify who need to be targeted
– Entice when the SIM is in the phone and the phone is ON
Time
ARPU
Phase 1: Usage
enhancement: Use
more from your
Warid SIM
Phase 2: Pack upselling to
ensure consistent usage
Phase 3: Retention offers
to avoid usage drop and
ensure high usage
Normal CLC
Usage drop

10. 3U Approach across Customer Lifecycle
Time
Customer Value
Usage
Uses
User
Retention campaigns
- Understanding early
indicators
- Retention offers
Usage drop analysis
Churn propensity analysis
Increase usage of range of products
- Conversion to primary SIM users
- Pack upselling through usage based
targeting
Usage based dynamic
segmentation
Usage enhancement
- Promotion through
contextual offers
Segmentation on age on network, weekly
sum of recharge

11. Approach to Segmentation : Setting the Ground Work for
Base Management
• Sub Segmentation based on usage trend
• Trend Analysis based on data over 3 periods (Mo/Wk)
• Micro level Segmentation based on usage pattern & dominant/ preferred
usage leg and/or Recharge pattern and/or pack subscription
• Macro level based on CLV (ARPU v/s AON) Matrix
• Static – based on (M-1) data
Tier 2
Tier 1
Tier 3
• Three tier segmentation approach to classify subs as per their CLV & Usage
profile
• The combination of 3 levels of tags along with the Real time tracking used to
design segmented campaigns & offers

12. Campaigns that Lead to Dramatic Results
11
Churn management campaigns
to manage high churn rate in Multi
SIM environment
• Subscribers showed high Talk
time Loading to Depletion
Ratio (100:95)
Strategy: pick churn indicators
early
• Track Usage on Real Time
• Churn propensity identified
based on the frequency of
recharge and Balance to
depletion ratio
• Subs are segmented into n1xn2
matrix and packs promoted
accordingly
Result: Significant churn reduction
by more than 20%
Segmented campaigns to
target users with declining usage
Strategy: Promoted free on net
minutes on recharge of their
favourite pack
Takers were given follow up
offer of further free on net
minutes for recharging with
packs of lower denomination
Result: Significant Increase in
REC base adding to top line
revenues
Pack Subscription promotional
and informational campaigns
Pack Expiry notification
reminder campaigns
Result: Improved pack revenues
and On-net usage
Grace Management campaigns
targeting subscribers moving into
inactive stage
Result: Dramatic reduction in churn
Campaigns Targeting New
Acquisitions to the network
through welcome offers and baby
care offers
Result: Improved CSAT scores by
more than 10%
Special campaigns targeting
increase of specific legs of usage
like ILD, SMS and DATA Data Pack
Upsell campaigns
Result: Doubling of Data Revenues
after campaign execution

13. Dramatic Results
12
Increase in Data Revenues
200%
Increase in Gross Revenue
36%
Growth in unique On-net
pack users
36%
Increase in On-net revenues
90%
Increase in ARPU
35%
Increase in OG MoU
19%
Increase in daily REC base
25%

14. Partnering with Warid for delivering Economic Impact
Warid’s business
objectives
• Technology: Big Data
Analytics
• Tools: Closed-loop,
Integrated, Real-time
• Services: Impact driven
Marketing Consulting
Dramatic Results!!!
What Flytxt offered? What we achieved?

15. Big Data Analytics Technology Driven Solutions
Comm.GatewayBIReportsFulfillmentEngine
Customer Retention
SMSC
MMSCOBD
USSD
IN
Systems
E-top
Up
Subscription
G/W
Stream
data
Batch
data
Applications realize
Economic Value
ACTIONs
E.G – Yield Optimization,
Optimum Promos, Credit
Linked, Suspension, etc.
RECOMMENDATIONs
E.G – Best-fit Offers, Bad Debt
Lists, Purchase Intents, etc.
INSIGHTs
E.G – High Value, Credit-Risks,
Frequent Traveler, Purchase
Propensity.
KPIs
E.g.- MOU, Usage, AON,
ARPU, Location, etc.
Big Data Analytics Framework
Aggregation,
Correspondence
analysis,
Filtering,
Soft Clustering,
Social Net. models,
Statistical Classifiers,
Predictive modeling,
Time series analysis,
Variance analysis,
etc. etc.
Intent Management
Mobile Advertising
Granular Risk
Management
Granular Margin
Management
Revenue
Enhancement

16. Sample text Sample textSample text
Closed Loop, Integrated, Real-time Marketing Tools
IntegratedClosed-Loop
Real-time
 Segmentation
 Reward tracking
 Fulfillment
 Action Mgmt.
 Reporting
 Targeting
 Tracking
 Interactive
 Control Group
 Exclusion/Inclusion
 Data source
 Reward/fulfillment
 Subs touch point
 Comm. policy mgr.
 Solutions

17. Economic Impact focused Service Delivery
• Design focus to deliver economic value for telecom operators >10%.
• Horizontally scalable, to cover a broad spectrum across CXO domains in an operator.
• Combined Onsite + Offshore delivery model for standardized services with localization.
• Standardized services, personalized delivery with focus on agility
• Shared best practices, with strict privacy and anonymity of data and marketing strategies
• Designed to house and deliver the full spectrum of big data competencies
• Service flexible engagement models
• Value based Revenue shared
• Technology License models
• Configurable set of managed services
• Alone as well as joint with 3rd parties
• Proven across multiple countries
• Different cultures and languages
• Different legal & regulatory environments

18. Enabling BTL Campaigns the Right Way!
• Sniper Shot Segmentation with the Right Insights
• Pick the revenue churn indicators at Right Time
• Recommendation Engine : The Right Product from the plethora
• Act with the appropriate offer at the Right Trigger
• Engage with Subscriber through Right Channel
RIGHT INSIGHT RIGHT OFFER RIGHT TIME

19. For a Differentiated Customer Experience!
Personalised Less IntrusiveRelevant
Impacts overall operator revenues by 5-7%
depending on:
• Operator field practices & Sub
demographics.
• Campaign management tools & practices.
Offers need to be :

20. 19confidential© 2013 Flytxt. All rights reserved. 14 August 2013
Chandrachur Ghosh, CMCO, Flytxt
chandrachur.ghosh@flytxt.com
www.flytxt.com
Q&A
Shailendra Naidu, CCO, Warid Uganda
shailendra.naidu@waridtel.co.ug
www.waridtel.co.ug