Onder presenting at Peppers and Rogers Managed Analytics Webinar on How Analytics Can Help You Weather the Economic Storm

1. Have You Looked at
Your Data Lately?
How Analytics Can Help You
Weather the Economic Storm
Wednesday, January 28, 2009
11:30 AM Eastern, 8:30 AM Pacific
©2009 Peppers & Rogers Group. All rights reserved.
1to1® is a registered trademark of Peppers & Rogers Group.

2. Have You Looked at
Your Data Lately?
How Analytics Can Help You
Weather the Economic Storm
Don Peppers
Founding Partner
©2009 Peppers & Rogers Group. All rights reserved.
1to1® is a registered trademark of Peppers & Rogers Group.

3. Have You Looked at
Your Data Lately?
How Analytics Can Help You Weather the Economic Storm
Hamit Hamutcu, Partner
Daniel Esterhuizen
Sr. Mgr Customer Analytics
Onder Oguzhan, Partner
©2009 Peppers & Rogers Group. All rights reserved.
1to1® is a registered trademark of Peppers & Rogers Group.

4. Today’s agenda
Topics of Discussion
 Why treating different customers differently requires
competent analytics capabilities
 What is required to build and operate a capable
analytics function
 How Telkom SA uses analytics for its customer-
centricity program
 Four challenges Telkom SA faced
Q&A
Survey
4

5. The business revolution in four words:
Treating different
customers differently
5

6. Customers are different in two ways
 They need different things from you
 They have different values to you
 Actual value – current customer LTV
 Potential value – LTV if customer behaved
in an ideal way
6

7. What are a customer’s “needs”?
 Generic needs include wants, preferences, desires
 Fundamentally different from demographics
 We have some needs in common with others
 Therefore, needs are sometimes predictable
 Some needs are truly personal and unique
 Needs can be situational in nature
 Some needs change over time
 Needs frequently do link to a customer’s value
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8. Analytics: vision and expertise
Treating different
customers differently
High
Analysis /
Modeling
Analytics
Expertise Data
control
Investment Derive
Data d
Values
Decision Clustering
Strategy Customer
Data
Roadmap CDR Mart
Unificatio
Billing
n
System
Low High
Analytics Vision
8

9. Analytics drives long-term
competitive advantage
Competitive
Re-align
Advantage
and Re-tune
Continuous enhancement
Execution of analytic prowess and
decision support capability
are critical in gaining and
Analysis maintaining long term
competitive advantage.
Data
Strategy
Roadmap
Time
Evolution Of Analytics Capabilities
Major drivers of success are
Organization: data-driven, solution-oriented
Capabilities: continuously improving, relying on internal and external resources.
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10. Process should follow a cyclical path &
provide continuous improvement and innovation
Internal
Changing Market Conditions
and Customer Preferences Dynamics
10

11. Managing customer analysis
and advanced analytics
Analytics Skills Cost effectiveness Interconnectivity
Tighter competition
Integration of a
and investor
Skills shortage in analysts
remote high-skilled
scrutiny leads to
and raising costs
low-cost workforce
more concise cost
considerations
A growing number of business executives are looking for more outside help with
customer analysis and advanced analytics
11

12. Out-Sourcing and In-Sourcing Compared
Venue Benefits Challenges
 Expertise can be hard to
In-house 1, Stability
find locally
2. Control
 May require long ramp-up period
 High resource management costs
 Requires special
management practices
 Insufficient knowledge about
Out-source 1. Broad range of
analytics business may cause inefficiencies
2. Often provides cost  Project based engagements
efficiency require ramp-up period
3. Scalability
 Communication effectiveness,
4. Longer work hour data security and time zones
 Resource turnover
12

13. Right-Sourcing Strikes the Right Balance
Customer Service Excellence
Continuously
Improved CRM
through Right-
Sourcing
Superior Customer Analytics
and Marketing
Infrastructure Strategy Execution
Right-Sourcing:
 Best internal talent, combined with
 Value-added consulting services, and
 Cost-effective outsourcing processes
13

14. Telkom South Africa
 More than 2,5 million customers, operating primarily
in South Africa
 Public company, market cap about $6 billion (US)
 Telkom aims to be Africa’s preferred ICT solutions
provider
 Building a fixed-wireless and mobile data network to
exploit fixed and mobile integration
14

15. Analyzing customer needs,
behavior and value
Customers differ with respect to why and how they use telecommunication services, and how much
value they bring to the operator. Customers using the same services may have totally different needs,
while customers with similar values might be using totally different services
Behavior
drives generates
Needs Value
Customer
Needs Dimension Behavior Dimension Value Dimension
The motive and need behind Service ownership of customers Value the customer brings to the
interest in telecommunications and their behavior when using the business
services services
15

16. Macro and micro segmentation
Macro Level Segmentation (Alignment) Micro Level Segmentation (Flexibility)
Value Based Segmentation Value, Needs & Behavior Based Segmentation
• Builds strategies and actions
• Builds ownership and org. model
• Serves the business needs of each department, using specific
• Common understanding of business
Purpose
characteristics of the customers of importance to departments
priorities across departments
• To the point and refined view on the customers for fine-tuned execution
• Integrated and aligned sales, service
of sales, service and operations
and operations from customers view
• Should serve specific departments
• Should serve all departments
• Should not necessarily be communicated to parties outside the
• Should be easy to communicate to:
• Customers department
• Employees
Marketing Micro Segments
VIP Corp.
Value
Large
High Integrated
Sample
Needs
Enter.
Value
Behavior
Young and Active
SMS Chatters
Medium
SME
Value
Handy-Holics
Social Butterflies
Low Value SOHO
Future High Value Youth
16

17. Customer segmentation
project at Telkom SA
• Customer value measured
Competitive • CPM, campaign
Advantage management and loyalty
programs are enabled
• Foundation of an organizational
level segmentation
Customer Portfolio Campaign Organizational
• Analyzing different customer Management for Management Change
Mass & Enterprise markets
patterns and clustering customers
according to their value, needs
and behavior Loyalty Customer 1-to-1 Marketing
Program Profitability
• Identifying churn risk of customers
• Customer information
spread accross different
systems is consolidated

Take-off
Data
control
Customer
Derive
d
Data
Values
CDR Mart
Clustering
Unification
Billing
System
Analysis
Preparations
Time
Evolution Of The Analytical Capabilities
17

18. Advanced analytical techniques
 Clustering: Clustering is used at
macro and micro segmentation for
I V IV
various purposes.
II
 Factor Analysis: Factor analysis is
used at needs segmentation.
III
 Decision Tree: Golden questions
at needs segmentation are
identified by using decision trees.
 Regression: Potential value,
revenue trend calculation, etc.
utilized regression.
 Extrapolation: Needs segment
assignment to customers was done
by extrapolation after needs
segments were identified by
analyzing market research output.
18

19. Segmentation study in redesign of
organizational structure
► Organization: Telkom currently is aiming
to better align itself against customer
value and potential.
► Strategy: Telkom is aiming to
“Treat Telkom customers
differently”.
► Targeted Promotions: Segmentation will become
the basis for targeted promotions as it reveals
comprehensive and actionable insight within
Telkom customer base.
19

20. Challenges faced by Telkom SA
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Product centric culture
 No clear organizational ownership
20

21. Adding analytical capabilities
 Identify requirements for a stable customer
analytics environment with a “Data Strategy
Project”
 Prepare a Telkom business plan in order to
purchase necessary equipment
 Gain approval for business plan from individual
Telkom business units
 Establish customer data mart with the new
equipment
21

22. Limited technical analytic capabilities
22

23. Challenges faced by Telkom SA
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Product centric culture
 No clear organizational ownership
23

24. Inconsistent data from different sources
 Identify data sources that
needs to be used based
on fields required for
customer analytics study
 Cover as many data
sources as possible Challenges
 Identify available fields in
those data sources that
can be used to create
customer analytics data
mart
24

25. Challenges faced by Telkom
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Product centric culture
 No clear organizational ownership
25

26. Telkom SA’s product centric culture
 Conduct several workshops with different units to
explain benefits and uses of segment centric
approach and how customer analytics is
performed. Aim was to increase awareness on
customer analytics.
 Share best practices and direct link to corporate
strategy
26

27. Challenges faced by Telkom
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Product centric culture
 No clear organizational ownership
27

28. No clear organizational ownership
Establish the internal customer analytics team,
which will take over completed analytical
infrastructure:
 Specify job requirements of the customer
analytics team members
 Interview with candidates and hiring most
appropriate one
 Buy data mining tool
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