Have You Looked at
Your Data Lately?
How Analytics Can Help You
Weather the Economic Storm
W...
Have You Looked at
Your Data Lately?
How Analytics Can Help You
Weather the Economic Storm
...
Have You Looked at
Your Data Lately?
How Analytics Can Help You Weather the Economic Storm
...
Today’s agenda
Topics of Discussion
 Why treating different customers differently requires
competent analytics ca...
The business revolution in four words:
Treating different
customers differently
...
Customers are different in two ways
 They need different things from you
 They have different values to you
 Actua...
What are a customer’s “needs”?
 Generic needs include wants, preferences, desires
 Fundamentally different from demogr...
Analytics: vision and expertise
...
Analytics drives long-term
competitive advantage
Competitive
Re-align
Ad...
Process should follow a cyclical path &
provide continuous improvement and innovation
I...
Managing customer analysis
and advanced analytics
Analytics Skills Cost effectiveness Interconn...
Out-Sourcing and In-Sourcing Compared
Venue Benefits Challenges
...
Right-Sourcing Strikes the Right Balance
Customer Service Excellence
...
Telkom South Africa
 More than 2,5 million customers, operating primarily
in South Africa
 Public company, market ca...
Analyzing customer needs,
behavior and value
Customers differ with respect to why and how they use telecommunication ser...
Macro and micro segmentation
Macro Level Segmentation (Alignment) Micro Level Segmentati...
Customer segmentation
project at Telkom SA
...
Advanced analytical techniques
 Clustering: Clustering is used at
...
Segmentation study in redesign of
organizational structure
► Organization: Telkom currentl...
Challenges faced by Telkom SA
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Prod...
Adding analytical capabilities
 Identify requirements for a stable customer
analytics environment with a “Data Strate...
Limited technical analytic capabilities
22
Challenges faced by Telkom SA
 Limited technical analytic capabilities
 Inconsistent data from different sources
 ...
Inconsistent data from different sources
 Identify data sources that
needs to be used based
on fields required for
...
Challenges faced by Telkom
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Produc...
Telkom SA’s product centric culture
 Conduct several workshops with different units to
explain benefits and uses of ...
Challenges faced by Telkom
 Limited technical analytic capabilities
 Inconsistent data from different sources
 Produc...
No clear organizational ownership
Establish the internal customer analytics team,
which will take over completed analyt...
of 28

How can Analytics help you?

Onder presenting at Peppers and Rogers Managed Analytics Webinar on How Analytics Can Help You Weather the Economic Storm
Published on: Mar 4, 2016
Published in: Technology      Business      
Source: www.slideshare.net


Transcripts - How can Analytics help you?

  • 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 7
  • 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. 9
  • 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 28

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