Customer Retention Through Analytics

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Customer Retention Through Analytics

• Paul King, President COO
• Aperio CI
• September 18, 2008

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Economic Pressures Require Service Providers to
Realize New Revenue Streams

• Churn is increasing
• While ARPU is declining
• Revenue and profits are squeezed
• Customers demand more and better service
• While brand loyalty becomes minimized

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Acquisition-centric Has Economic Challenges

• Pressure to reduce Capex and Opex
• Doing More With Less is a mantra heard
  world-wide by network operators
• IT constraints
• Internal Systems are over-taxed
• Requirement to spend marketing monies effectively
• Outspending the competition is no longer an
  option Providers demand tangible ROI
• Building brand loyalty is a necessity

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Operators Respond to Market Conditions

• Significant, and continuing, investments in CRM
  systems, practices, procedures and segmentation
  strategies to improve customer service and
  quality of offers
• Intense focus on churn propensity and market
  segmentation models to help address loyalty and
  reward programs
• Every mobile operator is looking for
  differentiators, but finding them is proving
  difficult, complex and expensive
• Content
• Data Services
• Devices

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Operators Respond to Market Conditions

• Frequent price reductions and increased bundles
  are utilized in complicated, and in many cases,
  less than optimal ways, to both attract and
  retain customers.
• Front-loaded promotions (handset subsidies,
  additional free minutes, etc) exacerbate profit
  dilution and reinforce more for less customer
  expectations.
• Complicated plans invite customer skepticism of
  pricing strategies, practices, policies and
  execution methods.

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Truths About Retention

• It is more cost effective to retain a customer
  than it is to acquire a new one.
• The presentation of the right offer at the
  right time and via the right method can only
  be enacted if the customers usage and history
  are analyzed in detail.
• To create the required offer necessitates
  analysis of usage data such as
• Account information
• Billing data
• Customer history

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A Different Approach

• Using Existing Customer Data To Break The Cycle
• Increasing ARPU
• Better Up- and Cross-sell Opportunities
• Enhanced Customer Satisfaction
• Improved Profitability

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Effective Use of Customer Data

• The Basic Tenets
• Operational proficiency
• Consistently accurate
• Timeliness
• Flexibility
• In order to provide profit-focused decision
  making, intelligence, and delivery systems must
  be tailored to meet each customers specific
  needs.

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Required Data Functions

• Software-based data analytics
• Gather, mine, and categorize billing records
  tightly woven with current user information
• Customer history
• Calling pattern analysis
• Competitive price positioning
• Bundling analysis
• Loyalty and reward history
• Competitor offerings
• Social Network indicators

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Required Data Functions

• Expert interpretation and analysis
• Cross-referencing critical identifiers
• Behavior changes
• Patterns of promotions
• Take-up rates
• Rewards and sales
• --Identify patterns and trends that accurately
  forecast customer behavior trends

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Required Data Functions

• Tailored, near real-time delivery
• Well-defined, fast and flexible execution
  processes
• Integrated offer delivery and reporting that
  works across all customer channels (fully
  integrated marketing)
• Contact center
• Web portal
• Text message
• Voice mail
• Direct mail
• Email

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Imperatives for Successful Execution

• To execute effective loyalty programs, there are
  fundamental bits of knowledge that you need to
  know
• Know your customer
• Who are they right now, at this moment?
• What tariff are they on? What handset do they
  have? (Do we know?) What options, bundles and
  services do they have?
• How do they actually use our products and
  services? (As opposed to what they have
  purchased from you.)
• Who do they callwhenhow often?

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Imperatives for Successful Execution

• Propensities, preferred method of
  communications, applied loyalty and reward
  offers
• What has worked before? Will it work now?
• How much theyve spent (basic LTV)
• Tenure and contract status (where applicable)
• How do they actually use your products? as
  opposed to what they have purchased from you

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Imperatives for Successful Execution

• Know your product
• Know the tariffs, handset, offer and
  product/service positioning in detail
• How do they fit within our product and service
  portfolio?
• How are they positioned relative to competitor
  portfolios and programs?
• Know whether or not the proposed product,
  service, or reward is useful to that particular
  customer based upon factoring all critical
  attributes.

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Imperatives for Successful Execution

• Know how your customer fits your products
• Assess all possible options, apply only what
  fits, when it fits and the channel by which the
  customer prefers to communicate
• This is where the rubber meets the road!

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Execution Requirements

• End-to-end delivery requires
• Systems and hardware
• Software applications
• Integrated access and delivery
• People and expertise
• Security
• Quality assurance
• ProcessProcessand did we mention?Process
• .. to meet customers specific preferences and
  needs.

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Analytics in ActionA Quick Case Study

• Large Western European Mobile Operator
• Challenge
• Saturated market
• Commoditized pricing
• Multiple plans bundles for voice/data
• High annual churn rate32

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The Analysis Highlights

• High annual churn rate 32 overall
• 73 of customers not on optimal plan
• Customers spending 30 or more above optimal
  plan churned at more than 60 per year!!
• Customers spending close to lowest priced
  churned at less than 15 per year
• Social network members churned completely within
  3 weeks of first disconnect

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The Solution

• Solution Targeted Best Plan Advice Offer
• Proactively notified customers spending 30 or
  more above lowest price when a better plan was
  availableregardless of contract stage
• Focus on Social Network members
• Reactive plan support at the call center
• Delivered side-by-side plan comparisons
• Allowed operator to focus on delivering value as
  opposed to cutting price
• Minutes
• Data bundles/content
• Enabled operator to offer more personalized
  offers that meet specific customer needs,
  multiple plans bundles for voice/data

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Analytics in ActionA Quick Case Study

• Results
• Churn was reduced by nearly 50
• Social Network churn reduced by more than 60
• Contact center processes more calls with improved
  resolution
• Improved morale
• Resources are optimized
• Up-selling and cross-selling improves
• ARPU increased by 4.2 (net!!), improving
  profitability

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Conclusion

• Proper use of analytics allow service providers
  to improve operational performance
• Reduces churn
• Increases ARPU
• Reduces margin erosion through accurate pricing
  actions and effective competitive response
• Increases cross and up-sell take-up rates
• Enhances customer care efficiencies
• Increases staff morale
• Builds customer and brand loyalty
• Positively impacts profitability