customer retention through analytics paul king, president & coo aperio ci september 18, 2008

Customer Retention Through Analytics

Paul King, President & COOAperio CISeptember 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 constraintsInternal Systems are over-taxed

Requirement to spend marketing monies effectivelyOutspending 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 customer’s usage and history are analyzed in detail.

To create the required offer necessitates analysis of usage data such as:

Account informationBilling dataCustomer 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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Expert interpretation and analysis:

Cross-referencing critical identifiersBehavior changesPatterns of promotionsTake-up ratesRewards and sales

--Identify patterns and trends that accurately forecast customer behavior trends



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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 centerWeb portalText messageVoice mailDirect 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 call…when…how often?



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Propensities, preferred method of communications, applied loyalty and reward offers:

What has worked before? Will it work now?

How much they’ve 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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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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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

Process…Process…and did we mention?…Process

….. to meet customer’s specific preferences and needs.



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Analytics in Action…A Quick Case Study

Large Western European Mobile Operator

Challenge

Saturated market

Commoditized pricing

Multiple plans & bundles for voice/data

High annual churn rate—32%



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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” OfferProactively notified customers spending 30% or more above lowest price when a better plan was available—regardless 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

MinutesData 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 Action…A Quick Case Study

ResultsChurn was reduced by nearly 50%

Social Network churn reduced by more than 60%

Contact center processes more calls with improved resolutionImproved 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 performanceReduces 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



customer retention through analytics paul king, president & coo aperio ci september 18, 2008

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