What does good look like in terms of Winning Back Lost Customers?


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This is one of a series of blogs from Paul Weston, the architect of The Customer Framework’s SCHEMA toolset. In each blog he reveals the thinking behind the individual capabilities & practices that make up one part of the SCHEMA Capability Assessment, which is becoming the World’s leading customer management benchmarking tool. There are 110 capabilities in the assessment, containing almost 400 individual practices that together provide a comprehensive definition of what ‘Good’ looks like in today’s “Customer World”.

In the “WIN” area of the assessment SCHEMA® has a specific capability called “Winning Back Previous Customers” and this is what it looks for

schema model the customer framework

Scoring for winback attractiveness

Clear criteria have been developed for deciding which customers are wanted back and which (if any) are not. These criteria input to a score for the attractiveness of winning back a lost customer, and are consistent with (but not identical to) the criteria that the organisation uses in its scoring of ‘retention desirability’. A ‘likely cost / difficulty’ element is also included based on mechanisms / algorithms that quantify the likelihood of success and potential cost of winback activity. This utilises latest and trend engagement scores; reason-for-loss insight; price sensitivity insight; market volatility insights; etc. Multivariate analysis (i.e. to understand what investment and / or types / combinations of offers are needed to drive different results) are used periodically, but estimations and proxies provide a valuable, pragmatic solution that can be run regularly across data on all ex-customers to identify potential Winback targets .

Development of specific Winback propositions

Propositions have been developed that are aimed specifically at winning back lost customers. These are based on a clear, aggregated understanding of why customers left, what the difference is in the organisations current proposition / quality-of-service, and what is likely to entice them back. This understanding usually involves a number of inputs: analysis of reasons-for-loss; specific needs research that allows lost customers to freely express their un-met needs; input from colleagues who have interacted with lost customers and those experiencing frustrations with internal processes that impact the customer; analysis of expressions of dissatisfaction and complaints data. The resultant winback proposition(s) go beyond product development and marketing communications offers and include all areas that matter to customers, including delivery, credit, finance, service, documentation, sales relationship, etc.

Implementation of Winback activity

Winback communications are based on a formally designed ‘ideal’ winback experience. They recognise the reasons-for-loss, encourage re-engagement and begin to introduce the winback propositions. They are targeted at those customers that have been defined as ‘wanted back’ and vary in nature / duration based on not exceeding a calculated, allowable cost of winback. Timing & targeting reflects the things that have been ‘fixed’, so that returning customers don’t experience the same problems again that caused then to leave in the first place. For customers that are low or medium attractive to win back the winback activity is at an arbitrary time after loss but for very attractive targets the activity is more individually timed, often based on research into the customer and their new vendor wherever possible.

Reason-for-loss information available for use in Winback

Any information that has been captured on reasons for loss, either directly from, or indirectly (e.g. from Sales People) about individual customers is available on the customer’s database records at available at all of the interfaces likely to be involved in winback activity. The data is usable in dialogue and can also be merged into outbound communication for winback targets. Where data on individual customers is not available then aggregated / analytical data about the type of customer is available to provide a more informed approach to winback that a simple, vanilla “please come back” message.

For a great illustration of a timely and well-targeted Winback communication from Vodafone to the author as a ‘small business customer’ check out this link

Republished with author's permission from original post.

Paul Weston
Paul Weston is a Director of The Customer Framework. Paul has been consulting for more than 20 years after a marketing and product management career in the telecoms and motor industries. He has worked with multinational clients in banking, insurance, telecoms, motor and hospitality. He has developed many tools to help clients address challenges as diverse as Contact Centre resourcing, business case construction and risk assessment. Paul leads the development and management of The Customer Framework's core SCHEMA Toolset.


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