Case Study
Learning from Attrition
Introduction
We all lose customers. Attrition analysis not only helps understand why but can identify predictors of future potential loss and allow the opportunity to take proactive steps to avoid losses.
A B2B SaaS SME developing medical technology systems has relatively high revenue concentration – a small number of long tenure, high revenue customers. Although the software is “sticky” in the sense it has high switching costs, it has not prevented attrition. Beyond the financial loss, the company wanted to understand 2 things more clearly:
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What are the causes of attrition and are there common factors that can be addressed through product or service enhancement; and
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Is it possible to predict future attrition and be in a position to take steps to mitigate.
With structured analysis it’s possible to address both.
The Opportunity
Customer loss brings financial, operational and reputational risk. Not all loss can be mitigated but gaining a deeper understanding of the root causes can allow actions to be taken to mitigate loss to a significant degree.
First step is to compile the history of customer loss for the past 3 to 5 years with emphasis on the following:
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Products/services consumed
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Financial terms - revenue, customer profitability
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Contract terms - term, financial penalties, break clauses etc.
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Operational data – no. users, support tickets, training, customer satisfaction scores etc.
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Anecdotal information – notes, visit reports
Second build a spreadsheet that categorises the information so that it can be easily compared across multiple customers. There are templates available that help structure the data.
Third is to conduct analysis to look for trends and common factors that might explain root cause of a loss. Pose hypotheses to test through data analysis such as:
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Is the loss contained to a small number of products or a particular service?
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Are there common types of support ticket that occur prior to loss? Does the successful closure of said tickets impact the outcome or not?
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Does the frequency, duration or nature of support requests change significantly in the lead-up to a loss?
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Is there an observable trend with regard general customer contact or the lack of?
This attrition analysis can deliver 2 valuable outcomes:
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Identification of observable factors that you can begin monitoring for existing customers to gain early warning of potential customer loss; and
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Potential changes to product/service features, support processes and/or general customer contact protocols.
For support-related factors, build the monitoring/reporting of them into your support desk platform to automate the process.
The Results
Through attrition analysis the company was able to address the following:
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Develop a deeper understanding of why some customers left
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Use the learnings to create an early warning system they can apply to existing and new customers
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Introduction of a proactive customer communications program to ensure regular contact is maintained by the support team irrespective of customer need for support
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Identify enhancements to certain product features and services to encourage more productive use or eliminate potential support issues
Initial results indicate improvements in customer satisfaction scores and the start of a downward trend in annual revenue attrition.