Retention
...In the past, data driven churn management has depended on two different kinds of sources. Firstly, data mining of your customer transactional and behavioral data to allow you to predict and flag customers who might defect – but not why they might do so. And secondly, market research that offers you diagnostics and insights on why the customers might defect but can not accurately identify who they might be.
Our model fuses these two streams of data to provide a comprehensive tool that tells you who is likely to defect among your entire customer database and also why they might do so. At the end of our modeling, our clients are not only able to accurately flag the vulnerable customers in their existing CRM system but also populate the CRM system with valuable insights and diagnostics on why they might defect; enabling their marketing, loyalty and customer service departments to take better actions towards managing retention and churn.
- Can you accurately predict who among your customers are loyal and who are likely to defect in the near future?
- Do you know why some of your customers defect while others remain with you for a long time?
- Do you know what specific actions you can take in terms of your marketing efforts and customer service/call center training to turn your vulnerable customers into loyal customers?
- Do you know who among your customers are most likely to be susceptible to competitive messages and switching incentives and why?
- Do you know what kinds of competitive messages and programs are the most powerful in driving churn?
- Do you have a complete profile of your loyal versus vulnerable customers?
Cognicient consultants have decades of experience in customer loyalty and churn management. We understand that in order to effectively manage churn we need to identify and flag every potential vulnerable customer in the database. But this on its own will neither help us develop the best retention strategies nor enable customer service and call center representatives to employ the best tactics for reducing churn. For this, we need to understand all the key drivers – demographics, psychographics and attitudinal – and apply that to the database on a customer-by-customer basis to offer a complete blueprint to address the needs of vulnerable customers.
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