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Retaining Customers. Proactively.

Retaining Customers. Proactively.

Owning an indispensable and uncontested product or service may be the ideal scenario for Customer Retention; however in most industries, a lot of grey remains between what you and a competitor is offering.  Media engagement to influence a customer’s brand recall, promotions such as loyalty cards or discounts are effective but may not be the optimum utilization of a company’s budget to manage Customer Retention.

Armed with sufficient data, a Business Scientist would like to approach Customer Retention in two steps:

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  1. Segmentation of customers into ‘Loyal’ or Engaged, ‘Lost’ or Attrited, and Customers that are ‘At-risk’ or that lie in the grey area of decreasing ‘Engagement’.
  2. Developing an effective Retention strategy for ‘At-risk’ Customers.

To build a Proactive Customer Retention (PCR) Strategy, an analytical model is developed leveraging past customer data, historical attritions, identification of specific attributes of attriting customers, and the weightage that each of these attributes carry.

Depending on whether it is a B2B or B2C business, magnitude of data capture, number of customers, frequency of purchase, etc. will vary. Typically, a B2B business will have lower numbers of customers and less transactions of higher value or contracts for a longer period; however such businesses tend to capture more details for each of their customers, their usage and purchasing patterns.  A B2C business on the other hand will primarily capture sales data. In such a scenario, building the model parameters around recency of purchase, frequency of purchase, tenure with the business and transaction value will be key.
Once the PCR model has been build and factors identified, current customers are scored based on the model results to understand their engagement level and ‘at-risk’ Customers identified. ‘At-risk’ customers may further be segmentated on basis of geography, transaction size or industry segment to develop segment specific retention strategies.
Next, a retention strategy needs to be developed. The retention strategy could be a periodic phone call to at-risk customers, offering limited period discounts, packaging two or more products/services together, customizing the product or service to suit a particular customer’s requirement, etc.  In addition, the PCR model can be employed to determine overall influx and outflux of customers, expected uplift from retention initiatives, and to predict future sales. A robust PCR strategy will also ensure that the model is refined and updated with fresh data from time to time.
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