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Predictive Analytics For Customer Retention

Predictive Analytics For Customer Retention

One of the biggest risks to companies and their growth is the silent customer. These customers do not reach out to companies and let them know if they are dissatisfied with their products or services. They then stay away from the company and cancel services altogether.

With predictive analytics, businesses can break the cycle of the silent customer churn. Here are several ways to do just that and retain customers:

  • Determine the customers who are most likely to leave even before they discontinue services.

With predictive analytics, subtle signals such as specific behaviors and decreasing engagement can easily be spotted well before the customer churns. Once these customers are identified early, the company can then take a full suite of steps to influence the customer’s decision to leave.

  • Determine the best steps that can effectively reduce the churn.

The most common remedy to silent customer churn is also the most expensive and least effective: providing discounts. This is not likely to work because companies tend to assume that the sole reason why customers are leaving is because they don’t feel that their services offer a good value for the cost. Predictive analytics can figure out the detailed features of your products and services that each unique customer is most likely to value. With these insights, companies can then help the customer discover the true value of a specific service. This is a win-win situation because companies will be able to gain the business of a customer based on the value of their services without losing money due to discounted offers.

  • Determine when, which channel, and what message will reach the customer.

Another great benefit of predictive analytics is that it can help companies identify the most effective combination of the message, time and channel they should use to connect with each customer. This is a step above the regular personalization found in most businesses today, and refraining from a one-size fits all method guarantees a higher chance of connecting with every customer.

  • Determine the complete set of steps to customer retention, rather than just one action.

One single action isn’t enough to reduce silent churn and boost customer retention. The final decision to churn usually happens due to multiple experiences or non-experiences by a customer. With predictive analytics, companies can then identify the full path and sequence that companies need to take to make the most of customer retention.

 

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