Reduce Media Subscription Churn

Media Marketing / Sales Improve Customer Experience Increase Revenue Churn / Retention Executive Summary
Increase your subscription retention rates by predicting which customers will churn and intervening.
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Business Problem

As highlighted by the Harvard Business Review, acquiring new customers can cost five to 25 times more than retaining existing ones. While media companies are investing heavily in the acquisition, failing to retain subscribers means that the initial cost of acquisition goes to waste, and if the issue is prolonged, it prevents their business models from ever becoming sustainable. A business only survives if their customer lifetime value exceeds their cost of acquisition, and for media companies who have a 5 to 10 percent monthly churn rate, they will eventually hit a mark where their balance sheets can no longer support the heavy upfront capital required in acquiring customers. Retention is a key component of survival for all companies, especially for those in the trenches of the media industry.

Media companies have been left to increase retention rates that have inherently been designed as lagging indicators. Retention rates evaluate past relationships by finding the total number of customers who stayed in a company compared to the total amount at the beginning of a period. While there is a lot to learn about the reasons why customers churned in an attempt to prevent it in the future, the challenges are twofold. First, the customers evaluated have already churned and they are too late to recover. Second, learnings about why they have churned can only be generalized to the entire cohort of future customers and cannot be personalized to each one.

Intelligent Solution

AI leads to a complete paradigm shift in how media companies are increasing customer retention by predicting in advance precisely which of your customers are likely to churn and offers you insights on the top reasons why for each individual customer. Instead of generalizing past learnings on all future customers, AI learns patterns from the past and captures the characteristics of those who churned to be able to identify future customers in the future who are likely to fall into the same category. For customers who have a high risk of churn, you can take proactive measures to increase customer intimacy by personalizing solutions for every customer depending on their predicted reasons for churn. For example, for those customers who don’t feel satisfied with their subscription due to their inability to justify its financial cost, your marketers can reach out with special discounts or offerings. This turns things around by 180 degrees because the customer who was likely to churn may now be a loyal follower with their newfound value in your ability to understand their needs. On a macro level, understanding the overall reasons why customers are likely to churn will allow you to continuously iterate your sales process to adapt to every changing customer desire that arises.

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