August 24, 2012 | Authored by: Vindicia Team Blogs
Measuring Customer Retention: Why Key Metrics Matter
Most businesses will agree that retaining customers is critical to their success.
However, what many digital businesses may not understand is the full impact of not retaining customers, and why tracking and understanding metrics is critical to minimizing that impact. Equally important, but often overlooked, is understanding that retaining ALL customers is not the key. What actually matters is retaining the right and best customers.
So how can a digital business gain a deeper understanding of its customers and how can they attract customers that will stay longer? One answer is utilizing Big Data. Big Data is a goldmine of untapped information that was previously unusable, but new technology has enabled this data to be translated into usable and meaningful analytics. However, just because Big Data is available doesn’t mean it is analyzed and leveraged to help make critical business decisions that encourage customer retention. A digital business needs to understand what metrics should be used to help drive those decisions.
The first steps to understanding the valuable metrics about customer retention are to understand what success looks like and what questions need to be asked and answered. Aside from the inherent knowledge derived from a product or service being sold, much of this information is available in the subscription billing and payments data being collected every month, quarter or year, depending on the chosen model. Few businesses actually analyze this data for trends in their business (other than payment success or failure) and even fewer use it to drive critical business decisions. None are able to use it to gain any industry-wide metrics or trends.
One critical metric that many digital businesses don’t fully understand, let alone analyze, is Average Customer Lifetime Value (ACLV). What does it really cost a business when they are unsuccessful in retaining a customer in month 3 of a 25-month expected lifetime, and how can they minimize this ‘cost’?
Let’s use Netflix as an example. Presumably, they value data and analyze it to help drive business decisions. Let’s say they have Average Revenue per Month (ARPU) of $11.65 and customer churn is around 4% (implying a 25-month average lifetime). Then this reflects an ACLV of $291.25. If they were unsuccessful in retaining a customer at month 3, they would have only captured $34.95 out of a possible $291.25 in revenue. This means that they are not realizing’ $256.30 in potential revenue. Clearly, this would not be the desired outcome, and if metrics were not used to manage this example, significant amounts of missed revenue would likely not be addressed.
Bottom line: Customer retention is not just about a one-time save. It’s about building value for your customer and then leveraging your metrics intelligently to enable you to capture their entire Average Customer Lifetime Value.
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