I recently read an article on Sociomantic, “Customer Lifetime Value in Three Dimensions,” about looking at lifetime value (LTV) tied to the customer journey and it adds another dimension to calculating lifetime value that could greatly improve its predictive value for you as well as pointing to areas for improvement. The article breaks LTV into three dimensions: recency, frequency and profitability (Note: The authors refer to the third dimension as “monetization.” Based on my previous posts on monetization, I felt this term would confuse my readers, as our definitions differ).
Recency
The article points out that a key determinant of recency is when the customer last made a purchase (or in a game, last monetized). When examining the recency dimension of your customers, you should analyze which cohorts purchased which items. With this information, you can then predict subsequent purchases, including what items each cohort (actually each customer) is likely to purchase. This analysis provides an LTV for each cohort (or even customer) and can power a machine learning recommendation engine or post-purchase retargeting engine that would increase LTV.
Frequency
Frequency is what it sounds like: How frequently a customer monetizes or makes purchases. Purchase frequency is a strong indicator of a customer’s lifetime value, as studies have shown more frequent purchasers will spend more over time (even if the purchases are smaller). It becomes even more valuable if you begin to analyze aggregated user data, using cluster analysis to identify trends and understand which shopping behaviors indicate which LTV. Thus, cohorts who spend more frequently should receive more service and efforts to retain them.
Profitability
The third dimension is profitability, the revenue from a customer minus their costs. It is effectively the margin for that customer or cohort (and different offerings have different costs to you) as well as taking product returns into account. Understanding underlying profitability allows you to optimize LTV by moving customers or players to products where you have a higher margin or focusing on territories where customers are less likely to chargeback or return a product.
Key takeaways
- If you look at your customers in three dimensions—recency, frequency and profitability—you can better predict and optimize the lifetime value of specific customers and cohorts.
- Recency focuses on when the customer last purchased and helps you predict if/when they will spend again.
- Frequency is a powerful predictor of future purchases, a customer who spends more frequently (even small amounts) is more likely to monetize in the future.
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