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).
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. Continue reading “Lifetime Value Part 21: 3D LTV”
I have written many times about the importance of customer lifetime value (LTV), about its central role in determining a company’s success and how to impact it. In this post, In this post, I will address how to manage users (customers, players, etc.) based on LTV.
Profitability, success and LTV
The success and growth of your company comes down to one basic principle, your customer LTV needs to be greater than the cost of acquiring and servicing the customer. The larger the difference between the value you get from a user and the costs associated with that user, the greater your profits. The greater the difference, the more resources you can devote to user acquisition. The greater the difference, the more someone will pay for your company.
The key to optimize the value of a customer versus their costs is not treating all customers the same. Each customer has a different LTV, which can be estimated from everything nearly all the data you are collecting, including from how you acquired the user, their demographic, their initial behavior, etc. The first step to optimizing your business is to determine your different customer segments (VIPs, heavy spenders, occasional spenders, one time spenders, social whales, browsers, etc.). You then put all of your users (hopefully automate this process) into these segments.
Managing a customer portfolio
Once you have segmented your users based on their behavior and predicted lifetime value, you need to manage actively this portfolio of users to optimize your profitability. For each segment, you need to build a strategy that maximizes the difference between the LTV and the costs. For users who spend frequently, you may want to give them enhanced customer service and free gifts so they come back (and spend) even more often. The costs of this additional service and gifts are more than offset by the additional revenue you generate. Conversely, for the one-time purchasers, you want to minimize expenses tied to them. Since they have a low lifetime value, you do not want to devote any resources (costs) to them. By allocating resources only where it increases the difference between LTV and costs, you optimize your profitability. Continue reading “Lifetime Value Part 13: Managing users and customers profitably”