Expected Lifetime (eLT) is the fifth of seven key SaaS metrics used in our framework and looks at churn to determine how long you can expect to retain a customer. If you haven’t yet read prior posts covering tCAC, ARPU, RGP and GMPP, I suggest you start here.
Step 5: Calculate eLT – Expected Lifetime
eLT is the length of time a company expects to keep a paying customer. While some customers will churn out immediately and others will stick around for an eternity, eLT is concerned with the average lifetime across a group of customers. Converting the familiar churn metric into eLT (eLT = 1/churn) allows for an intuitive comparison to Gross Margin Payback Period. Recognizing that companies might not have detailed cohort analysis to model long-term retention curves, month-to-month calculations of churn within a segment of customers is an adequate proxy. (Note, we have a serious problem if eLT is shorter than GMPP!) While some SaaS companies have long-term contracts that suggest a predetermined minimum customer life, we care more about customer “stickiness,” not contract length. After all, contracts can be renewed – and broken.
Different acquisition channels often yield customers with different profiles. Organic customers are often “sticky” because they sought the company directly; customers from affiliates are often “flighty” because a third party did some or all of the sales work. In our example, the component view demonstrates that Premium customers are more loyal than Basic customers. Using company level eLT rather than component level eLT would cripple our ability to draw real conclusions about existing customer behavior.
We also need to discuss a concept even more important than account churn – the idea of dollar churn. While SaaS companies will constantly be fighting a losing battle against account churn (at best, breakeven), the good news is that customers who stick around often increase the size of their subscription over time. Account growth can occur for several reasons: periodic price increases; a growing customer requires more seats; or satisfaction with the product leads to the purchase of additional modules. Furthermore, there is such a thing as “good churn” that occurs when low-ARPU, support-intensive customers leave and resources can be reallocated to higher profit customers that have a greater chance for upsell.
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