How do you know if your CLV metric is accurate?

Not all CLV models are created equal. If you’re reviewing CLV from your organization or a vendor, start by asking yourself a few questions to see if the metric is accurate and useful.

  1. Is the CLV at the aggregate level or individual level? If it is aggregate, is it the mean or median? It’s pretty easy to calculate CLV at the aggregate level. Because most business use cases require individual level CLV, you’ll want a model that calculates CLV for each customer.
  2. Is CLV historic, predictive or some combination? If CLV is provided at the individual level, you want it to be predictive and not just historic.
  3. How much of CLV is already observed vs predicted future revenue/profit? The danger of using only future-predicted revenue is that you can no longer compare future-predicted revenue of a highly active current customer with a previous cohort of customers.

Read more about the CLV questions you should be asking in this blog post.