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How ARPU can lead to a 120% error in Customer Lifetime Value
- 3pt14159 15y agoI've done many, many LTV and CLV reports for companies and I always account for this. Protip: churn also goes down for SaaS apps. Also, you need to account for a discount rate but most of the time people don't want to hear this because it makes their numbers look less shiny. Pretty basic math, all things considered.
- jacques_chester 15y agoI suppose fitting a decaying function would be better than flat-out ARPU? Or even a moving weighted average?
- cpierson 15y agoWe're going to explore some of those approaches in upcoming posts!
- aaronjg 15y agoChurn also goes down in retail. If you look at retail cohort analysis, you will say that 10% of users are active three months after their first transaction, and then 5% are still active six months later. So you lose 90% in the first three months, and then only 50% in the next three months. This is particularly important in the RLV calculations, as assuming a constant churn rate will undervalue your existing customer base. Sounds like you are taking the right factors into account. What sort of accuracy are you getting with your calculations?
- 3pt14159 15y agoPretty close. Usually around 5 to 15 percent when taking off the top 2% of customers.
- badclient 15y agoWhatever font you guys are using for the body of the post is very difficult to read.