Sometimes when you’re forecasting LTV, you want to see how projections based on recent performance compare to projections based on longer time periods.
Up until now, Everhort’s LTV forecasts were always based on a linear projection of the blended average performance of the last 12 monthly cohorts. There were reasons for this. If customer retention rate drops off after 6 months, you typically want to factor that into your forecast. But if average order value has been increasing recently, you want to account for that as well. A trailing one year period strikes a good balance between considering enough historical context to know how customers engage with the business over time, while still incorporating recent data, which is why it’s still the default time period for LTV forecasts in Everhort.
But sometimes your business changes significantly. Maybe you’ve been experimenting with new offers or eCommerce subscriptions. You’ve seen big changes and you’re curious how that could impact future LTV if recent trends continue. For this reason, we’ve recently enhanced Everhort’s LTV forecast tool to tailor its projections to the currently selected time period:
You can see from the example above that the one year forecast based off the trailing 6 months of cohort performance is $1,943, compared to $1,276 when using the last 12 months of cohort performance.
One last thing to note: When a shorter historical time period is selected, Everhort will also shorten the time period used in its forecast.
We believe having the flexibility to compare forecasts based on different historical time periods will help you get a better sense of what you can expect LTV to look like in the future.