Measure your customer lifetime value, check how each cohort is performing and predict future cohort behavior - how long customers will stay retained, how many orders they’ll make, and what their expected 6-month or 12-month revenue is.

The Lifetime Value feature of the Lebesgue: AI Marketing & LTV app is designed to help you better understand your customer behavior and how much revenue you are making from them during their lifetime with your business.

Use it to analyze how different customer cohorts and customers acquired through different channels are behaving and what the difference in LTV is between them.

See how your monthly revenue changes over time, and compare revenue generated from first-time and repeat customers.

See how your monthly orders change over time and compare orders generated from first-time and repeat customers.

Use cohort analysis to analyze how your customers behave over time: how frequently they are reordering, how much revenue they’ve generated over 6 or 12 months, and explore their retention.

Use the “Cumulative” view to see the total revenue or orders generated by a cohort, and use “Prediction” to unlock a powerful statistical model that forecasts <b>future customer behavior.

Pro tip: Compare cohorts generated during sales (cohorts that used a discount code) to measure the quality of customers purchasing on discounts. Frequently, higher-valued customers are those who purchased outside of the sale period.

Analyze all key metrics for every single cohort - average order value (AOV), lifetime value (LTV), customer acquisition cost (CAC), and payback period. Use the “Expected” view to see how a cohort will behave in the next 6, 12, or 24 months - what is its expected revenue and LTV.

By using the Expected LTV and Expected revenue metrics, you will be able to compare your older and newer cohorts more equally since these metrics reflect the LTV or Revenue at the end of a selected period (6 months, 1 year, or 2 years), allowing you to see whether your newer cohorts will perform better or worse compared to the older ones that have had more time to gather data already.

Pro tip: Using this analysis allows you to allocate the marketing budget more effectively in the future, and combining it with the UTM filter allows you to figure out the most effective marketing campaign or channel.