LTV Cohort Calculator Service Connector for AI agents.

It's a capability that lets your AI agent pull historical revenue for specific customer groups and calculate their lifetime value. It helps you see which customers are worth the most over time.

It uses your historical data to project what a customer group will spend over the next 36 months. You can choose different growth models to see various outcomes.

Yes, you can ask your agent to find the cumulative value at any milestone, such as 3 months, 6 months, or a full year after a customer joined.

Linear projections assume steady growth, while logarithmic projections model a slowdown in growth over time. Using both helps you see a more realistic range of possibilities.

You can use it to compare different acquisition cohorts. This helps you see which marketing channels are bringing in customers with the highest long-term value.

Yes, your agent can pull metrics for different signup months so you can compare the performance of various marketing campaigns side by side.

Use the fetch_cohort_metrics capability. This function retrieves the accumulated monthly revenues for a specific cohort, providing the foundational time-series data required for all subsequent LTV analyses.

First, use calculate_cumulative_ltv to determine the exact LTV at fixed points (like 3 or 6 months). Then, if you need a longer-term forecast, feed those historical metrics into generate_ltv_projections. The projection capability uses advanced math to estimate value beyond observed data.

The generate_ltv_projections capability requires two key pieces of information: the unique cohort identifier and a structured JSON array containing historical revenue metrics. This data is typically sourced from running fetch_cohort_metrics first.