> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sourcemedium.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Cohort LTV analysis

> How to analyze customer lifetime value (LTV) by cohort using SourceMedium tables and common filters

Use this guide to analyze **lifetime value (LTV)** by cohort (typically first purchase month) and compare cohort quality over time.

## Recommended tables

* Orders: [`obt_orders`](/data-activation/data-tables/sm_transformed_v2/obt_orders)
* Customers: [`obt_customers`](/data-activation/data-tables/sm_transformed_v2/obt_customers)

## Define LTV (before you chart)

Decide which revenue definition you want to use consistently:

* **Net revenue** (common for LTV): `order_net_revenue`
* **Gross revenue**: `order_gross_revenue`

If you include refunds/returns/cancellations, be explicit and keep the same definition across dashboards.

## Build the analysis (high level)

1. Filter to SourceMedium-valid orders (`is_order_sm_valid = TRUE`).
2. Determine each customer’s cohort (first valid order date).
3. For each cohort, compute:
   * Total net revenue (or gross revenue)
   * Distinct customers
   * LTV = `total revenue / distinct customers`
4. Add cohort aging (e.g., “months since cohort start”) if you want true cohort curves.

## Common pitfalls

* Comparing cohorts at different maturity (newer cohorts are incomplete).
* Mixing revenue definitions when validating against other reports.
* Not filtering out excluded/invalid orders.

## Next steps

* Pair with order behavior: [Cohort LTO](/help-center/common-analyses/cohort-lto)
* If net revenue looks “off”, start here: [Why don’t Executive Summary & Shopify match?](/help-center/faq/data-faqs/why-dont-the-executive-summary-and-shopifys-sales-report-match)