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Lifetime Value (LTV) is the cumulative Gross Profit net of CAC, generated by a cohort over time. LTV represents the gross profit of an average customer in the cohort.

LTV = the cumulative gross profit from a cohort in month x / the # of customers in the cohort - CAC

For example, if you wanted to find LTV for your January 2021 cohort at month 3, you would:

  • Sum the gross profit for each customer in the January 2021 cohort for January through April
  • Divide by the number of customers in the January 2021 cohort
  • Subtract CAC 

LTV is a helpful metric because it combines gross margins, sales efficiency, retention, and ACV to give an overall picture of how profitable a company’s customers are. When LTV goes from negative to positive, it represents the “true” CAC payback period after S&M expenses and COGS, including cohorted expansion. A company with > 100% net dollar retention will see LTV grow super-linearly over time; alternatively, when NDR < 100% LTV will be sub-linear and eventually asymptote, not growing any further.

The way SaaSGrid calculates LTV is sometimes called “observed LTV”. This is because it shows the actual LTV of cohorts based on revenue earned, gross margins, retention, and CAC. There are other LTV calculations that try to “compute” LTV by doing calculations like ACV / (1 - Logo Retention)  to calculate how many years the average company will contribute revenue for. This “computed LTV” is often displayed as an LTV / CAC ratio. The issue with these computed LTV metrics is that they assume consistent margins and retention are consistent over time, and can’t account for cohorts with > 100% Net Dollar Retention. While sometimes helpful for consumer SaaS companies, SaaSGrid believes observed LTV is the best metric for B2B SaaS.

SaaSGrid also computes the Weighted Average LTV for each cohort age. For example, if you wanted to find the Weighted Average LTV for month 3:

  • For every cohort that has reached Month 3, multiple Month 3 LTV by the size of the cohort
  • Sum all the products
  • Divide by the number of customers in all cohorts that have reached Month 3

Weighted Average gives a good sense of how a cohort will most likely behave at a certain age.

Settings: Segments, Date Range, Date Aggregation, Revenue Type, S&M Offset, Expense Segments