Estimating Lifetime Value (LTV) of SAAS Customers
Calculating Lifetime Value (LTV) of customers is essential for smart marketing in any B2B SAAS company. LTV dictates how much money to spent in acquisition as well as the nature of retention and upsell efforts.
To make things interesting, LTV typically differs by customer tier, requiring further refining of marketing strategies and budget allocations for different tiers.
In this blog, we will look in to how to calculate LTV of customers. For this discussion, customers are treated as homogenous (say, mid-sized businesses only). However, the logic can be extended to different customer tiers as your business warrants. Also, we will assume all customers sign annual contracts – meaning churn occurs only at the end of contract period.
With these considerations, the LTV can be estimated using the following formula:
(Average ARR) * (Average Lifetime in Years)
Calculation of each component is detailed below.
Calculation of Average ARR
Calculating Average ARR is straight forward – For the current customer base, add up ARR’s and divide by number of customers. Note that this amount will be different from average of new ARR’s (at the time of sign-up) because it will account for effects from upsell and cross-sell efforts. However, we want to capture impact of these effects in the LTV calculation.
Calculation of Average Lifetime
Calculating Average Lifetime will need some extra calculation. Essentially, this will involve estimating sum of lifetimes of a cohort of customers and dividing by the number of customers.
For this calculation, ideally you will have at least 2 years’ worth of customer history. That will allow you to select a cohort of customers from early period and track their churn characteristics for at least two years. If this history is not available, or if you think your business has changed substantially over time, use your best judgement to arrive at key considerations detailed below.
Let us assume you start with 100 customers 2+ years ago and look how many churned in the first year and second year. If the average churn per year is 30% (i.e. retention of 70%), the customers remaining from the cohort will be as follows:
First year: 100
Second year: 100*70% = 70
Third year: 100*(70%)^2 = 49
And so on..
The above series is a geometric series. In such as a geometric series, if the first term is “a” and the multiplication ratio is “r” and if r is less than 1, the sum of such series will be: a/(1-r)
In the above example, the sum would be 100/ (1-0.7) = 333.3
Therefore, The Average lifetime will be: 333.3/100 = 3.33 years.
The above methodology can be used to estimate Average Lifetime, and consequently Lifetime Value of your customers.
In most real-life cases, the churn pattern will not fit neatly into a geometric series as discussed earlier. Some aberrations can include, such as:
- Churn occurs in the first few months after acquisition
- Higher churn in the first-year anniversary, and lower churn in the subsequent years
The solution for these aberrations will be different based on your unique situation. However, one potential solution is as follows:
- Treat the first year as a separate case (not part of geometric series) to accommodate the special cases of (1) churn in the first few months and (2) higher churn in the first-year anniversary
- Geometric series will start after the first year. The churn after 2nd year, 3rd year, et cetera are more uniform and they will most likely will fit into a geometric series.
The approach provided here is a simplified version. However, as noted, many adjustments can be made to be relevant and useful to your specific situation. Therefore, the concepts provided can be easily extended and applied to fit your business.