# How much are your customers worth?

Customer lifetime value (CLV) is the monetary value each customer generates over the lifetime of their engagement with your business. Repeat purchase behaviour is a driver of value. Businesses track % of repeat purchases as a key metric. However, this can be misleading if the business is experiencing significant growth. Growth entails many new customers; hence the mix of these first time customers will distort the view of the actual quantum of repeat purchases.

To estimate CLV, you have to conduct cohort analysis. Whist this is just an estimation, it gives a good sense of CLV before the end of a customer’s lifetime with your business. This helps to inform decisions on marketing and customer acquisition. So how do you estimate CLV?

#### CLV = ESTIMATED LIFETIME X ARPU X GROSS MARGIN

ARPU: Average Revenue Per User

Let’s look at ‘Estimated Lifetime’ first. Check out my spreadsheet here with an example of cohort analysis for a hypothetical subscription business, which is assumed to have been operating for one year. Firstly, let’s categorise the subscribers into cohorts depending on when they first signed up to the service. The numbers in red are the customer retention rates at the end of month X. Take the yellow cell as an example — it means that if 1,000 subscribers had signed up to the service in month 2, only 917 of them were still subscribing by the end of their 1st month.

Notice that for those who joined in month 1, we have 12 months of retention data; for those who joined in month 2, we have 11 months of retention data; and so on. Averaging across cohorts gives you the average customer retention rate after 1 month, 2 months, 3 months, etc. As we progress down the months, there are fewer data points to average across — this means that the probability of error is greater. Having said that, this is still a useful drill to get a feel for the company’s ability to retain customers.

You’ll notice a pattern of steep ‘drop-offs’ in retention after the initial month. This is typical of a subscription business, where attrition tends to be high in the first month before tapering off later. This pattern means that you can project retention rates forward a few years using historical month-on-month attrition. In my model, you’ll see that the ‘average % retained from previous month’ is 93.5%. Using this number, I estimated an average lifetime of 9.2 months per customer by projecting retention rates forward for 5 years.

Now ‘ARPU’ and ‘Gross Margin’ come into the picture. If you are a subscription business charging £10/month (ARPU) whilst making 80% gross margin, then you would have a CLV of:

#### CLV = ESTIMATED LIFETIME X ARPU X GROSS MARGIN= 9.2 MONTHS X £10 X 80%= £73.6

This is effectively the maximum you should be paying to acquire a customer, since you always want the value that a customer is bringing (CLV) to exceed the cost required to acquire that customer (CAC). I’ll be discussing the relationship between CLV and CAC (Customer Acquisition Cost) in a future blog post… so stay tuned!!

P.S. Although this is an example of a subscription-based business where the key driver is the number of subscribers, you could do the same analysis for other businesses with different metrics. For example, the key ‘repeat’ metric for a social media business might be the number of active users who are posting photos