Gathering Customer Lifetime Value Data – Start Small and Build

It’s important to segment your customer data to gain useful insights, but the relevant segments may not become apparent until you start wading through the financial data. In this post, we’ll discuss three important financial factors you’ll need for your customer lifetime value (CLV) calculations.

There are three important things you’ll need to find:

1. Retention rate/Customer lifetime

2. Revenue per customer segment

3. Margins per customer segment/sale

The latter two are pretty straightforward, and don’t leave much room for interpretation, so in this post we’ll focus on divining the retention rate. (One caveat on revenue – businesses with a brick and-mortar presence should also make sure to account for the “research online, buy offline” effect when calculating CLV. Otherwise,customers acquired via online channels will be undervalued.)

Customer “lifetime” doesn’t mean forever

“How long is a customer’s lifetime?” is a pretty common question. The “lifetime” in lifetime value isn’t quite so literal. You’re not expected to be projecting profits for the 75 years or so of a customer’s life. For one, that’s impractical. But more pressingly, the further out the revenue projections, the less reliable they are. Generally, we would recommend calculating your CLV within a five-year window (although some exceptions apply).

There are a number of different ways to figure out your customer’s lifetime. Two of the more common methods involve using your retention rate or your repeat purchase rate.

Scenario 1: Use retention rate

If you charge your customers a monthly or yearly retainer or subscription fee, you should know your monthly or yearly churn rates (retention rate = 1 – churn rate).

For example, an enterprise SaaS company with a yearly retention rate of 90% would have an expected customer lifetime of 10 years based on the equation below:

Scenario 2: Use repeat purchase rate

Repeat purchase rates are very similar to retention rates, except they are more relevant for companies whose customers have irregular purchase cycles. For example, a retailer with repeat purchase rates of 50% will have different customer lifetimes depending on whether their customer buys from them every 3 months, or every 3 years.

Scenario 3: You know neither

Some businesses may not know what their repeat purchase or retention rates are. In those cases, you’ll have to back into the number. You can do this by specifying a gap of inactivity where you decide a customer is no longer a customer, and then measuring the time period between the customer’s first and last purchase.

The period of inactivity in which you determine a customer has lapsed depends on the nature of your business. For example, a grocery store whose best customers buy weekly might determine that a 3-month dry spell is sufficient enough to indicate that they are no longer customers. Other businesses – auto dealerships for example – will have much longer lag between purchases.

Don’t forget about your segments

Regardless of how you calculate your customer’s lifetime, remember from our previous post that you’ll want to find the customer lifetime for each relevant segment you’re measuring, not just the total average customer lifetime.

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