Facts and Festivities Day 10 – Calculating Customer Lifetime Value

On day seven of this series, we highlighted the importance of Customer Lifetime Value (CLV). If you had to choose just one ROI metric from an exhaustive bunch, we said, you should choose this one.

And as well you should. Because advertisers who focus on CLV make around 15 percent more revenue in the first year.

First, a reminder of what it does:

The CLV metric measures gross profit and success over a customer’s “lifetime” (12-24 months)

In eCommerce, generating new business can be expensive. According to the Harvard Business Review, it costs up to five times as much to attract new customers—which emphasizes the importance of keeping your existing ones. Forecasting returns can be another challenge. This is where CLV can help.

Which version means what?

The CLV metric exists in different guises, including “predictive” and “historic.” Predictive CLV can be more challenging to produce, but it’s arguably worthier than its counterpart. This format uses previous transactions mixed with a variety of behavioral indicators (that forecast a lifetime value for an individual customer). With each new purchase (and new behavioral data) the metric changes to become more accurate over time.

Here is the equation:

PredictiveCLV = ((AverageMonthlyTransactions x AverageOrderValue) AverageGrossMargin) AverageCustomerLifespanInMonths

Spoiler alert: Every industry is different—you may have to make specific changes to your CLV equation over time to have it accurately reflect the value of customers. There are more advanced versions of the predictive CLV algorithm available, and you should explore how well those options may fit your business model.

Historic CLV is simpler. This version is the sum of the gross profit from historic purchases made by a specific customer. It takes into account any expenses associated with the purchases the individual made:

Historic CLV = (Transaction1+Transaction2+Transaction3…) X AverageGrossMargin

This is simple enough to be calculated in Excel as long as you have all of your transactional data on hand for a given customer. This should also take into account any expenses like service costs, returns, acquisition costs and other expenses to provide a clear picture of individual profit.

Of course, it can be complex to put together these expenses on an individual basis. Attributing certain costs to an individual customer is often problematic. When in doubt, use averages to estimate until you can properly track expenses individually.

For more advice on your campaigns (including how to better leverage CLV), contact us via info@crealytics.com.


Luke is a Content Marketer at Crealytics

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