How to Calculate Lifetime Value
Calculating customer lifetime value can involve some complex math with many variables and equations that can be quite intimidating. There is even very expensive software to compute complicated CLVs for all different types of customers and products. Fortunately, you don’t have to be a mathematician or computer scientist to compute a basic, helpful CLV estimate.
Remember that the more data you can gather about your customers’ buying habits, the more accurate your results will be. However, the method is quite easy and you can get a good estimate of your CLV with relatively little data. It’s a three-part process:
Calculate the CLV.
Identify profitable customers.
Use this process to estimate a typical customer’s revenue:
Calculate how much money a typical customer (or a typical customer from a specific segment) generates per purchase.
One way to do that is to average the revenues from several customers (within a segment or from your market as a whole).
For example, the typical revenue from a customer’s purchase in a sandwich shop can be around $8. The figure shows fictional purchase data from six different customers, as well as the average.
The larger the customer sample, the more precise the results are. The CLV can’t be more precise than the data it is calculated from. Therefore, look at “hard” data such as historical or current sales, to obtain accurate averages.
Estimate the frequency of the customer’s purchases.
The appropriate time frame, called the purchase cycle, depends on the industry. A sandwich shop may find that the most relevant time frame is one week, and that each customer purchases about three times per week (like some of my colleagues), as illustrated.
For purchasing desktop and laptop computers, it’s likely two to four years, and for rental cars and airline tickets it may be a few times per year, depending on the customer segment.
Calculate the revenue per customer over a certain time period.
Multiply the revenue per purchase by purchase frequency:
Revenue per purchase x Frequency of purchase = Revenue over a certain time period
In the sandwich shop example, the result would be expressed in dollars per week:
$8/purchase x 3 purchases/week = $24/week
The figure shows the breakdown of this average for the same six customers.
Calculating the CLV
The simplest way to compute the customer lifetime value is to evaluate how long the average customer does business with your company and to calculate how much revenue is generated during that period:
Revenue per purchase x Frequency of purchase x Customer lifetime = CLV
In the sandwich shop example, assuming that the revenue per purchase is $8, the frequency of purchase is three times per week, and the customer lifetime is 20 years, the CLV is
$8/purchase x 3 purchases/week x 52 weeks/year x 20 years = $24,960
However, to make the result more precise, other factors should be taken into account if the data is available. Using the revenue generated from a customer will almost always overestimate the customer’s true lifetime value because it doesn’t factor in the costs of things like employees, building and/or equipment lease, and advertising. In fact, without factoring in costs, CLV is usually referred to as customer lifetime revenue (CLR).
It, therefore, makes sense to factor in the profit margin, which is the percentage of the revenue left over after subtracting all the company’s expenses. A more realistic CLV can then be calculated using the following equation:
Revenue per purchase x Frequency of purchase x Customer lifetime x Profit margin = CLV
In this example, with a 21% profit margin, the CLV becomes $5,242. Profit margins vary significantly by industry and product type. For example, General Electric’s lighting business has profit margins of less than 5% and its industrial business has margins around 15%. Computer software typically has margins above 70%.
Do the best you can to compute a realistic margin based on your business and products because it has a substantial effect on computing an accurate lifetime value calculation.
Two values can be used to refine your CLV calculation:
Retention Rate: The customer retention rate is the percentage of the customers who repurchase over a specific period of time.
As a simple example, if 800 out of 1,000 customers are still customers after a year, the retention rate is 80%. If you have the data, look at multiple years to generate a more accurate rate of retention.
Discount Rate: The discount rate is an economic notion that is used to calculate the present value of future revenues.
The basic idea is that having money today is worth more than having that same amount of money at some distant point in the future. Would you rather have $10,000 today or $10,000 in ten years?
The same principle applies to company profits. Future profits are discounted to account for their current value.
If the lifetime of a customer is short (weeks, months, or a year or so), then the discount rate won’t have as much of an effect as if the lifetime lasts years or decades.
The CLV equation becomes more accurate if retention rate and discount rate are taken into account:
Revenue per purchase
x Frequency of purchase
x Customer lifetime
x Profit margin
x ( retention rate) / (1 + discount rate – retention rate)
If the retention rate is 75% and the discount rate is 10%, you obtain a CLV of $11,233 for the previous example. While the retention rate is always lower than 100% and therefore reduces the CLV, taking the value of future money into account using the rate of discount results in a higher yet more realistic CLV.
As with most of the customer analytics discussed in this book, the precision of the CLV depends on the quality of the data available and the number of variables that can be evaluated. However, even imperfect results can be used to compare different customer segments and identify the most profitable customers.
Identifying profitable customers
Calculating the lifetime value of different customer segments enables you to identify the segments that are worth the investment of large acquisition costs.
To find the most profitable customers, calculate the CLV for your different customer segments and compare with the average CLV. Differences in lifetime value between segments can be rather large and should help focus your customer acquisition strategy. It may be more expensive to gain the good customers’ loyalty, but in the long run, they will generate more revenue.
If, for example, the sandwich shop’s frequent customers generate about $3,000 more than the infrequent customers over their lifetime, then an investment of say $500 spent marketing to acquire these more frequent customers would pay off.