Customer Lifetime Value

Customer lifetime value (CLV) represents a customer’s profitability over their entire relationship with the business. A straightforward way of thinking about CLV is as follows:

CLV = average profit per sale (AP) × number of repeat transactions in a period (RTP) × retention time (RT)

Please note, however, that this is a simplistic approach used to illustrate this concept and not something we would recommend using in a real-life setting.

Let’s use the example of a subscription business (i.e., period = 1 month). The business has a churn rate of 2%. Churn rate represents the rate of customers leaving a company per period (Wikipedia). In this case, the company is losing 2% of its customer base every month. Churn rate is useful to calculate the average retention time of customers: By dividing 1 by the churn rate, we obtain the retention time. In this case, customers stay with the business for an average of 50 months (or 1 divided by 0.02). The average profit per sale is $30. The number of repeat transactions per period is one, because customers are making one transaction per month and the period we are looking at here is one month. The CLV is thus CLV = AP × RTP × RT. Since AP = $30, RTP = 50, and RT = 1, CLV = 30 × 50 × 1 = $1,500. Over their lifetime, each customer brings the business $1,500.

CLV draws our attention to the importance of catering to the lifetime of a customer with a business. The first sale to a customer is not what typically brings revenue to a firm. Acquisition costs for a customer are generally much higher than the revenue a firm will make on its first sale. Thus, the objective of firms is to engage customers to increase their lifetime value.

More concretely, CLV can play many roles for a firm. For example, it helps firms price their customer acquisition strategies and calculate their return on investment. This is important because it helps evaluate whether acquisition strategies are profitable and manage marketing efforts more generally.

Continuing with the example above, let’s assume the firm is running a PPC search ad campaign to acquire customers. In this simple example, let’s further assume that people search for something, click on an ad which leads them to a landing page, and convert to customers from this landing page. The total campaign cost is $20,000, including all campaign elements (i.e., developing the landing page, all costs related to ads, etc.). The campaign gets 2,500 visitors on their landing page. The conversion rate is 5%, meaning that the firm converted 5% of the 2,500 visitors to their landing page. That works out to 125 customers (2500 × 5% = 125). The cost per acquisition is thus $160, or $20,000/125.

At this stage, firms will be asking themselves, “Is this profitable? What is my return on investment? Should I continue running this acquisition strategy campaign?” CLV becomes useful at this stage.

As a reminder, this firm earns $1,500 per customer on average throughout their lifetime with the company. Even if the company only makes $30 on the first sale (meaning that they just “lost” $95, since it cost them $160 to acquire the customer), two rules of thumb help us see that this is a profitable customer acquisition strategy over time.

The two rules of thumb to quickly gauge whether a customer acquisition strategy is profitable are:

1. Am I recovering my cost per acquisition over the next 12 months of the life of the customer with my business? In this case, the answer is yes: The company will make $360 per customer (AP × 12 = $30 × 12 = $360).
2. Is my CLV more than three times my cost per acquisition (CAC) (that is, CLV/CAC > 3)? In this case, the answer is also yes. CAC is $160 while CLV is $1,500, and CLV/CAC = 9.375. In fact, the firm should be happy to pay up to $500 per acquisition.

Among many other uses that CLV serves, it can also support retention and customer support strategies central to the Engage stage. By knowing the lifetime value of customers, firms can more easily price retention and support strategies, i.e., how much to put into trying to retain customers.

CLV varies per persona, where some personas will be worth more over their lifetimes than others. This helps firms to decide where to spend extra resources and which personas to pamper a bit more. It can also help a firm see whether it should “fire” a persona, i.e., minimize the efforts dedicated to customers already acquired and stop acquisition strategies for a specific persona if their CLV is drastically lower than that of other personas.

Lastly, it is important to keep in mind that, apart from subscription businesses such as the example above, customers rarely bring in the same amount to a firm throughout their lifetime. The relationship between a customer and a firm evolves over time, and it is important to recognize that the journey of customers expands beyond their first purchase with a firm. Not only does this vary between personas, but it might also vary between markets. In some markets, such as videogame consoles or eyewear, products are seldom sold, with an extended period between purchases that might encourage churn. In other markets, like groceries, consumers are continuously making purchases over their lifetime. As is the case in the market for diapers, other markets might see a significant uptick at the start of the customer’s life with a company and then declining sales over time as, in the case of diapers, the baby ages into a child. Although the new approach is predictive analysis, some earlier analytical tools, such as RFM analysis (discussed in the next section), provide information regarding some of these aspects. They also help us understand the basics of analyzing customer behavior to make strategic decisions.