How Customer Lifetime Value Drives Analytics

In the context of a service-based experience as a product, organizations look for metrics for assessing and quantifying the value of a customer over the duration of that customer’s relationship with the organization--otherwise known as customer lifetime value. This is particularly important in industries that compete for customer attention and commitment. An example is in the mobile telecommunications industry, which relies on a combination of customer purchases (of equipment) plus ongoing subscription costs (for monthly service).

The concept of “customer lifetime value” (or CLV) is a function of the various revenues and costs associated with maintaining a customer relationship. For our mobile telecommunications example, broadly speaking, a customer’s lifetime value comprises a combination of the costs and the revenues over the duration of the relationship, including:

These amounts have to be adjusted to account for the time value of money (that is, the discount rate), but for our current conversation we can ignore that. 

Let’s look at an instance of a specific category of customer who is a single individual who pays a $100 initiation fee, $200 every two years for a new phone (billed monthly over a two-year period) and a $40 monthly service fee each month.

Let’s also say that the company’s cost of acquisition bundles the amortized costs of advertising, marketing and sales, and that the bundle amounts to $25 per new customer. Finally, let’s say that the cost associated with servicing each customer is $1 per month. Using this simple framework, the value of a customer can be specified as the sum of the acquisition cost (AC) and the servicing costs (SC) multiplied by the number of months (m), subtracted from the sum of the initiation fee (IF) and (the monthly cost paid for the equipment (EC) plus the monthly service fee (SF)) multiplied by the number of months (m), or:

(-AC – (SC*m)) + (IF +((EC+SF)*m)

This table shows the calculation over different monthly durations:

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Note that this is somewhat simplified, since it does not account for attrition in the middle of a contract period or an equipment upgrade prior to the end of a two-year period, as well as many other potential scenarios. However, this simple model provides some visibility into anticipated revenues and profit margin for the company--it basically says that this type of customer is worth approximately $688 per year. Get 10,000 customers like this, and you can suggest that they represent annual revenues around $6,680,000.

Of course, reality is not that simple for a number of reasons:

From an analytics perspective, customer lifetime value is important because it provides a frame around how analytical models are used.

In essence, customer lifetime value is a double-edged sword, as the outcomes of customer lifetime value-oriented analytics activities will end up driving organizational decision-making (such as allocation of advertising budget by market segment) and influencing customer behavior (through targeted actions facilitated through personalization).