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How Customer Lifetime Value Drives Analytics

Customer lifetime value provides a frame around how analytical models are used.

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:

  • The cost of acquiring the customer
  • The ongoing costs of servicing the customer
  • The price that the customer pays to initiate the relationship
  • The amount that the customer pays for equipment during the relationship
  • The periodic subscription charge for the service

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:

Screen Shot 2020-07-22 at 1.22.28 PM.png

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:

  • There are additional variables that need to be considered in maintaining the relationship, since there are always risks that the customer will discontinue the relationship. This introduces additional costs for customer retention.
  • Not all customers are homogeneous. There are going to be different categories of customers. For example, some customers represent a single subscription, while others represent multiple subscriptions (for example, a family plan for multiple telephone lines).
  • Customers may change over time from one category to another, either by changing preferences for the volume of service or type of equipment, which changes the revenue stream.
  • In some situations, the customer lifetime value deteriorates over time. Even in our example, because of the $100 initiation fee, the value of a customer during the first 12 to 24 months is higher than the value of that same customer over subsequent periods.
  • To accommodate for some of that value deterioration, organizations may introduce additional incentives to augment or expand the relationship.
  • This model does not account for some less-tangible aspects of a relationship, such as the degree of influence in streamlining new customer acquisition. For example, customer “word of mouth” is often underestimated in its contribution to customer lifetime value.

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). 

TAGS: Big Data
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