How to Calculate Lifetime Value of a Loyal Customer

Do you know how to calculate the lifetime value of a loyal customer?

Marketers often discuss the lifetime value of a loyal customer as a key metric to compare alongside customer acquisition costs, retention & churn rate.

In this article, we'll walk through the process of calculating lifetime value using what's known as 'simple lifetime value' equation.

To begin with, I need to establish a few definitions:

1. Customer Lifetime Value: The total profit or loss seen from an individual customer over the 'life time' of their use of your product
2. Customer Acquisition Costs: Dollar amount your brand invests to acquire a single customer
3. Customer Retention: The percent of customers retained against the number of customers that approached you for a cancellation of service
4. Churn Rate: The rate at which customers churn, or cancel use of your service, over a specific period of time

Now that we have defined a few of the key terms to be discussed in this article, let's all step back for a moment and ask a question:

How is your brand actually measuring the full lifetime value of your loyal customers?

We examine three key factors to measure customer lifetime value:

1. Ability to measure across devices & marketing tactic
2. Understanding anonymous vs. known users
3. Tools needed to tie these points together

Factor #1: Measuring Across Devices

In this day and age, one of the biggest tasks involved in measuring lifetime value is: Capturing and measuring lifetime value across devices is most commonly performed through aliases Let's walk you through an example of creating and integrating aliases:

1. Your website provides an anonymous identifier, "user123" for example, each time a unique individual visits from a new device (iPhone, iPad, PC)
2. When the anonymous user finally signs in, using an email form for example, they authenticate themselves
3. As the user continues to sign in across devices (iPhone, iPad, PC) using their email address, that authentication process brings the disparate aliases together to create a complete picture of that individual user

Factor #2: Measuring Across Marketing Channels

Building on Factor #1 (Measuring Across Devices), it's equally important to understand the lifetime value of the marketing channel that drove each user to originally purchase your product or service.

For the sake of argument, let's discuss channel measurement in terms of last click attribution (as opposed to multichannel attribution).

Using aliases & authentication, you can measure individual customer value down to the unique marketing channel that drove customer acquisition in the following format:

• Customer Acquisition: How much investment did it take to acquire that customer originally?
• Retention Rate: Did she stay a customer following a free trial / initial sign up period? Or ...
• Churn Rate: Was she part of the percent of users who cancelled their service following sign up?

Factor #3: Tools Needed

Your brand is ready to begin measuring customer lifetime value: Fantastic! Let's outline a short list showing of the  type of tools you'll need as well as a few examples of vendors that provide these capabilities:

• Web Analytics: A web analytics tool will allow you to create goal conversions & events to measure site engagement, marketing channel performance and product purchases. Examples of web analytics tool include Google Analytics, Omniture & WebTrends
• Data Management Platform: A data management platform provides you with the ability to create aliases, store anonymous customer data & integrate known customer data points for users who have authenticated. A low-fi (yet powerful) example of an aliasing tool is KISSmetrics, while a more robust data management platform like x+1would provide more customer data storage & usage capabilities

A Sample Calculation of Customer Lifetime Value

Now I'll caveat this calculation up front: There are a  number of ways to calculate customer lifetime value.

I'll just walk through what's known as 'Simple Lifetime Value' equation.

First up, let's get some definitions established:

• (span) = Average number of years customers remain loyal to 'Client XYZ'. For this example, let's assume average span is 20 years
• (revenue) = Measured in months, this is the revenue the individual customer spends on your product. Let's assume your product costs $20 per month
• (months) = measurement on an annual basis. Just as a reminder, there are 12 months in a year

Let's walk through a sample equation:

(months x revenue) x span

Now when we fill in some data pulled from the 'Client XYZ' archives:

(12 x $20) x 20 = $4,800 There you have it: Client XYZ's average lifetime customer value is $4,800.

Your turn! Try plugging in your own company data into the model outlined above and see what comes out!