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Successful businesses are driven by growth in revenue and, ultimately, profits. This is the case across industries and regardless of the size of the business. And as a result, most companies focus on year-end revenue goals, based on a desired growth rate. Translating this goal into daily action—in a way that is meaningful across business units and positions—is challenging. The tendency is to take note of the ultimate goal at a yearly review, then return to a lengthy list of tasks already in process.

To bridge this divide, secondary business goals must be established—and these goals must be connected to metrics that are meaningful and, more importantly, can be influenced by every part of the business. One of the classic—and commonly used—example of such a secondary metric is “customer lifetime value.”

Put simply, customer lifetime value is an estimate of the present value of predicted cash flows expected over the entire customer relationship. Calculating this value precisely can be complex and will vary significantly across industries and between businesses. A basic equation, however, considers average monthly revenue per customer, margin per customer, and retention rate (calculated as 1 –churn rate). The relationship between these variables is illustrated as:

Once this value is established, it’s easy to estimate the value of each additional customer that is created—and this is often how the metric is implemented. But investing resources in customer acquisition is not without cost. This may seem obvious but one overlooked element is that these acquisition costs have a direct impact on customer lifetime value. More accurately, the relationship should be illustrated as:

In this example, customer acquisition rate is the total expenditure on acquisition activities including advertising, direct mail, PR, discounts and promotions, and so on, divided by the total number of new customers (those that actually make a purchase) added.

Where does testing and optimization fit in?

If a testing program is up and running smoothly, it could safely be considered a fixed cost in this context. In other words, the cost of testing does not increase as each new customer is added. Most businesses, however, plan to expand the size and scope of their testing program. If this is the case, the cost of expansion could be divided by total number of customers (i.e. users positively impacted by the program) to generate a metric of testing cost per customer. Adding this element to our illustration produces the following:

With the illustration complete, we can see that the presence of testing and optimization impacts the relationship in three important ways. Even when considered as a cost, the effect of testing:

1. Increases acquisition efficiency

Given the same level of costs, testing and optimization improves the value of customer acquisition by converting more curious users into paying customers. For those doing the math at home, this leads to a larger denominator in the acquisition calculation and, as a result, a smaller product subtracted from the total value.

2. Increases retention rate

Testing can also be used to increase the number of customers that return to make additional purchases. This will effectively decrease churn rate, leading directly to a higher lifetime value.

3. Increases average revenue per customer

Testing and optimization is very commonly used to increase average order values and, as a result can contribute directly to this critical factor in the lifetime value calculation.

Clearly, testing and optimization presents a versatile, effective means of increasing a critical metric that ultimately contributes to increases in total revenue and profit. More importantly, it provides strategic direction for both optimization efforts and marketing strategy in general—and illustrates an opportunity that is too good to ignore.