# Customer Lifetime Value: A Framework for Assessing Marketing Resource Allocations

### Contributed by Ivan Ruzic, Ph.D.

­­­­­­­­­­­­­­­­­­­­­­­­­­­

Conventional accounting has long viewed marketing expenditures as costs and not as investments in intangible assets. However, it is demonstrable that the value of a firm is linked to expectations of future performance. Therefore, resources allocated to marketing efforts should really be seen as investments in assets that can be leveraged to enhance the company’s future performance.

Viewed this way, expenditures on developing market-based assets only make sense if the sum of the discounted cash flows generated by these marketing efforts is positive. Clearly, a framework is needed that allows the estimation of these discounted cash flows and assessment of whether these investments make sense.  The concept of Customer Lifetime Value (CLV) is such a tool.

Customer Lifetime Value is defined as the sum of the lifetime value of a present and future customer. It is calculated by projecting the net cash flow that a company expects to receive from a customer over time and then discounting that stream to its net present value.

There are several different and equally valid ways of calculating CLV.[1] The following is one of the most common formulations. To simplify calculations, this formula assumes that customer margins and customer retention rates are constant over time, in which case Customer Lifetime Value (CLV) can be calculated as:

CLV\$ = Margin\$ x Retention Rate % / (1 + Discount Rate % –   Retention Rate %)

• Margin\$ is the average revenue per customer minus operating expenses divided by the number of customers.
• Retention Rate% is the ratio of customers retained in a given period divided by the number of customers at risk.
• Discount Rate% is weighted average cost of capital.

Two Examples of CLV

As an example, let’s calculate the CLV for an online backup service that charges \$12.50 per month. Variable costs have been calculated to be approximately \$1.50 per month per customer, average weighted cost of capital is 1%, marketing spend is \$6 per year and customer attrition is 0.5% per month.

Contribution Margin = (\$12.5-\$1.5-\$6/12)=\$10.50

Retention Rate = 0.995Discount Rate = 0.01

Then CLV\$ = \$10.50 x [0.005 /(1 + 0.01 – 0.995)] = 10.50 x 66.33 = \$696.46

The time dimension for the lifetime calculation is implicit in the way that the retention rate is derived. The lifetime period can be twelve months, five years or some other value. What is important is consistency in measurement. Note that in the above example, everything was reduced to a per month basis.

Here’s another example. This time, we will examine the credit card issuances of five different banks (Table 1) and use CLV to gain insight into their operations. CLV has been calculated using the above method, with the table ordered from smallest CLV to the largest.

Simply by plotting the column variables against CLV we quickly find that CLV has a very strong correlation with both customer retention rate and contribution margin (Figure1).

#### Figure 1: X-Y Plots of Credit Card CLV against Customer Retention Rates and Contribution Margin for Five Banks

We can now run a quick sensitivity analysis on any of the banks to look at the potential impact of programs that may increase either customer retention or contribution margin. Using Bank A as an example, we see that it has the highest customer churn rate (over 50%) and the lowest customer lifetime value.  A quick “what-if?” calculation demonstrates that a 5% increase in the customer retention rate for Bank A increases CLV by almost 10%. This is a significant payoff deserving the attention of management.

Applying the CLV

There are numerous marketing applications of CLV, including the following:

• Market segmentation: By measuring customer value regularly and consistently, companies can rank customer importance and use this ranking as the basis of value-based segmentation. The result is a rigorous approach to allocating resources and fine tuning different levels of both communication and service to different customers or customer groups. For example, if a customer complains about a problem, a simple CLV index or an individual CLV score can help front-line employees decide what action to take immediately and how much effort to invest in solving the problem.
• Strategy evaluation: Assessing the potential impact of (a) targeting different customer groups or segments, (b) alternate market budget allocations, (c) differences in pricing policies, (d) differences in customer retention rates, and (e) different sales channels and loyalty programs can be rooted in CLV.
• Developing customer retention programs: CLV serves as the ultimate basis for developing customer loyalty programs and can serve as an early warning system to detect unexpected customer churn rates.
• Fine tuning marketing campaigns: As a general rule, the highest profitability results from investing the marketing budget in campaigns that focus on customer groups, potential customer groups and groups of defected customers with above-average CLVs. For example, CLV can be used to selectively reactivate inactive customers by focusing on those whose CLV is potentially above average. Similarly, cross-selling campaigns can be targeted at customers who have been defined and selected using CLV.

However, once operationalized, the CLV concept also has much broader utility within the organization. For example, consider:

• Augmenting conventional company objectives and monitoring performance: For example, “increase sales by 10% per year and also increase Customer Lifetime Value by an equivalent amount.” Because it is closely aligned with shareholder value, it provides a more useful measure of a company’s economic development than sales alone. Further, it helps shift the focus from short-term financial performance to the long-term value of customer relationships.
• Sales force management: CLV can be used to (a) help determine which sales districts require additional attention, (b) allocate sales resources, (c) reward sales agents (for example, a higher commission for selling to customers with a higher potential CLV), (d) manage sales competitions and sales performance (for example, rewarding the sales agent with the highest number of total customers instead of the highest annual sales), etc.. It can also be used to determine win-back priority. Research has shown that a customer often has a different CLV before defection and after recovery (win-back), with the second CLV frequently being better than the first.
• Company valuation and screening of M&A candidates: If a company can calculate CLV for its customer groups (potential customers, existing customers and defected customers), it can develop an exact picture of its market position and its existing customer base. These figures may then be incorporated as part of a business case supporting a company’s valuation. In a similar manner, CLV can also be used to support a business case for the merger between two companies, as mergers often influence both the customer acquisition rate and the customer retention rate.

Conclusion

This article has briefly explored a useful conceptual framework for understanding the relationship between shareholder value, market-based assets and the allocation of marketing-specific resources. It has also looked at the central role played by customer relationships in operationalizing Customer Lifetime Value, a powerful tool at our disposal for better understanding these vital relationships.

Calculating CLV provides many advantages. First, in a general sense, it aids in developing a thorough understanding of the potential value of customers.  Second, it helps develop profiles for desirable customer groups that can then be leveraged in customer acquisition efforts.  Finally, CLV helps differentiate between the values that different groups of customers bring to an organization and provides a consistent way of managing the existing customer base.

CLV is a sound basis for developing optimal strategies for each customer group, reducing costs and creating long-term perspective of the potential relationship with different groups of customers.