Customer Value Measurement and Optimization

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Understanding customer value tiers is critical in developing programs to preserve or increase the value of the customer portfolio.

The customer portfolio is a firm's most important asset, yet most companies don't have an effective way of measuring the value of their customers. Many marketing executives see the need for measuring customer value but usually give up on the idea because of the operational and organizational challenges associated with creating a value metric with universal buy-in across the enterprise. Others waste months debating how to come up with a perfect statistical methodology that will enable them to create a customer value score.

On the other side, there are examples of marketing organizations that have been successful in creating and operationalizing a value metric across the enterprise. One telecommunications company, for example, learned that 50 percent of its customers capture nearly 90 percent of the entire customer portfolio value whereas 8 percent of the customers have negative value, indicating that they are hurting the overall profitability of the company. The same company developed the capability to score each unique customer using a value model, and now formulates marketing decisions according to the value of different customer segments. For example, most valuable customers, also known as Hidden Heavies, get prioritized ahead of other customers when they call customer service; they also receive the most attractive retention offers.

How to measure it?

A consistent definition of a customer lifetime value (CLV) metric is critical in quantifying the value of the customer portfolio. CLV is defined as the total value of a customer captured during his entire "length-of-stay." It's the measurement of customer's time-discounted cash flow over time and includes both the life-to-date value and future value. A starting point of customer value is existing customers, but it's possible to develop statistical models to map the value scores to prospect populations. These prospect models can inform the media targeting decisions for precision media such as direct mail and email, as well as mass media such as TV and radio.

The followingexhibit shows a conceptual framework for the calculation of CLV.

Going beyond transactional value

Besides transactional value, there are other components that should be considered in calculating customer lifetime value. The first component is engagement value, which is based on non-monetary activities such as website visits or social media activity that ultimately tie back to the transactional value. The second component is referral value, which is generated through new customer referrals or influence.

There are also advanced methodologies to measure CLV dynamically by incorporating information about customers' attitudes. These analytics frameworks reflect the continuous learning about a customer base and update the value information pertaining to customers' attitudes towards the firm. After obtaining the customers' transactional and attitudinal information in each period, companies can develop proactive marketing actions to interact with the "right" customers so that CLV is maximized.

How CLV enables program development and optimization

CLV has become one of the most popular metrics for customer relationship management. Measuring CLV accurately is the key to success in segmenting customers, which enables the creation of many acquisition, customer management and retention programs. CLV allows marketing organizations to develop programs that are differentiated based on the different value segments. As a result, higher value customer segments get different marketing treatments than lower value segments.

There are two specific practical applications that apply to customer and prospect populations. On the retention front, companies can use the customer value metric to identify what best customers look like and re-focus customer marketing investments where they have the largest impact to incremental CLV. In addition, loyalty and retention strategies can be developed based on best customers that contribute most to the overall portfolio value. On the customer acquisition side, new prospecting strategies can be developed to deliver more best customers. Value scores can be used to refocus marketing efforts in specific new customer acquisition strategies will acquire the greatest amount of customer value.

Conclusion

Companies don't need a perfect or all encompassing CLV score to incorporate customer value into their marketing strategies. A simple yet universally accepted robust value score could be a great starting point for many organizations. Understanding the value differences across customer value tiers is critical in developing programs that preserve or increase the value of the customer portfolio. The customer value metric and its resulting benefits also show shareholders the health, stability, and long-term value of an organization's customer base and make the connection to the overall firm value.

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About the Author: Ozgur Dogan is the co-leader of the Quantitative Solutions Group at Merkle

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EXPERT OPINION