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Opinion: making sense of customer value

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26th Jun 2007
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By Michele Eggers and Jeff Gilleland, SAS

If you Google the term 'customer value' you will get back 156 million hits. To put that into perspective, the term ‘customer relationship management’ has 36 million. It is one hot topic in marketing these days and has been referred to as the 'holy grail' metric to measure. However, many marketers feel it is an unreachable metric to calculate, measure and manage as a better indicator of customer ROI. This article will provide insights and thoughts on what customer value should consist of, and also provide you with an evolution model for adopting customer value without making you jump off the deep end.

When looking at customer value, you should consciously break it down into three distinct elements: current value (or current customer profitability), lifetime value (LTV) and potential value. Current value is a historical view of each customer’s profitability based on the products and services that they have consumed to date from your company. Lifetime value is an extrapolation of each customer’s current value into the future based on the products that they own today. And, potential value uses statistical techniques to estimate your customer’s propensity to grow more profitably by buying additional goods and services from your company.

Developing customer value metrics, like most endeavors, should be approached as an evolution. If you’re just getting your arms around implementing it, you might want to attack customer value in a five step model. First, focus on the basics. Keep the evaluation of customer value to a revenue-based metric based on the number of products owned by the customer. When determining current value, look at the revenues that you have generated from each customer in the past and present, whether that be annual fees, late fees or net purchases – depending on your industry.

"When determining current value, look at the revenues that you have generated from each customer in the past and present, whether that be annual fees, late fees or net purchases."

In the second phase, incorporate some costs – those that you are able to attribute to the customer level. The two core costs to try to incorporate initially would be service costs (eg customer service call costs, waived fees, return costs) and marketing costs (eg creative, print, fulfillment and call centre conversion costs).

When you’re comfortable with that, the third phase should also roll it up to the household level. Understanding customer value from the household perspective is an important step in understanding your overall relationship with your customers. The reality is that while each customer has their own individually calculated value, in many industries - like retail banks, insurance and brokerage - purchases are typically a decision for the household, not just the individual.

So, it’s important to have a pulse across all individual purchases in the household to see their overall value. And, even in industries where customer level valuation has stronger merit (eg retail, gaming), it’s still important to have an understanding of overall household value; especially in determining how to treat these individuals. For example, when calculating individual value scores, you may find a very high value customer and a negative value customer in the same household.

Sales capacity and marketing dollars

When looking at these customers separately, you may determine to retain and grow the high value customer and to price-up or out the negative value customer. However, these conflicting treatment tracks may result in losing both customers – which you don’t want to do! Hence, a household view enables you to look at all household members and develop a treatment strategy that makes sense.

"Why track customer potential as a separate metric from LTV? Because it tells you where to invest sales capacity and marketing dollars in order to have the greatest impact on profitability."

The fourth step is to calculate a lifetime value score for each customer. Recall from earlier, this is an extrapolation of the current value already calculated in the previous steps. LTV scores project future profits that you can reasonably expect without additional investment. You’ll need to determine the number of years to project, which typically is three years out. Your financial group will easily grasp and endorse the LTV calculations because these projections are based on current customer holdings, and tend to be more accurate than estimations of customer potential.

The fifth step is to develop a customer potential score. Adding this metric should be the last, and most value-adding, phase in the evolution model for customer value. This metric uses all available customer attributes and sophisticated statistical methods to calculate a customer’s propensity to grow more profitably through the purchase of additional goods and services. It calculates a customer’s propensity to buy each product currently not owned and the incremental profit that would be realised if purchased.

The metric then aggregates the incremental profit across multiple products (net of any cannibalisation that would occur from products currently owned). Simply stated, customer potential is an estimation of the incremental profit. Why track customer potential as a separate metric from LTV? Because it provides greater insight for incremental improvement and action – more specifically, this metric tells you precisely where to invest sales capacity and marketing dollars in order to have the greatest impact on profitability.

Now, there are other dimensions of customer value to consider that we don’t have time to dive into including the role that a customer’s credit risk and attitudinal needs play into a customer value model. But, we think this should give you an excellent starting point to make some sense out of customer value. And, in doing so, you should be able to reap more than 'pennies' in additional profits.

Michele Eggers is a customer intelligence product manager at SAS. Jeff Gilleland is a customer intelligence global strategist at SAS.
 

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