Customer Valuation (or modeling customer value) is a process to predict the future profitability or value of a customer, today.


Instead of targeting all prospects equally or providing the same incentive offer to everyone, you select only those individuals that meet specified profitability thresholds levels based on previous purchasing behaviour, demographic, life-style, or psychotropic data.

Predicting the value of a customer can be an important part of deploying marketing campaigns. Two prospects may both have the same percentage of responding to your offer, but prospect "A" might generate $10 in profits while prospect "B" might generate $50 in profits. While the cost of acquiring each prospect might be the same, the impact to the bottom line is very different.

Predicting the value of future purchases will help you identify which prospects are most likely to respond and are most worthwhile targeting. Similarly, if you build an attrition model to identify those customers at risk for leaving your business (churn), a customer valuation model can identify those customers that are worth trying to salvage through a retention program.


In addition, the life cycle of customers typically varies greatly. That is, upon customer acquisition, the marketer may actually experience a net financial loss while expecting to recoup their losses and more over the lifetime of the customer. For example credit card companies spend money setting up an account, generating a credit card, mailing the customer numerous brochures etc. If the credit card holder never activates his/her card, or seldom uses it to charge purchases, or deactivates the card soon thereafter, they may not be profitable customers. Valuation models can help predict the spending levels of consumers at different points in the life cycle or lifetime.

Using a valuation model, you can:
Use available date to predict the spending levels of prospects and to target acquisition campaigns at the most profitable ones
Use purchase history and other information for old for "old" customers in your database to predict the future Lifetime Value of more recent customers.
Identify and demonstrate appreciation (e.g., by implementing a preferred customer program) towards those customers who are predicted to generate the most profit.
Target retention programs at the profitable customers who might be at risk I of churn or attrition and give an incentive or special offer of the appropriate "value" relative to their future profitability.
Rank your customers by predicted value and then implement up sell programs to improve profitability of your second tier customers. Or, implement different marketing programs to increase profitability of your currently least valuable customers, as a new area for expansion of Lifetime Value (LTV)

A simplified definition of LTV can be expressed as:
LTV = Frequency of purchase x Gross Margin x Duration
This equation basically says that a customer's lifetime value can be determined by their frequency of purchases times the gross margin or profit associated with such purchases times the length of time that customer remains loyal to your business.


The benefits of customer valuation are:
Early identification of customers predicted to be most profitable over the long term.
Identification of upsell prospects/opportunities.
Identification of probable churn customers.
Improved return on investment (ROI*) for marketing dollars.
Improved preferred customer programs and customer retention.

Return on investment (ROI) is a widely used measurement of investment effectiveness. It is typically computed as a ratio of generated profit (return) over the cost of program implementation (investment). A value of one presents a break-even campaign. Value greater than one represents a profitable campaigns and values less than one mean losses were incurred.
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