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current rate of spending, the number of products that he owns, and the retention rate of his segment. There is something else that you can predict, however. You can look at all the additional products that you can sell to Arthur Hughes and estimate the increase in his lifetime value that would occur if you were to sell him each of several possible products. You can also predict the likelihood of his buying each of these products, based on the response rate of members of his segment when they are offered the products. You can draw up a table for each customer like that in Table 4-13. The most pro table product you could sell this customer would be product B, with a potential LTV of \$1200. But the product he would be most likely to buy would be product C, with a potential LTV of only \$300. Potential value is computed by multiplying the 3-year LTV by the probability of the customer s buying each product. Putting both together, it looks as if the next best product for Arthur Hughes right now is product C. If you can sell him that, then go for product E, which has the next highest total value to your company. Banks do this analysis today. The next best product is put into every customer s database record. Bank employees are asked to look at these records when they are communicating with customers so that they can discuss the next best product. This is using a lifetime value table to increase bank pro ts.
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Thus far, we have discussed the lifetime value of customers only. We have not discussed prospects. Of course, prospects have a potential lifetime value. How to go about determining this is covered in 13, Finding Loyal Customers. Table 4-13 Next Best Product
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Possible Product A B C D E Probability of Buying 45% 5% 85% 35% 20% 3-Year LTV \$ 400 \$1200 \$ 300 \$ 200 \$1000 Potential Value \$180 \$ 60 \$255 \$ 70 \$200
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One of the most powerful uses of LTV is internal to the company. Every marketing organization in every corporation has to come up before a inty-eyed chief nancial of cer every year to get a budget for its next year s activities. Before LTV analysis, this was not a very easy sell. Advertising can point to the colorful TV ads that it produces. Sales can point to the number of customers that were signed up last year and the number that are projected to be signed up in the year to come. What can marketing point to Here is where LTV comes into its own. In the Asian automobile case, the database marketing manager can come to the CFO and say, I can bring in \$56 million more pro ts during the next 9 years if I can have a budget for a welcome kit and a series of strategic customer communications. When asked to prove this statement, the marketer can trot out the projections shown in Table 4-7 and back them up with detailed tables like the ones shown in this chapter. Assuming that the presentation goes well, the CFO will retain these charts and refer to them in future budget sessions. She is likely to ask, What was your actual repurchase rate What were your actual marketing costs The great thing about LTV is that these numbers are all actual projections that can be audited by PricewaterhouseCoopers or Deloitte & Touche. They are not smoke and mirrors, but projections of real events that will actually occur and can be veri ed. Database marketing, therefore, becomes a combination of science and art. The art, of course, is thinking up the strategies that will produce the improved customer relationships, and hence the improved repurchase rate. The science is putting all these projections together in an LTV chart that makes sense and proves the value of your efforts.
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