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was in a secular uptrend during most of the testing period. Profitability continued out-of-sample, from 1993 through 1996, with a 265% return, 23 trades (30% profitable), and with an average trade yielding $891.30. The results for Wheat were also good across samples. In-sample, 57% of X4 trades were profitable with a $203.27 average trade and 859% return (not annualized). Out-of-sample, there were 29 trades, 55% profitable, a $260.78 average trade, and 406% return. Our initial research suggested further study would be worthwhile. The tests below examine the effects of solar activity on the standard portfolio. Daily sunspot numbers from 1985 through 1999, from the Royal Observatory of Belgium, were used to generate entries.

We can look at the LTV of women versus the LTV of men We can look at the LTV of people living in the Northeast versus those living on the West Coast We can look at the differing LTVs of white, black, and Hispanic owners Where do we stop in our calculations We have to consider two things: 1 Do the demographics result in signi cant differences 2 If so, can we use these differences to craft different relationshipbuilding strategies that will improve the repurchase rate The rst question can be answered in short order by an analysis of the database going back 6 years We can tell pretty rapidly whether older.

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people have a higher repurchase rate than younger people, whether there are differences between whites and blacks, whether there are differences between East and West, and so on. In most cases, there will be only marginal differences, so we forget about those factors. You will have to look at the numbers to decide whether you can create a marketing program that recognizes and uses the differences. For each possible program, we have to decide whether the cost of the program will be suf ciently low and the bene ts suf ciently high for the resulting LTV to actually go up when the programs are put into place. In many cases there is little we can do. There are more possible database marketing programs that drive LTV down than there are that drive LTV up. That is part of the reason why CRM has been such a failure in so many industries.

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Once we have LTV in everyone s database record, we can begin to think about segmentation. We have already segmented customers by model and year, and we may also have segmented them by demographics. One important segmentation method is by total value to the company. We can arrange all customers by LTV from top to bottom and create segments that we call Gold, Silver, Bronze, Steel, and Lead. Our Gold customers are the most valuable ones. They have the highest lifetime value. They probably own more of the company s products, and they have a higher spending rate and retention (or repurchase) rate. They are cheaper to serve, and they tend to buy higher-priced options. They are less pricesensitive than other segments. We really want to retain these Gold customers. We must devise programs to keep them coming back for more. We will add their segment designation to their database record so that we can recall them easily when we want to communicate with them.

E vitamins, 40, 51, 78 79 Eat, Drink and Be Healthy (Willett), 70 Ellagic acid, 94, 97, 174 Environmental Health Center of Dallas, 213 Environmental Health Perpectives, 28 Environmental Protection Agency, v, 20, 27 Environmental Protection Agency s Safe Drinking Water Hotline, 214 Enzymes, Phase I, 9 10, 99 Enzymes, Phase II, 9 10, 99 Epigallocatechin gallate (EGCG), 96 97 Eppley Cancer Research Institute, 27, 98 Ericaceae, 43 Esophageal cancer, 99, 100 Essential fats, 52 55 Estrogen, 6 Exercise, physical, 34 36, 74, 140

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Most companies have more than one product that they can sell to their customers. Statistics from a variety of industries, such as banks, insurance, and travel, show that the retention rate is often a function of the

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number of products owned. The more of a bank s products you own, for example, the less likely you are to drop the bank s credit card when you receive a competing offer. Because of the importance of multiple product ownership, many companies have put major resources into selling their customers a second product not only for the pro t they make from the second product, but also because the second product shores up the retention rate for the rst product. Since multiple product ownership is important, when you create a LTV table, you can segment customers by the number of products owned and create separate retention rates, and hence LTVs, for owners of multiple products. The chart that a bank developed is shown in Figure 4-1.

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