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Assumption 1: Why People Buy Things
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Let s see why none of these assumptions proved to be correct. In the rst place, why do customers and prospects decide to buy something You can come up with lots of answers, but the key answer is that they decide that owning the product or service at a particular time will make them happier than not owning it. What happiness consists of is de ned by the person who is trying to possess it, and it varies from person to person and from time to time. I like Big Macs, but not all the time. Sometimes I like sh, sometimes I like chicken, and quite often I like home-cooked vegetables. There is no way that you can accurately predict what I will want to eat next unless you know what I ate last, how hungry I am, where I am at the time, whom I am with, and how much money and time I have available right now for eating. There is no way that any data warehouse could ever collect such timely and relevant information or that anyone other than the customer could accurately weigh the importance of each piece of information. The same principle applies to predicting my interest in taking a trip, buying clothing, buying a car or an appliance, or taking a college course. You can collect some relevant information, but you cannot collect enough to make accurate predictions concerning what Arthur Hughes will do today. What you can say with some accuracy is that people in Arthur Hughes s age and income group who have similar purchasing habits are more likely to buy a certain type of clothing or insurance policy than the average person picked out at random. But of course, that is not CRM or one-to-one marketing. That is regular database marketing, where you are targeting segments. You don t need a data warehouse for that. You need only a database (which can be built for a fraction of the cost of a data warehouse) that permits dividing the customer and prospect base into purchasing segments.
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What is the difference between database marketing and CRM They are both based on databases of prospects and customers that are used to guide marketing and sales strategy. CRM requires
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a large data warehouse with costly software, aimed at determining and in uencing the behavior of individuals through one-to-one marketing. Database marketing is based on a data mar t, which costs about 10 percent of the amount required for a CRM warehouse. Database marketing is usually aimed at identifying customer segments and marketing to them, and also building one-to-one relationships with existing customers through loyaltybuilding communications. To see the difference, think of 100,000 customers on whom you have data. With database marketing, it might be possible to predict with 75 percent cer tainty that 40 percent of a cer tain segment of those customers will buy product X within the next month. But you cannot be 75 percent cer tain that Ar thur Hughes (a member of the segment) will buy the product next month or ever, for that matter. The rst conclusion comes from segment analysis using database marketing. The second conclusion would come from CRM if it could be made to work. Unfor tunately, it cannot.
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We should note here that there has been a corruption in terminology. Many companies are practicing database marketing, but are calling it CRM because that sounds more modern and up to date. They don t have a data warehouse. They don t have million-dollar software. They don t really even attempt one-to-one marketing. They have just built a modest data mart and are creating marketing segments and marketing to them. They call what they are doing CRM, but it is really plain old database marketing, which works wonderfully in the right situation.
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