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To achieve these goals, EPVA worked with CSC to undertake several projects. 1. Donor pro les. Create a sample of 400,000 records, with 100,000 in each of the following categories: Star donors Nonstar donors single donors Nonstar donors multiple donors Nonresponding rental les Use the demographic data available on these records to determine the pro le of these people, measuring their Gender Household income Age Housing type (own or rent and single family or multifamily) Ethnicity Presence of children Years at present address State Urban vs. suburban vs. rural DMA areas Occupation of head of household Education Marital status Number of adults in household 2. Create segments. EPVA planned to append Prizm codes to four groups of 10,000 each: Star donors Nonstar donors single donors Nonstar donors multiple donors Nonresponding rental les These data would help EPVA to determine which lifestyle groups were more responsive to the EVPA message than other groups. The results would be used for future list selection and donor mailings.
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3. Lifetime value. EPVA decided to use the data in its database to determine Which lists pull the best over the long haul. To do this, it measured the response rate of each list used over the previous 3 years, comparing the results to determine whether the contributions were going up, going down, or staying the same. The effect of frequency of mailing on the level of donation. To do this, it set aside a test group of 20,000 two-time donors and sent these donors only two mailings in the subsequent year. An exactly similar group of donors received four mailings. At the end of 1 year, EPVA could determine which group had the highest contribution. 4. Product analysis. EPVA decided to compare the performance of 50,000 star donors and 50,000 nonstar active donors to determine What was the product that brought them to EPVA in the rst place What products produced the best subsequent responses How did each group perform by product
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Many companies have had success with referrals. The idea is to get your existing customers to recommend that people that they are related to, work with, or know also become customers. In other words, your customers become advocates. They tell their friends what a wonderful company or product you have, and they get these friends to try your product. Once someone has become a customer as a result of a referral, something wonderful happens. These referrals who become new customers display, as a group, higher retention levels and higher spending levels than the average customer who is recruited by other means. You can prove this for yourself. First, you have to set up a formal referral program. Tell your customers about it, and make it easy for them to generate referrals by contacting a customer service rep or by going on the Web. Once you
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have a new name, address, and email name, it is your job to get that person to become a customer. However, you put the person s ID number into the referring customer s database record, and you put the referrer s ID into the referred customer s record. They are now tied together. You can now measure their retention and spending rates and their lifetime value. Let s say that you have done this, and you discover that your typical customer has a 3-year LTV of $70, whereas your average referral has a 3-year LTV of $100. What can you do with that information You can use it to create a special referral incentive program. America Online has done this. At various times, it has rewarded customers with $25 or $50 for recommending someone who also becomes a customer. This is a wonderful example of successful database marketing. There are two parts to the AOL story. In the rst place, AOL has to spend a lot of money to acquire customers. It places ads on TV, sends out CDs in the mail, puts CDs in tens of thousands of stores in POS displays, and recruits customers through partnership arrangements. This must be expensive. I would imagine that it costs AOL at least $100 to acquire a new customer. Once acquired, however, these customers pay AOL $23 per month forever. What is the marginal cost of servicing a new customer Not very much. Once you have the system and software in place, it is not that expensive to add a new customer perhaps $5 per customer per month. At that rate, AOL is doing very well if it is spending $100 to acquire customers who produce $18 in net revenue per month. Of course, some of these new customers do not stay. They cancel after a few months. This is true of all customers and all types of companies. That is where the referrals come in. Referrals are much less likely to cancel than people who are recruited by other means. Why Because they know someone who is on AOL the person who referred them. They may have joined to send that person email. They will some day have to face the question, Well, how do you like AOL They don t want to have to say, Well, I tried it, but I couldn t get it to work or I didn t like it or It was a waste of my money. They are not going to want to say these things to their friends. So they are more likely to remain as customers than people who have no such connections. For this reason, AOL can afford to give away a little money to acquire such people, and so can you.
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