Once you have segmented your customers and identified your best customers – loyal, frequent shoppers who spend a lot – how do you find more like them? As direct and interactive marketers know, it’s easier said than done!
First, you have to identify the publicly available data that will actually help select likely prospects. Literally dozens of firms offer data elements to append to your file that will help you identify the available characteristics to select top prospects. The best of these sources offer behavioral data, often supplemented with demographics.
One great, generally available resource is the co-operative database, where direct merchants or retailers or non-profits pool their house files. These marketing databases receive data from members, combine it, and then construct models to identify best prospects that look like your best customers. They typically operate on a membership model. As a member, you pay a lower rate to rent prospect names, and non-members who operate in the same sector (retail, non-profit) generally cannot rent names unless they are members.
If you are marketing credit or insurance, you can obviously go to the granddaddy of all co-operative databases – the credit database. However, you can only access these great, behavioral resources if you are extending firm offers of credit or insurance and are prepared to operate under all the relevant legal restrictions.
Next, you analyze the data and possibly build a predictive model using the available data and appropriate statistical tools.
Finally, you select “look-a-likes,” either by using the most predictive selection criteria or by applying the model to a large database, ranking the prospects and selecting those that have the highest score.
Once you have those best prospect names, it’s important to extend your offer both to them and to a small “control group” of randomly selected consumers to see how well your selection criteria worked.