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The Tasks of Database-Marketing:
Selection of the right target-groupBoth, selecting the right target-group and selecting the target-group right is one of the very specialities and strengths of Database-Marketing, since with Database-Marketing selection of (potential) customers gets into a new dimension! Since the depth and quality of possible selections is only limited to either the data you have available on your database or that you can obtain from commercial providers, it is obvious that the "standard" segmentation of:
becomes obsolete. The more up-to-date techniques start from the other way round: instead of defining a target-group out in the big universe of the market you might wish to find out which customers are:
And all of these questions you could then break down by:
To help you with deciding which is your perfect target-group you may even set up some scoring sheets, which evaluate customers on a range of criterias. The most popular method (although I admit it is not the newest one) is the RFMR-method (Recency - Frequency - Monetary - Rating). Although originally developed within the mail-order business, you can easily adapt it to fit your companies needs. After having defined the scoring sheet, you simply let all the information you have about your customers run through it and calculate the according score. Afterwards you simply have to select the customers with the highest score - et voila: here is a high potential target group! Never forget that with Database-Marketing it is getting more and more easy to break down all of the above mentioned questions not only to product-lines but to a specific product or even a combination of products. You have answered all of the questions above - so what now? The next step where Database-marketing can considerably improve your marketing-performance is that you can now go out and find your potential customers within your database or go to a list-broker and have only addresses selected that really match your criterias. For example: As an advanced feature you might like to find also customers that only match to a certain perspect (i.e.: age, income, sex, ... matches perfectly, but geographic location is a bit to far away). From normal selection methods you would have "lost" these potential customers, but advanced techniques can help to find them too. |
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