This case study explains how we were able to help a client to ensure that their leaflets were distributed to areas where people would be most receptive to the service they were offering. It shows how careful targeting can improve response rates and also help minimise wastage.
We recently completed a job for a company who help people with financial difficulties to release capital from their house. This job was interesting from the perspective that the client was keen to distribute 10,000 leaflets into a specific geographic area based on her ‘gut feel’ and local knowledge.
We used a combination of our residential address database and mapping software to identify an area that had 10,000 houses in it. We were, however, concerned that the area was too wide and would not contain a high percentage of people who were in her target market, resulting in a high level of wastage. A typical example of this can be found in our case study about targeting the wrong audience.
After discussion, we agreed that it would be a good idea to run a demographic analysis on the area in order to identify the areas where people who would be interested in her service would be most likely to live.
The starting point was to understand the what their ideal client ‘looked’ like. For this client, this was a relatively straight forward process. They were looking for people who owned their own home and were likely to have high levels on indebtedness.
We ran these (and a few other) criteria through our demographic analysis system and used the resulting information to identify the most appropriate targets for the client. This was done by analysing each of the demographic types identified by our system and extracting the the percentage of people who owned their own house, the percentage who had CCJ’s (Count Court Judgements) against them and their CII (consumer indebtedness index).
Using these three pieces of information, we were able to create a weighting for each demographic type which allowed us to identify those that were a very good match, a good match and a reasonable match. It also enabled us to exclude those types that did not provide a good match.
The types identified in each of these three categories were plotted on a map of the area that the client wanted to target. This enabled us to identify the specific areas that were most appropriate for the client and resulted in 5,000 leaflets being distributed as opposed to the original estimate pf 10,000. Using this demographic analysis enabled us to save the client the cost of printing and distributing 5,00o leaflets to people who would had had no interest in their service.
The client was very pleased with the response they got from this leaflet distribution and we and now working with them on identifying the next area to be targeted.
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