Targeting the poor student, by Merlin Stone

Within the political shenanigans in education lies a nice story of database marketing success. No, I’m not referring to the postcode lottery for secondary school places. Private sector marketers might regard that particular mess as resulting from lack of deployment of geographic information systems to analyse and forecast demand and – more importantly – from complete unwillingness to match resources to geographic demand patterns. Schools are very inflexible. Imagine a retailer saying "None of my branches should ever shrink. All my staff have an absolute right to stay in the branch which currently employs them".
My customers must spread themselves evenly between my stores to allow me to pursue this inflexible resource allocation policy.” We’d laugh. Sadly, however, it’s not the schools’ fault. They are not free to manage their resources, but are allocated resources by formulae that change frequently, at short notice, based on a logic impenetrable to them. So they get their allocations wrong. This is just poor marketing planning. No, I’m referring to the sector where I do some of my work, higher education. Before you wail with derision about declining standards, about the illiteracy of young graduates you recruit and about the poor quality of staff you have to deal with when you take students on assignment, let’s be honest about some of the facts. Education standards True, this is partly by letting lecturers’ real wages decline, but this reflects their lower average quality. However, the real marketing gain is that today resources chase students rather than the other way round. And while in most areas of database marketing, the chase for volume results in an unwanted decline in the average quality of customers, here it doesn’t matter! The quality decline is accepted. Let’s not be elitist either – hundreds of thousands of people who previously couldn’t get into university now can. Database marketing role In my short sojourn at Bristol Business School, I encouraged the University of the West of England’s External Relations Director to take this perspective one step further, and consider both school (and the recommenders within them) and individual applicants as customers. The analysis was stunning. It not only confirmed the same regional applications pattern that we had seen at Kingston, but more interestingly, massive exceptions. These were schools which given their profile (geographic, school type, size) ought to have been yielding far more applications but were only doing so in one or two subjects. Simple conclusion – this was probably due to careers teachers or subject teachers having particular views about the courses at Bristol. Policy conclusion – follow the classic direct marketing approach of “sailing with the wind”. First market intensively to schools in high propensity applications areas and with high applications in one or more subjects but not in others. Follow this by marketing to schools in those same high propensity areas but with low applications rates across the board. Then go to “new” catchment areas. The work could be refined by taking into account likelihood of the applicant to be accepted. There is no point targeting areas likely to yield lots of applicants who are unlikely to make their grades, except those in underprivileged areas that the government wants us to recruit. The next step is to include Finals success rates in the calculation. In higher education, many of the applications statistics are available to all universities. All competitors can see their “share of wallet” by school, by subject and so on. Using this data, the university can now decide where to send staff on schools liaison visits, where to send expensive prospectuses or cheap leaflets to, and whom to invite to open days. We’ll be publishing an article on this whole exercise later this year. All out effort Merlin | June 2003
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This month's column is reproduced with kind permission from Database Marketing, 2003.
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