Personalised marketing: improving evaluation

Abstract

This paper provides guidance to local authorities and others who may wish to apply a personalised marketing program in a given area and to measure the impact of such an intervention. 'Personalised Marketing' is used to describe a program aimed at changing people's travel behaviour by a combination of education, persuasion and provision of personalised information to either individual households or individual people. One of the best-known personalised marketing programs in Australasia and Europe is 'IndiMark' or 'individualised marketing'. Various personalised marketing demonstration programs have claimed substantial success in decreasing car use and increasing trips by alternative modes, thereby convincing some local authorities that such programs may be the 'panacea' to congestion problems in urban areas. Our recent involvement in helping to plan the evaluation of a personalised marketing trial in Birkenhead (Auckland, New Zealand) caused us to review the international experience with various trials and their evaluation. Our investigation is two-pronged: to learn to what extent we can guide 'pre-selection' of the area and participants/households for a personalised marketing initiative to learn from pitfalls in the evaluation of the impacts of such programs. The evaluation ('after') and elicitation surveys in Birkenhead highlighted the inadequacies of the current public transport system, providing evidence to support the widely-used pre-selection criteria of a 'good quality' public transport service being in place prior to the initiation of a personalised marketing program. Analysis of the 'before' survey data revealed characteristics distinguishing 'receptive' from 'non-receptive' individuals and households. Not only did the analysis reveal significant differences in personal characteristics and attitudes towards 'environmentally friendly modes', but also we found indications of pre-existing differences in mode use, which could confound potential evaluations of mode change after the intervention (e.g. as claimed in some analyses of individualised marketing in South Perth). Furthermore, great care must be taken with respect to the sample used for the evaluation. The statistical power to detect significant differences between before- and after-measurements is determined not only by sample size but also by the variability of behaviour. If people vary greatly in the number of trips driven and/or distance driven on a day-to-day or week-to-week basis (even in the absence of an intervention), then larger sample sizes (and/or longer data collection periods than the usual one-day trip diary) are needed. We used the 1997/98 New Zealand Travel Survey to estimate day-to-day variability in transport behaviour (both distance and trips, for several different modes). Results suggest that the sample sizes required are distinctly larger than seen in some recent research locally and that traditional travel diary methods may not be cost-effective for impact evaluation of many small pilot projects.

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