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Journal of Advertising Research
Int. Journal of Market Research
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The Marketer's Dilemma: Focusing on a Target or a Demographic? The Utility of Data-Integration Techniques
Includes video content
Recommended by Warc editors
Mike Hess and Pete Doe, Journal of Advertising Research, Vol. 53, No. 2, 2013, pp. 231-236
Data-integration techniques can be useful tools as marketers continue to improve overall efficiency and return on investment.
Data-integration techniques can be useful tools as marketers continue to improve overall efficiency and return on investment. This is true because of the value of the techniques themselves and also because the current advertising market, based on demographic buying, has major opportunities for arbitrage in the range of 10 percent to 25 percent (where in that range depends on the nature of the vertical). The current study reviews different methods of data integration in pursuing such negotiations.
An approach to fusing market research with database marketing
Includes video content
Recommended by Warc editors
Barry Leventhal, International Journal of Market Research, Vol. 39, No. 4, 1997
This paper discusses the ways in which market researchers can work with databases within the guidelines set by The Market Research Society whereby respondent confidentiality must be maintained.
This paper discusses the ways in which market researchers can work with databases within the guidelines set by The Market Research Society whereby respondent confidentiality must be maintained. It describes an approach used in the financial sector, which combines customer transactional data with market research on the same individuals. The development presented uses NOP's Financial Research Survey (FRS), a continuous monitor of financial holdings, which is undertaken on the back of the NOP Random Omnibus. A segmentation was developed, known as FRuitS, which classifies adults 18+ according to their likely use of financial services. In order to map FRuitS onto an organisation's customer base, the FRS and customer databases are matched at an individual level to extract a sample of customers who also responded to the FRS. The logistics of the matching process are designed to protect the confidentiality of both data sources. Case study examples are presented.
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