Purpose - To demonstrate the successful use of lifestage segmentation and survival analysis to identify cross-selling opportunities. Design/methodology/approach - The study applies lifestyle analysis and Cox's regression analysis model to behavioural and demographic data describing 10,979 UK customers of a large international insurance company. Findings - There are clear differences between the lifestage segments identified with respect to customer characteristics affecting the likelihood of a second purchase from the company and the timeframes within which that is likely to take place. The "mature" segments appear to offer greater opportunities for retention and cross-selling than the "younger" segments. Research limitations/implications - The study was limited by the type of data available for analysis, which related mainly to life insurance and pension products characterised by low transaction frequency. Different results might be expected for banking or credit-and-loan products. The findings could be enhanced by incorporating a wider range of customer characteristics into the analysis. Practical implications - The findings show clear differences in behaviour across the segments identified, providing a basis on which marketing planners might differentiate marketing and communication strategies for particular products market segments. Originality/value - The paper illustrates the adaptation of survival analysis methodology, familiar in other disciplines but comparatively rare in marketing, to the cross-selling of financial services. It shows how planners cannot only identify customers most likely to repurchase but also predict the timeframe in which that will take place.
机构:
Ajou Univ, Dept Artificial Intelligence, Worldcup Ro 206, Suwon 16499, South KoreaAjou Univ, Dept Artificial Intelligence, Worldcup Ro 206, Suwon 16499, South Korea
Yun, Siyeong
Cho, Woojin
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Ajou Univ, Dept Artificial Intelligence, Worldcup Ro 206, Suwon 16499, South KoreaAjou Univ, Dept Artificial Intelligence, Worldcup Ro 206, Suwon 16499, South Korea
Cho, Woojin
Kim, Chulhyun
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机构:
Induk Univ, Dept Ind & Management Engn, 12 Choansan Ro, Seoul 01878, South KoreaAjou Univ, Dept Artificial Intelligence, Worldcup Ro 206, Suwon 16499, South Korea
Kim, Chulhyun
Lee, Sungjoo
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机构:
Seoul Natl Univ, Dept Ind Engn, 1 Gwanak Ro, Seoul 08826, South KoreaAjou Univ, Dept Artificial Intelligence, Worldcup Ro 206, Suwon 16499, South Korea