Imputing unknown competitor marketing activity with a Hidden Markov Chain

Dominique Haughton, Guangying Hua, Danny Jin, John Lin, Qizhi Wei, Changan Zhang
2014 Journal of Direct Data and Digital Marketing Practice  
This paper demonstrates via a case study on two competing products at a bank how practitioners can use a Hidden Markov Chain to estimate missing information on a competitor's marketing activity. The idea is that, given time series with sales volumes for products A and B and marketing expenditures for product A, as well as suitable predictors of sales for products A and B, it is possible to infer at each point in time whether or not it is likely that marketing activities took place for product
more » ... The method is successful in identifying the presence or absence of marketing activity for product B about 84 per cent of the time. The authors allude to the issue of whether, if one can infer marketing activity about product B from knowledge of marketing activity for product A and of sales volumes of both products, the reverse might be possible and one might be able to impute marketing activity for product A from similar knowledge of product B. This leads to a concept of symmetric imputation of competing marketing activity. The exposition in this paper aims to be accessible and relevant to practitioners.
doi:10.1057/dddmp.2014.15 fatcat:2mftge5acjc37nxffwxy6osaua