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Decoupling the individual effects of multiple marketing channels with state space models

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Artificial Intelligence and Machine Learning in the Travel Industry
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Abstract

An important problem in marketing is understanding the impact of various marketing efforts on sales and revenue. If specific measures have not been taken before hand to distinguish responders across the various marketing initiatives, it becomes increasingly difficult to assess the effectiveness of investment across individual marketing channels. We present State Space model to estimate the individual channel effects using aggregate sales or response data across all channels. The proposed framework allows for varying carry over effects across marketing channels. Also, the proposed framework allows for differing rates of decay across marketing channels. We demonstrate its use when data on sales due to individual marketing channels is not available and only aggregated sales data are available. The proposed State Space modeling approach offers the advantage of: (1) allowing for varying rates of decay across marketing channels, and (2) allowing for a natural way of modeling time series dynamics. The approach also opens the way for more comprehensive marketing-mix optimization by allowing varying rates of decay.

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Correspondence to Melvin Woodley .

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Woodley, M. (2023). Decoupling the individual effects of multiple marketing channels with state space models. In: Vinod, B. (eds) Artificial Intelligence and Machine Learning in the Travel Industry. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-25456-7_4

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