Multi Stage Promotional Resource Allocation for Segment Specific and Spectrum Effect of Promotion for a Product Incorporating Repeat Purchase Behavior

Prerna Manik (), Anshu Gupta () and P. C. Jha ()
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Prerna Manik: Department of Operational Research, Faculty of Mathematical Sciences, University of Delhi, Delhi 110007, India
Anshu Gupta: School of Business, Public Policy & Social Entrepreneurship, Dr. B.R. Ambedkar University, Sector 9, Dwarka, Delhi 110077, India
P. C. Jha: Department of Operational Research, Faculty of Mathematical Sciences, University of Delhi, Delhi 110007, India

International Game Theory Review (IGTR), 2015, vol. 17, issue 02, 1-21

Abstract: Promotion plays an important role in determining fate of a product. It voices product qualities and persuades potential customers to make purchases. In todays diversified markets every customer has individual needs and preferences. This calls for market segmentation which facilitates companies to adopt customer driven marketing. Product is also promoted using mass promotion to influence larger markets and segments with a spectrum effect. Existing literature in promotion resource allocation optimization evades distinction in two types of promotion strategies while allocating resources and primarily focuses on either of them statically. In this paper, we formulate an optimization model which dynamically allocates differentiated and mass promotional resources in segments to maximize sales under budgetary and minimum market share aspiration constraint on each segment as well as on total market share including repeat purchase behavior. Planning horizon is divided into multi-periods, adoption pattern is studied in each period and then resources are allocated attuned to current market behavior. Dynamic allocation provides a way to track the market potential expansion due to promotion and plan the allocation for the uncaptured potential. The proposed optimization model is NP hard and very challenging to solve. Solution methodology is presented with practical application based on real-time data using differential evolution algorithm.

Keywords: Market segmentation; differentiated market promotion; mass market promotion; spectrum effect; dynamic promotional effort allocation; repeat purchase; NP-hard; differential evolution algorithm; durable technology product; innovation diffusion models; 68Q25; 93B40; 90C30; 68T20; 91B32 (search for similar items in EconPapers)
JEL-codes: B4 C0 C6 C7 D5 D7 M2 (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1142/S0219198915400216

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