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

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.

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

“…Quite a few researchers have worked in the area of promotional resource allocation [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Davis and Taylor III [7] formulated a goal programming problem for allocating a state's promotional effort to specific regions of the country based on the tourism potential of those regions.…”

“…The non-linear programming problem so formulated was solved using DE algorithm. Further, Manik, Gupta and Jha [23] formulated a dynamic promotional allocation problem for a single product of a firm under the combined effect of differentiated and mass promotional campaigns to maximize the effectiveness of promotion measured through sales incorporating repeat purchase behavior for the product under budgetary and minimum sales aspiration level constraint on each segment. Problem was also extended to incorporate minimum aspiration level constraint on total sales to be achieved from all the segments taken together.…”