Market segmentation enables the marketers to understand and serve the customers more effectively thereby improving company’s competitive position. In this paper, we study the impact of price and promotion efforts on evolution of sales intensity in segmented market to obtain the optimal price and promotion effort policies. Evolution of sales rate for each segment is developed under the assumption that marketer may choose both differentiated as well as mass market promotion effort to influence the uncaptured market potential. An optimal control model is formulated and a solution method using Maximum Principle has been discussed. The model is extended to incorporate budget constraint. Model applicability is illustrated by a numerical example. Since the discrete time data is available, the formulated model is discretized. For solving the discrete model, differential evolution algorithm is used

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Digital revolution has resulted in a paradigm shift in the field of marketing with online advertising becoming increasingly popular as it offers the reach, range, scale and interactivity to organizations to influence their target customers. Moreover, web advertisement is the primary revenue stream for several websites that provide free services to internet users. The website management team needs to do a lot of planning and optimally schedule various advertisements (ads) to maximize revenue, taking care of advertisers’ needs under system constraints. In this paper, we have considered the case of news websites that provide news to its viewers for free with ads as the primary source of their revenue. The considered news website consists of many webpages with different banners for advertisement. Each banner consists of different number of partitions and cost per partition varies for different rectangular banners. Many ads compete with each other for their placement on a webpage on a specific banner, based on partition requirement, at specific time interval(s). Here, we have formulated a mixed integer 0–1 linear programming advertisement scheduling problem to maximize the revenue over planning horizon divided into time intervals under various system and technical constraints. A case is presented to show the applicability of the model. Branch and bound integer programming and goal programming techniques have been used to solve the formulated problem.

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.

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