On the Optimal Allocation of Resources for a Marketing Campaign.
Patrick Hosein,Shiva Ramoudith,Inzamam Rahaman +2 more
- 01 Jan 2021
- pp 169-176
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TL;DR: A mathematical model is presented in which, given a marketing budget of calls, one can determine a policy for selecting customers to target along with the optimal number of calls to use for each selected customer.
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Abstract: Many companies and institutions, such as banks, typically have a wide range of products that they make available to customers. However, such products must be marketed to their customers, especially when the product is new. Phone calls, emails, postal mail, and online advertisements are among the ways companies can market products to specific customers. However, the cost incurred during marketing increases with every contact made. Phone calls are the most personal means of targeted marketing but also the most costly. In telemarketing, a company can make multiple calls to a single customer with each call incurring a human resource cost. Such calls may or may not be able to persuade a customer to subscribe to the service or product. Some customers might subscribe after the first call. Some customers might require several calls to convince them. Other customers might never be persuaded. In light of limited resources, to maximize return, a company would need to determine which customers to contact and how many attempts to make for a customer. In this paper, we present a mathematical model for this problem in which, given a marketing budget of calls, one can determine a policy for selecting customers to target along with the optimal number of calls to use for each selected customer. We illustrate our model using a Portuguese banking dataset and show that our model can achieve significantly higher levels of success performance.
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Citations
Optimization of Production Decisions Under Resource Constraints and Community Priorities
Tetyana Nestorenko,Oleksandr Nestorenko,Mangirdas Morkunas,Artiom Volkov,Tomas Baležentis,Dalia Streimikiene,Jinyang Cai +6 more
TL;DR: In this article , an analytical solution of the problem of optimal allocation of resources in the game of two parties, based on the production function of Cobb-Douglas with constant returns under changing scale of production, is proposed.
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A Proposed Nonlinear Programming Optimization Model for Optimal Budget Mix of Digital Marketing Campaigns
Zakaria Yahia,Mostafa ElBolok +1 more
- 19 Oct 2024
TL;DR: This paper proposes a nonlinear programming model for optimal digital marketing budget allocation, using the Sainsbury Normal Method, to maximize expected net impressions while considering budget limitations and advertiser preferences through a systematic quantitative framework.
A stochastic nonlinear programming model for budget mix optimization of digital marketing campaigns under uncertainty
Zakaria Yahia,Mostafa ElBolok,Zakaria Yahia,Mostafa ElBolok +3 more
Abstract: Abstract This study introduces a stochastic mixed-integer nonlinear programming (MINLP) model designed to optimize budget allocation for digital marketing campaigns under uncertainty. The model maximizes Expected Net Reach (ENR) by integrating the Sainsbury Normal Method (SNM) to correct for audience duplication across platforms and employing Sample Average Approximation (SAA) to handle volatility in key metrics like impressions and reach. The primary contribution is a novel formulation that combines stochastic programming with net reach estimation, a methodological advance that avoid duplicated impressions and inaccurate aggregated metrics. This study also incorporates a weighting mechanism based on target audience demographics, enabling flexible allocation across digital platforms. To test and validate the proposed model, we conducted four case studies across various industries (Banking, Entertainment, Education, and FMCG) that demonstrated significant improvements in impressions and reach. Experimental analyses were performed to assess the performance of four budget allocation mechanisms—Empirical Weighting, Uniform Allocation, Meta-Focused, and Meta-Minimized—across different budget scenarios (50%, 100%, and 150% of the nominal budget). The numerical results highlight the dominance of Meta and YouTube platforms in brand awareness campaigns, consistently yielding the highest return on impressions. For example, in the entertainment sector, YouTube generated 77% of total impressions with only 56% of the budget, outperforming Meta and TikTok. Similarly, in the banking sector, Meta achieved 75% of impressions with a 39% budget share, proving to be the most efficient platform. These findings provide actionable insights for marketers seeking to optimize budget allocation in digital campaigns, offering a structured and adaptive framework to navigate the complexities of modern advertising.
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