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Research Article

Influence of Promotion and Pricing on Purchase Incidence, Demand, and Sales Using Machine Learning

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  • @ARTICLE{10.4108/eetismla.5082,
        author={Rahul D Shanbhogue and Anwesh Reddy Paduri and Narayana Darapaneni},
        title={Influence of Promotion and Pricing on Purchase Incidence, Demand, and Sales Using Machine Learning},
        journal={EAI Endorsed Transactions on Intelligent Systems and Machine Learning},
        volume={1},
        number={1},
        publisher={EAI},
        journal_a={ISMLA},
        year={2024},
        month={4},
        keywords={Promotion, Pricing, FMCG, Machine Learning, Demand},
        doi={10.4108/eetismla.5082}
    }
    
  • Rahul D Shanbhogue
    Anwesh Reddy Paduri
    Narayana Darapaneni
    Year: 2024
    Influence of Promotion and Pricing on Purchase Incidence, Demand, and Sales Using Machine Learning
    ISMLA
    EAI
    DOI: 10.4108/eetismla.5082
Rahul D Shanbhogue1, Anwesh Reddy Paduri2,*, Narayana Darapaneni3
  • 1: PES University
  • 2: Great Learning
  • 3: Northwestern University
*Contact email: anwesh@greatlearning.in

Abstract

The consumer goods industry is a dynamic and fast-paced sector that faces significant challenges in meeting the consumer’s ever-evolving demands and preferences. Today’s retail businesses focus on optimizing their supply and retail execution to maintain a competitive edge in the market and remain profitable. The most impactful method is to offer promotional events that stimulate large-scale purchases and attract new customers. The patterns of normal sales days, promotion days, and non-promotion days are different and it is vital to capture the influence of promotions on demand and sales. Thus, it is vital to understand the effects of promotion and plan them. This paper aims to understand the influence of promotion and pricing strategies for FMCG retail businesses to maximize demand for each brand. Explore the use of Machine Learning (ML) and Deep Learning models such as Clustering and Neural Networks to identify and understand the various demand patterns to analyse the influence of promotion and pricing on demand, and enable businesses to respond more quickly to changes in the market by enabling them to make better-informed decisions that can mitigate risks associated with the impact of disruptions and to ensure the continuity of the business.

Keywords
Promotion, Pricing, FMCG, Machine Learning, Demand
Received
2024-02-09
Accepted
2024-04-04
Published
2024-04-10
Publisher
EAI
http://dx.doi.org/10.4108/eetismla.5082

Copyright © 2024 R. D. Shanbhogue et al., licensed to EAI. This is an open-access article distributed under the terms of the CC BYNC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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