Personalised Marketing Campaigns Using Machine Learning in Retail

As the retail sector is rapidly evolving, machine learning (ML) based personalised marketing has emerged as a practical solution to enhance customer outreach, consumer behaviour prediction and profitability. In the given paper, the researcher will speak about the opportunities that retailers can use machine learning models and data analytics to individualise their ways of approaching marketing. A retail dataset was considered to conduct a comprehensive Exploratory Data Analysis (EDA) utilising publicly available data to understand customer behaviours and purchasing pattern better. The tailoring of the marketing activities according to the trends was also applied through customer segmentation by K-Means clustering technique, time-series forecasting, and trend identification. The results indicate that data-driven approaches can transform retail marketing since it is possible to promote specific offers and optimise resources. The following paper provides some implementation insights together with detailing the challenges and the adoption implications of ML-based personalisation in the retail stores.

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