Data Mining For Customer Profiling and Sales Prediction

Predescu, Adrian (2024) Data Mining For Customer Profiling and Sales Prediction. Bachelor's Thesis, Computing Science.

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Abstract

In the age of big data, organizations are frequently overwhelmed by the sheer volume of data they have to handle. The real challenge, however, is not in gathering the data, but in effectively using it. The process of converting raw data into structured, actionable insights is intricate and does not always yield successful results. In this Bachelor’s Thesis, my goal is to investigate the use of data mining methods for customer profiling and sales predicting. This involves a deep dive into various data mining algorithms, including clustering algorithms like K-means, hierarchical clustering, and vector quantization. Moreover, I will evaluate their efficacy in interpreting customer behavior and predicting future sales patterns. This research will illustrate how these techniques can enable businesses to customize their strategies to satisfy customer demands and maximize sales. Additionally, it will add to the expanding knowledge base in the realm of data science and its practical uses in business intelligence. In essence, it aims to pave the way for harnessing data-driven insights in strategic decision-making.

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Dustegor, D. and Truong, H.C.
Degree programme:	Computing Science
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	06 Aug 2024 13:56
Last Modified:	06 Aug 2024 13:56
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/33883

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