Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/2A528A2A-270E-4F2E-AF3B-1102F5A17FF2 | ||
| Year | 2023 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Georgios Parousis, "Market segmentation using data mining and multi-criteria analysis", Diploma Work, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2023 https://doi.org/10.26233/heallink.tuc.98992 | ||
| Appears in Collections |
In businesses special emphasis is placed in the power of information. The department that is responsible for data analysis should use every piece of information that can be derived from the collected data. The goal is to discover new opportunities, address problems, and identify areas that require improvement. Similarly, the marketing department is responsible for selecting the best possible strategy for introducing new products and services and modifying or withdrawing existing products and services. Market segmentation is a crucial practice for the strategic planning of a marketing team, aiming to improve a targeted advertising campaign for a segment of the consumer audience with similar behavioral characteristics. The success of a business comes from its ability to tailor its products to these specific characteristics, allowing it to meet the needs of the respective customer groups it targets. This paper presents a methodology for market analysis and segmentation. The methodology combines a multi-criteria method with Neural Networks algorithm. More specifically, the Utastar methodology is used in combination with Self Organizing Maps.
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