Increase the Performance of Sales and Marketing By Using Data Mining Techniques

  • Unique Paper ID: 145484
  • PageNo: 525-528
  • Abstract:
  • Classification and extracting patterns from the customer data are very important factors for decision making and business support. Identifying newly coming trends is needed in business process. Sales patterns from complete list of data indicate market trends and can be used in future which has great capacity for decision making, planning and market competition. Here the System consists of two phases. In the first phase we divide the stock data into different clusters based on the product categories and sold quantities. Here the categories are Dead Stock, Fast Moving and Slow Moving by using K-means algorithm. In the second phase we will use Most Frequent Pattern algorithm to find frequent patterns of item attributes in each category products and also give sales trend in neatly packed form.
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Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{145484,
        author = {J .AMARNADHA REDDY and S. MUNI KUMAR},
        title = {Increase the Performance of Sales and Marketing  By Using Data Mining Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {10},
        pages = {525-528},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145484},
        abstract = {Classification and extracting patterns from the customer data are very important factors for decision making and business support. Identifying newly coming trends is needed in business process. Sales patterns from complete list of data indicate market trends and can be used in future which has great capacity for decision making, planning and market competition. Here the System consists of two phases. In the first phase we divide the stock data into different clusters based on the product categories and sold quantities. Here the categories are Dead Stock, Fast Moving and Slow Moving by using K-means algorithm. In the second phase we will use Most Frequent Pattern algorithm to find frequent patterns of item attributes in each category products and also give sales trend in neatly packed form.},
        keywords = {Stock data, K-Means, Clustering, Most Frequent Pattern, Data Mining.},
        month = {},
        }

Cite This Article

REDDY, J. .., & KUMAR, S. M. (). Increase the Performance of Sales and Marketing By Using Data Mining Techniques. International Journal of Innovative Research in Technology (IJIRT), 4(10), 525–528.

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