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

Increase the Performance of Sales and Marketing By Using Data Mining Techniques
Author(s):
J .AMARNADHA REDDY, S. MUNI KUMAR
Keywords:
Stock data, K-Means, Clustering, Most Frequent Pattern, Data Mining.
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.
Article Details
Unique Paper ID: 145484 Publication Volume & Issue: Volume 4, Issue 10 Page(s): 525 - 528
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