Using Data Mining To Improve Consumer Retailer Connectivity

Download Document/Synopsis
Many consumers prefer online shopping. Day-to-day busy schedule made many consumers to visit online e-commerce websites for shopping. This saves time and cost of the consumer. With the growth of the e-commerce websites retailers tend to fail to attract more and more consumers. Consumers no longer feel difference between e-shopping and offline shopping. We proposed a system of connecting the consumer and the retailer. This system creates a bridge between consumer and retailer. We had implemented an effective data mining algorithm to analyze new patterns and trends. This system will gather data from the customer behavior pattern and is supplied to the retailers, so that retailers will able to know the new patterns and trends. With these information retailer can approach targeted customer and can constantly interact with those consumers that retailer is exactly looking for. This system helps retailer to keep constant connectivity among the retailers and the consumers. In this system we had used data mining algorithm that helps the retailer to discover new patterns and trends. The system updates the retailers with new trends and patterns .This system helps to improve the sales and business of the retailer. System will also help the retailer to know about the updated price of the product as well as new trend in market.



Advantages
  • System helps retailer to keep constant connectivity among the retailers and the consumers.
  • With the help of data mining algorithm, system will display new trends and patterns.
  • System will help to discover new trends and patterns in market.
  • This system helps to improve the sales and business of the retailer.
  • System will also help the retailer to know about the updated price of the product as well as new trend in market.
Disadvantages
  • Users who don’t have internet connection can’t access the system.
  • We have to create e –commerce website where retailer can access the system.
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