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  • bidder recommendation system
    Our Success Story

Project Overview

  • Bidder notification was a challenge
  • No chance of cross-selling opportunity of any material
  • Price estimation challenge

About The Client

An E-Commerce company, offers a wide range of e-Selling, e-Sourcing, e-Finance, and Knowledge services across diverse industry verticals that empower businesses with greater process efficiencies.

Case Survey

Requirement 1 - Bidder Notification: There is a big challenge in deciding which bidders need to be notified about which auction.

Requirement 2 - Cross-Selling Opportunity: There was no such chance of cross-selling opportunity of any material which may be relevant to a bidder though initially, he didn’t show interest in that material.

Requirement 3 - Pricing Estimation: Estimated Price before the auction in a scientific way as based on this client prepares the reserve price.

Our Solution

k-means cluster analysis algorithm used to develop the bidder recommendation system.

We grouped the bidders into n (15) number of homogenous groups based on the levels of all parameters.

It reveals associations between data objects and helps to outline structure which gives much sense and meaning to the data when discovered.

Business Benefits Delivered

  • Cluster Analysis allows us to group similar data.

  • Helps in identifying patterns between data elements.

  • After a clear structure emerges, it allows easier decision-making.

Technology Stack

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