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AI-Powered Product Price Optimization Platform
  1. case
  2. AI-Powered Product Price Optimization Platform

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AI-Powered Product Price Optimization Platform

innokrea.com
Information technology
eCommerce
Business services

Challenge

Innokrea's clients, particularly those in the eCommerce sector, face difficulties in accurately pricing used products, especially electronics. This is due to the variability in product parameters, limited data availability for withdrawn items, and the need to quickly determine competitive prices to maximize sales and buyer satisfaction. The lack of readily available and reliable price estimation tools leads to time-consuming manual price comparisons and potential lost revenue.

About the Client

A technology company specializing in developing innovative software solutions, including AI-driven applications for various industries.

Project Objectives

  • Develop an AI-powered platform to estimate optimal resale prices for products.
  • Provide sellers with an automated price suggestion based on product parameters and market data.
  • Enable buyers to assess the fairness of prices and identify deals.
  • Improve user experience and increase platform engagement.
  • Reduce the time spent on price determination for both sellers and buyers.

Functional Requirements

  • Product parameter input and processing.
  • AI-driven price estimation (Linear Models, Neural Networks, KNN).
  • Price suggestion display for sellers.
  • Price comparison tool for buyers.
  • Display of similar product listings.
  • Price driver analysis (identification of key price influencing factors).
  • Search functionality for best deals.
  • User account management (for both sellers and buyers).

Preferred Technologies

Python
Scikit-Learn
Django
Mobile application development (iOS & Android)
Web application development

Integrations Required

  • Potential integration with existing eCommerce platform data sources.
  • Possible integration with third-party data providers for market pricing information.

Key Non-Functional Requirements

  • Scalability to handle a large volume of product listings and user traffic.
  • Performance: Fast price estimation response times.
  • Security: Secure data storage and user authentication.
  • Reliability: Consistent and accurate price estimations.
  • Usability: Intuitive and user-friendly interface for both sellers and buyers.

Estimated Impact

The successful implementation of this platform is expected to significantly improve the user experience on Innokrea's eCommerce platform. Sellers will save an estimated 10 minutes per product listing, leading to increased listing frequency. Buyers will have a more informed basis for purchase decisions, leading to greater satisfaction and potentially higher transaction rates. The ability to quickly compare prices and identify deals will drive increased user engagement and platform loyalty. The platform aims to process 10,000+ auctions and provide alternatives for buyers and sellers.

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