Boosting Auction Price Accuracy and Sales Efficiency by Integrating Damage Image Analysis with Market & Historical Data

Industry: Automotive, AI

Client

Top Vehicle Auction & Pricing Analytics Firm

Goal

To improve pricing accuracy by developing a predictive model that analyzes car damage images and forecasts auction prices more effectively.

Challenges

  • Developing a system that incorporates visual data from damaged vehicles.
  • Integrating visual data with other data points to improve pricing predictions.
  • Enhancing the accuracy of vehicle price estimation.

Solution

Used ChatGPT Vision API to analyze car damage images and extract relevant features for price prediction.

Integrated additional features—such as vehicle specifications, historical prices, and market trends—into the pricing model to improve accuracy.

Designed a machine learning model combining visual and textual data to predict the most accurate auction prices.

Impact:

Significantly improved pricing accuracy by integrating image analysis with traditional price prediction features.

Increased sales efficiency by providing more accurate vehicle pricing, reducing discrepancies between predicted and actual auction prices.

Enhanced the bidding process by offering sellers and buyers more precise pricing information, strengthening the platform’s market reputation.

*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.