AI-driven decision support system for the automotive market
Cardog's market analysis engine adopts a three-fold data modeling approach: firstly, it captures the listing prices of mainstream used car platforms to form a benchmark database, secondly, it accesses the macro circulation data from the government's vehicle registration system, and lastly, it predicts price fluctuations through the analysis of online public opinion. When users query a specific model (e.g. "2022 Toyota Camry US market price trend"), the system automatically generates a visualization report containing historical price curves, heat maps of regional spreads and forecasts for the next three months. Test data shows that the accuracy of this function in predicting price fluctuations of used cars reaches 78%, significantly higher than the industry average of 62%. The platform also innovatively introduces the "Buying and Selling Timing Index" algorithm, which analyzes 12 parameters such as inventory turnover and new car promotions to provide users with specific trading suggestions. The platform also innovatively introduced the "buying and selling timing index" algorithm, which analyzes 12 parameters such as inventory turnover rate and the strength of new car promotions to provide users with specific trading suggestions.
This answer comes from the articleCardog: Vehicle Information Research and Intelligent Analysis of Automotive Market Data》
