【Pricing Example】Automotive Industry DX Firm Collects Data from WECARS for AI Utilization

Client

Our client for this request is a company driving Digital Transformation (DX) in the automotive industry. The automotive sector is currently undergoing a significant transformation known as CASE (Connected, Autonomous, Shared & Services, Electric), which demands the creation of new services and business models leveraging digital technologies. Our client contributes to shaping the future of the automotive industry and realizing a safer, more comfortable mobility society by harnessing cutting-edge technology and data. The application of AI technology stands as a crucial strategy at the core of their initiatives.

Objective

The primary objective of this project was to collect comprehensive automobile information. Our client sought to gather detailed vehicle data from WECARS to facilitate the development of innovative AI-powered services. By training AI with a vast amount of automotive data, they aimed to enhance the accuracy of various services, including used car price prediction, demand forecasting, and personalized recommendations for customers. Data-driven decision-making is a cornerstone of their DX promotion.

Challenges Faced

The client had been manually collecting automobile information from WECARS using their in-house employees. However, WECARS lists an immense volume of vehicle data, making manual collection of all necessary information an extremely time-consuming and labor-intensive task. This process required several employees to dedicate long hours, leading to increased costs including personnel expenses. Moreover, the manual approach inherently presented a high risk of human error, affecting data accuracy. These challenges were significant obstacles to our client’s DX initiatives.

Impact of Problem Resolution

By automating data collection from WECARS, our client achieved significant cost reductions and improved operational efficiency. The time and effort spent on data collection were drastically reduced, leading to substantial cost savings, including labor costs. Additionally, by leveraging scraping technology, they prevented data entry errors caused by human mistakes and enhanced data accuracy. These improvements allowed the client to concentrate on AI development, enabling them to pursue DX promotion more rapidly and efficiently. High-accuracy data enhances AI learning effectiveness, enabling more precise predictions and analyses.

Pricing

The total cost for this data collection was $202.44. Considering that 16,435 items of automobile data were acquired, the cost-effectiveness is remarkably high. Maximizing results within a limited budget is crucial.

Data Content

The collected data comprehensively covers automobile information essential for AI learning, including URL, Title, Grade, Amount, Dealer, Address, and Phone Number. All this information is the latest data obtained from WECARS, enabling the client to continuously develop AI based on up-to-date data. Data freshness is critically important for enhancing AI learning effectiveness and achieving highly accurate analysis results.

Number of Records

The number of collected data records totaled 16,435 items. Possessing this volume of data allowed the client to train their AI with a large dataset, enabling the construction of more accurate predictive models. The quantity and quality of data are crucial factors affecting AI performance. A large amount of data enhances AI learning effectiveness and enables the recognition of more complex patterns. As a result, more precise predictions and analyses become possible.

Delivery Time

The delivery time was 5 business days from the request. This rapid delivery enabled the client to commence AI development immediately after data collection, ensuring smooth project progress. A speedy response is crucial in today’s rapidly changing business environment and supports the client’s business success.

WECARS Sample Data (Quoted from Source)

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