Our AI tools helped a traditional car dealership work faster and make smarter decisions when buying and selling cars. Using SQL for data mining and combining clustering methods (DB scan, Agglomerative clustering, K-means) with Ensemble learning, our team built a new algorithm.
About Client
The client owned a well-known car dealership with good prices but relied on old-fashioned manual data analysis.
Challenge
Even though the dealership had loyal customers, they found it hard to quickly gather and study car data from different sources. This made market research and accurate car valuations difficult.
Our Solution to Get their Desired Results
Our AI tool is built to update how car dealerships sort through market data and figure out their car values.
Data Aggregation
Built an algorithm that searches the internet for car information from many websites and puts it all in one place for easy use.
Adjustments
We introduced additional weights to balance the classes within the model. This helped reduce bias and allowed predictions to be more accurate.
Advanced Analysis
We used XGBOOST, a tree-based machine learning model, to classify cars into affordability categories. We also used advanced data pre-processing techniques to refine the dataset.
What it can do
Informed Decision-Making
A 95% accuracy rate in price predictions significantly improves confidence in buying and selling decisions.
Market Position
The dealership experienced a remarkable uptick in sales efficiency, with the AI system providing a competitive advantage in a saturated market.
Customer Experience
Better inventory management and customer satisfaction, which improved profitability.
Got an idea for your product?
We will build it for you from scratch and share the structured documentation to help you keep your system in top shape.