AI-Powered Vehicle Sales Projections

Challenge

In the highly competitive vehicle sales industry, client faced the challenge of accurately projecting sales figures, leading to suboptimal inventory management and potentially missed sales opportunities.

Overview

Client leveraged AI and ML techniques to analyze test drive data, vehicle preferences, and durations. Insights were derived to personalize recommendations and improve sales.

Solution

Test Drive Analysis

client harnessed AI and ML to analyze test drive data, including vehicle preferences and durations. This allowed for personalized recommendations based on customer preferences, test drive experiences, and location.

Predictive Factors

The analysis considered various factors, such as test drive duration, location of the vehicle on the lot, the salesperson involved, time of day, and day of the week. These variables were used to predict customer behavior and preferences.

Training the Model

client used existing logic and fundamentals to train the AI model. A data warehouse with legacy data was created to facilitate this process.

Model Selection and Fitting

Regression algorithms were used, and the model was tested with 30% of the data. Metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R² (R-Squared) were evaluated.

Results

The AI-powered approach resulted in accurate sales projections and improved inventory management, revolutionizing TrueSpot’s operations.

Top Vehicles vs. Duration

TrueSpot identified which vehicle models performed best in relation to test drive duration, enabling targeted marketing efforts.

Top Vehicle Models

Clear insights into the most popular vehicle models allowed for optimized inventory stocking.

Predictability

The AI model provided a high level of predictability, enhancing decision-making regarding test drive recommendations and inventory management.

Model Confidence

Selecting the model with a confidence level exceeding 75% ensured reliable sales projections and recommendations.

Tools Used

Python

scikit

Google collab

Tensorflow

ML Flow

0 %
Sales Projections with an Accuracy Rate Exceeding
0 %
Rate of Test Drives to Vehicle Purchases
0 %
Reduction in Marketing Costs
0 %
Increase in Customer Satisfaction Scores

Conclusion

Conclusion
By harnessing AI and ML techniques and utilizing a range of tools, client successfully tackled the challenge of accurate sales projections. These AI and ML-driven outcomes not only improved inventory management but also enhanced customer satisfaction and sales opportunities, solidifying client’s position in the competitive vehicle sales industry.

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