CASE STUDY
Vehicle Prediction and Pricing Optimization for Leading Automotive Company
Industry | Automotive
Technology | AI/ML
Location | USA
Our client is at the forefront of the American automotive industry, blending over a century of engineering excellence with cutting-edge technology. Founded in 1967, its heritage is rooted in innovation and a commitment to the principles of sustainability and performance. Based in Detroit, Michigan, the client has evolved into a flagship American car manufacturer, known for its robust lineup of vehicles including fuel-efficient sedans, SUVs, and electric vehicles.
Challenges
Traditional pricing strategies don't consider real-time market dynamics.
Fixed pricing models lacked flexibility, which led to missing opportunities to maximize revenue
The client lacked dynamic pricing capabilities.
The client struggled to respond to competitor actions.
Key Outcomes
4%
Increase in Total Revenue
3-7%
Enhanced CLV (Customer Lifetime Value)
2.5%
Improvement in Pricing Strategies
Solutions
Collected historical sales data, vehicle features, market trends, competitor pricing, and customer demographics
The dynamic pricing engine developed was based on two-stage machine learning.
Deployed the ML-based pricing optimization model into production environments
Built intuitive dashboards and visualization tools for stakeholders.
What Customer Say about RoyalCyber
Congratulations and a big thank you to everyone that worked on the Portal 8.5 Version upgrade and successfully implemented. The team did a great job working through all the tasks that came up and hats off to everyone that worked on this project.
Craig McCroskey
Sr. Director IT
80%
Increase in Customer Activity
Audience
- Executives, CTOs, Director
- IT Consultants
- Business Analysts
- Project Managers
- IT Project Coordinators
- Architects and Specialists
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