Summary

With more than 20 million business-to-business and business-to-consumer transactions per year and 1 billion prices active across nearly a dozen distribution channels, each of this global car rental company’s pricing analysts had to manage more than 20 million prices daily. An advanced pricing optimization solution was needed to effectively manage this volume, improve forecasting techniques and support prioritized management by exception

Challenge

The company faced pricing challenges that are common in the car rental industry. Even though pricing and fleet decisions relied on one another, these decisions were made independently. Insufficient communication and visibility between the two areas caused internal disconnects that hindered crucial decision-making, especially for pricing analysts who manage more than 20 million prices daily.

Moreover, pricing decisions were not synchronized with continually changing fleet and distribution costs nor were pricing strategies aligned with current fleet plans. The company’s performance was further impacted by “gut feel” pricing decisions that failed to maximize profit opportunities at all levels of the organization.

The company eventually sought the ideal technology partner to help it:

• Improve pricing processes to offer the right price at the right time based on customer purchasing behavior and product attributes.
• Identify opportunities to increase revenue and profit from low-performing customer and product segments.
• Equip product and pricing managers with enhanced reporting capabilities to understand how different pricing initiatives impact margins.
• Create a pricing solution that sales representatives would embrace and use consistently.

“PROS Contribution Management System is the only complete software solution capable of addressing price optimization, inventory allocation and fleet optimization— the key challenges facing the automobile rental industry.”

Car Rental Company Customer

Solution

The company approached PROS in hopes of improving its pricing processes with a goal of increasing gross profit by $150,000 in the next quarter. Although the company was already using a high-end hardware platform, it was open to an alternative if PROS could offer a solution with the capacity to handle a multi-terabyte environment and add value beyond what the company’s existing platform could provide.

So, PROS implemented a solution that automated the transfer of approved prices to a central pricing storage system, a process that the company had to execute manually on its previous platform. Pricing analysts were then able to effectively target prices for every rental to maximize contribution margin on every deal.

Results

PROS started the implementation by using sophisticated statistical methods to forecast demand at the product level (location, car class, rental date and rental length). This baseline demand forecast became the foundation for decision-making throughout the company.

Using a more accurate demand forecast, pricing analysts were able to balance trade-offs between rental length and daily revenue to maximize overall profitability. PROS also provided insights into the costs associated with fleet moves between locations to identify the most profitable mix of business.

After implementing PROS software, the company’s pricing and fleet organizations worked in tandem to accelerate their time-to-market pricing. The company also experienced a significant reduction in avoidable costs and met or exceeded stated targets for customer revenue improvement.

The company realized millions of dollars in overall revenue improvement and recouped its entire PROS software investment in less than a year.

Conclusion

In summary, PROS solutions delivered several significant advantages over the car rental company’s existing pricing platform:

• Automated time-consuming, manual processes for transferring approved prices to a central pricing storage system.
• Enabled pricing analysts to target optimal prices for every rental, maximizing margins on every deal.
• Improved decision-making with more accurate demand projection.
• Illuminated costs associated with fleet moves between locations to identify the most profitable mix of business.