November 06, 2023

The Challenge

A family-owned car wash operation in the Southeast region of the United States had been in business for over a decade and was growing and operating successfully. They had expanded to over a dozen locations and had a solid base of customers and members.

Not only were they known for providing a great experience, but their customers also loved their quality. In fact, over 35% of their customer base was purchasing their highest-tier wash.

While the business was sucessfuly, competition was increasing, and the cost of chemicals and labor were going up. The owners wondered whether their pricing model was optimized for maximum revenue. The fact that so many customers were choosing the top wash was an indicator that theere may be potential to increase prices, especially on the top package.

Rather than doing a standard price increase across the board and hoping for the best, the owners partnered with SUDS for a data-based recommendastion using PrecisionPricing^® in order to optimize the ROI of this change.

The Solution

PrecisionPricing predicted that by adjusting the prices of three of their four packages, they could increase their retail ticket average by nearly $2. That means for every non-member that visited the wash, they could be making almost $2 more.

With an operation of this size, this could increase topline revenue by nearly a million dollars in just the first year without washing a single car more than their current traffic level.

The key to success was that the owners understood that there was more potential profit to be made by using a data-backed strategic analysis approach like PrecisionPricing rather than simply increasing their prices across the board based on instinct.

The recommendation provided by PrecisionPricing leveraged factors like the number of wash packages, the price difference between each wash adn the price difference between the single wash and a membership to optimize profitability.

The Results

SUDS predicted that if the operators implemented our recommendation that the new distributions would be as indicated in the left column below. These distributions represent the perccentage of customers who choose each wash package.

In the right column, you'll see what actually happened.

In short, the percentage of customers who chose each wash package was almost identical to the predictions. Customers behaved almost exactly as we predicted they would with the new prices. And even more importantly, the ticket aveage increased by $1,72, which was in line with PrecisionPricing's initial prediction.

Learn how PrecisionPricing can influence your ticket averages. Request a SUDS consultation today.