CASE STUDY: Automated Pricing

Ecommerce and Dynamic Pricing for Resorts and Attractions

Maximizing Sales Potential with Automated Pricing

Catalate works with hundreds of ski areas on everything from pricing strategies to online marketing best practices. We collaborate with partners in many different ways—some are happy to let us handle all things eCommerce while others like to test strategies of their own.

This case study highlights a real situation and actual data from two Catalate partners, and addresses an important question: Does a close level of collaboration with Catalate yield better results? Keep reading to see the advantages of working together.

The Test

Does Demand- or Time-driven Pricing Result in Higher Ticket Sales?

Meet the Catalate Automated Pricing model. It’s our pricing tool that factors in historical data and our partners’ unique attributes to sell lift tickets at the best possible price. Each calendar date has a set number of tickets at a range of prices. As tickets sell through, the price automatically rises. We call this demand-driven pricing. The price of the ticket will not change depending on when the ticket is purchased (which is known as time-driven pricing).

The Story

Early in the ski season, a partner (let’s use Partner A) is concerned about holiday pricing and decides to switch from our recommended pricing strategy to a solely time-driven pricing strategy. Ticket prices three plus weeks in advance are offered at a flat 85% of the window rate, two weeks in advance are 90% of the window rate, and the week of the trip date are 95% of the window rate.

In the same region, Partner B—of similar size, annual skier visits, and clientele as Partner A—decides to continue with our customized pricing strategy where prices rise automatically as tickets sell through. Prior to switching pricing strategies, Partner A’s sales were roughly the same as Partner B’s.

The Results

Partner A’s bookings into the holiday period plummet after the first time-driven price increase. The conversion rate drops 55% from the periods before and after the switch (spoiler alert: they return to a demand-driven pricing strategy). Meanwhile, Partner B continues to sell into the holidays at high velocity, earning $300K more in revenue than Partner A. Both partners maintain the same average yield. After reviewing the pricing choices, Partner A returns to our recommended demand-driven pricing strategy.


The Key Takeaway

Our Automated Pricing strategy lets prices rise naturally based on demand and the individual factors of your ski area, whereas changing prices based on calendar dates alone can lead to missed revenue. Partnering with Catalate gives you the advantage of our pricing expertise and years of testing and data to maximize revenue. It’s our priority to help you succeed with your best interests in mind.

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