Catalate’s Pricing Model Applied Across Industries

There are a number reasons ski resorts and other activities businesses, like water parks and attractions, look similar. While for one you bundle up, and the other you layer down,  both types of businesses have almost unlimited capacity, are subject to unpredictable weather, and have big fluctuations in demand/visitation through the duration of the season. 

In an earlier post, Evan wrote about how to determine what type of pricing strategy is right for your ticketing business. Unsurprisingly, ski resorts, water parks, amusement parks (as well as a “Timberlake concert when he’s 89”) fell into the same quadrant based on experience characteristics (see image above).

These characteristics mean both ski resorts and water parks/attractions can benefit from dynamic pricing strategies to grow advanced sales, and increase operational and financial predictability. 

Over the past several years, Catalate has expanded its portfolio of non-ski businesses to over 14 partners, giving us a large enough dataset to examine the performance of partners using our pricing model outside of ski, like Gulf Islands or Cowabunga Bay, to our ski resort partners using the same underlying pricing model.

What did we find?

The short story is that when we examine key metrics (searches per visit, revenue per search, and revenue per visit) for ski resorts and non-ski businesses, we see extremely similar performance and output from our pricing model. Although the underlying activities of these businesses is different, it confirms the effectiveness of our pricing model for businesses who sell a high volume of tickets with wide time slots.

Let’s look at this in more detail.

The goal of our analysis was to see how our non-ski partners performed against our ski partners across three primary metrics; one for each part of the e-commerce funnel.

  1. Searches per visit (SPV), to measure traffic at the top of the funnel
  2. Revenue per search (RPS), to measure conversion of that traffic
  3. Revenue per visit (RPV), to measure output and final results

Our first cut of this analysis used total revenue date-specific ticket revenue to calculate RPS and RPV, but given that a large percentage of ski resort revenue comes from multi-day tickets, including those products in the comparison against waterparks and attractions wasn’t apples to apples. We decided to include only 1-day ticket revenue for the purposes of the final analysis. 

We compared SPV, RPS, and RPV for our non-ski partners this past summer to the 90th, 75th, and 50th percentiles of ski partners from winter 18/19, and to our delight (but not surprise!), the results are very comparable. The metrics from our non-ski partners fall right around the benchmarks from our network of ski partners.

The charts above show individual non-ski partners’ performance (shown by blue bars) across three main metrics vs. the 50th, 75th, and 90th percentile of ski partners (shown by orange bars). Overall, when normalizing for the 1-day ticket, these success measures fall into the same range regardless of partner industry.

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