The key to understanding your performance this season

Somehow, it is that time of year again. The time of year when lifts stop spinning, snow begins to melt, and Liftopia helps its partners assess their performance over the past season. At the close of each winter, the Liftopia team prepares “End of Season Reports” for each of its partners, highlighting not only individual performance metrics from the season, but how the results for each partner compare to other resorts on the platform across a variety of relative metrics.  We’ve talked before about the importance of using relative metrics to assess performance relative to potential, and End of Season reports from Liftopia are another place to access that information for your resort.

E-commerce funnel and associated metrics

In general, we focus on metrics for the past season across the three main components of the e-commerce funnel: Intent, Conversion, and Results. At the top of the funnel, metrics related to “Intent” tell us how well a resort drives traffic into their e-commerce environment. Searches into Cloud Store (or any e-commerce environment) are a result of efforts such as email marketing, social media posts, direct traffic, etc. At the middle of the e-commerce funnel, metrics related to “Conversion” measure how well a partner converts its traffic into revenue. Success in conversion is closely tied with pricing strategy and product mix. And finally, at the bottom of the e-commerce funnel, metrics related to “Results” measure output (think revenue and guest days) from e-commerce. End of Season reports from Liftopia display raw metrics (Searches, Demand Capture, Guest Days) across each party of the e-commerce funnel, as well as relative metrics that allow us to compare resorts of different sizes, regions, etc. such as Searches per Visit (SPV), Revenue per Search (RPS), and RevPASS.

For example, each chart in the end of season report related to SPV, RPS, and RevPASS compares a partner’s performance to the 90th percentile of the platform and the 90th percentile of the region, to provide context for individual resort performance.

After we walk through metrics tied to the e-commerce funnel, we examine “Pricing Efficiency”. Looking at pricing patterns for each partner across all trip dates of the season, and comparing those trends to the platform, allows us to examine what worked and what could have been better this past season, and potential changes to pricing strategy for next winter.

Yield example, your resort and the platform

Next we dive into booking patterns, to understand how the resort’s pricing strategy affected customer booking behavior. Which products are booked further in advance than others? Which trip dates had the longest booking windows? Why? What is the relationship between search behavior and booking behavior?

Cumulative revenue, searches and yield by booking window example

Finally, we share demographic information about customers so our partners can understand more about their consumer base and where their customers come from. In addition to displaying purchaser location data, Liftopia is in the unique position to share which other resorts a customer skis at across the Liftopia platform.

Customer demographics example
Resort overlap example

Looking back at results from the season is an important step in the continuous improvement cycle of pricing strategy and revenue growth. While the results from a resort individually are valuable, looking at how those results compare to the results across a larger network can provide deeper insights and opportunities for growth.

Do you have questions about End of Season reports at Liftopia? Contact us at partners@liftopia.com.

Post Author: Kathryn Quinn

Leave a Reply

Your email address will not be published. Required fields are marked *