A Note from Greg Spathias, Partner Enablement & Analytics

Have you ever wondered what different pricing strategies look like? Taking a look at different pricing strategies can help to paint a clear picture of why one strategy performs better than another.  With Liftopia’s large network of resorts, our team can compare partners with different strategies in a controlled environment. We will also show you what you actually want to see – a strategy that delivers the most revenue for every trip date of the season. 

We have a few really cool examples below of similar partners (region, size, window rate) with different pricing strategies yielding very different results. While we always encourage our partners to have highly variable (different prices on different days) and highly dynamic (prices change for each day too) strategies, they don’t always take our guidance (it’s ok, our ego isn’t too hurt) so we can do these types of comparisons. Let’s take a look.

Example 1:

  • Two East Coast resorts
  • Each does ~200K visits annually

Each point in the scatterplot below represents a distinct price point for each trip date of the ski season for a standard 1-day lift ticket. Partner A, shown in green, implemented a variable, dynamic strategy whereas Partner B offered one price per trip date. The second chart shows the result of these different strategies. Partner A was able to earn more revenue for almost every day of the season than Partner B. Overall, Partner A was able to achieve 57% more revenue than Partner B. Partner A’s overall yield for the season was slightly lower than Partner B. Yield in this case is taken as the purchase price divided by the window price for that product. The last chart shows the average booking window for the season. Booking window is defined as the number of days between order date and trip date. Partner A was able to generate a higher average booking window than Partner B.

Dynamic pricing strategy visualization
Pricing Strategy Visualization
Revenue by Day
Average Yield
Total Revenue
Average Booking Window

Example 2: 

  • Two Western Canadian Resorts
  • Each does ~400K visits annually

The same type of visuals are shown below for partners in a different region. Partner A, in orange, had a variable, dynamic pricing plan whereas Partner B offered 1-2 prices per day. Partner A  earned more revenue than Partner B for every day of the season. In this case, Partner A earned 12x the revenue of Partner B overall. Similar to example 1, Partner A has a lower overall yield than Partner B. Partner A achieved a higher average booking window than Partner B.

Dynamic pricing strategy visualization
Pricing Strategy Visualization
Revenue by Day
Average Yield
Total Revenue
Average Booking Window

Example 3:

  • Two Resorts in the Sierra Nevada Mountain Range
  • Each does ~100K visits annually

In the third example, Partner A, in green, had a variable, dynamic pricing plan and Partner B offered a large range of prices, but still only offered 1 price per day. Partner A earned 40% more revenue than Partner B. Partner A’s yield for this product was lower than Partner B, but similar to example 1, Partner A was able to achieve more revenue further in advance than Partner B.

Dynamic pricing strategy visualization
Pricing Strategy Visualization
Revenue by Day
Average Yield

Total Revenue
Average Booking Window

So,why does dynamic pricing work?

The short answer is that all days aren’t equal. Since demand is highly variable throughout the season, a dynamic pricing plan makes sure that customers are seeing the right price, at the right time, for the right day. By using a dynamic plan, a non-peak Tuesday will have a lower starting price than a peak Saturday because the demand for both of those days is different. Dynamic pricing that rises over time also encourages customers to buy now, since they know the price is going to go up if they wait to buy. With a dynamic plan, you’ll lock in revenue in advance and ticket yield will increase as more tickets are purchased. 

Liftopia has a dedicated team that tests and adjusts our pricing strategies to yield the highest revenue possible for each day during the season for every partner. The pricing engine is built on millions of data points of consumer behavior online and prices each date according to demand.  The large network of resorts that use Liftopia’s pricing model allows us to reinform our pricing model and make real-time improvements to strategy at a much faster rate than a resort or attraction implementing pricing strategy alone.

The three examples show that a variable, dynamic plan can work for partners of different sizes in different regions. Do you want to see if our pricing plan will work for you? Reach out to partners@liftopia.com and we can build you a pricing plan focused on gaining more revenue for every day of your season.


Post Author: liftopia

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