Pricing Engine Launch

Today, Wheelhouse is releasing a new pricing engine that represents a significant improvement in how our ability to drive rental revenue, based on local demand signals.

introduces a (leveraging a “Generalized Additive Model”, methodology detailed below) to replace our last model generation’s “Distributional Pricing” approach.

This new methodology leverages machine learning to better interpret how demand signals relate to the market’s price tolerance, with performance improvements including:

Model 9.0 is much better at decomposing demand into distinct components — seasonal trend, day-of-week effects, and event-specific spikes — and understanding how these components should contribute to specific daily pricing recommendations.

This advancement has two benefits - both making price recommendations more accurate, and making it easier to use your settings to create your ideal pricing strategy.

Model 9.0 is very effective at understanding the relationship between local demand patterns and booked prices. This capability means your engine is far more proficient at analyzing your current competitive landscape, and knowing where to move your pricing in order to maximize revenue.

Importantly, this improvement helps to better position your listing in both high & low demand environments.

Model 9.0 is better at responding to emerging demand signals without overreacting and pushing your prices too dramatically, day over day.

This allows your listings to more precisely adapt to events in the far future, without risking owner/guest complaints from overly reactive pricing changes.

As part of our evaluation of Model 9.0, we have been running an A/B test across >1,000 real, live listings across 20+ markets, and a wide range of inventory.

The results of this ongoing A/B test are available here, and will be updated weekly until the end of the trial (early February).

The new pricing engine is clearly differentiating itself in terms of driving revenue.

Additionally, we are also happy to see that the revenue creation is being partially driven by increased ADR, as well. This helps us determine that these results are not just a short term bump tied to cannibalizing future potential bookings.

Model 9.0 should be much easier to work with - right out of the box.

For our A/B test, our testing team reduced the use of model customizations ~81% between our control & test group for Seasonality, Day of Week, and Demand Sensitivity.

This reduction was based on strong agreement with the output of the new Pricing Engine, in matching their understanding of each local market.

With this launch, we are publishing live results of an ongoing A/B test, in order for you to follow along for learnings, updates & results.

👩‍💻 The live tracker is linked here

Yes, this test has been configured & run by a teammate at Wheelhouse.

However, as you examine how the trial has been structured, I think it will be clear that the trial setup & execution are as fair as possible, and serve as a decent showcase for the different approaches and results for Model 8.3 & 9.0.

With this new Pricing Engine, Wheelhouse has created a new set of tools that will allow you to:

Both on your terms and timeline. Therefore, you will be able to evaluate the where the model recommends increasing & decreasing prices, key model metrics, and more.

Want to evaluate the model, or opt-in to the newest pricing engine?

📄 on from this Help Center article

📽️ on how to upgrade here