Mastering Pricing Model Performance: Unlocking Success for Property Managers

In the competitive landscape of short-term rentals, property managers face the constant challenge of optimizing pricing strategies to maximize revenue and stay ahead of the competition. One essential aspect of this optimization process is measuring pricing model performance. By analyzing the effectiveness of your pricing algorithms, you can gain valuable insights into how well your strategies are working and make smarter decisions on new pricing models, tools and revenue manager coaching. 

The Significance of Measuring Pricing Model Performance

Measuring pricing model performance allows property managers to evaluate the effectiveness of their pricing strategies and make informed decisions to optimize revenue. Here's why it's crucial:

• Revenue Optimization: Analyzing pricing model performance helps property managers identify potential areas for improvement. By measuring key performance indicators, such as revenue per available night (RevPAN), occupancy rates, and average daily rates (ADR), managers can fine-tune their pricing algorithms to maximize revenue generation. Other helpful metrics between model versions will be price regret, does the model suggest lower prices than what was sold, and price recall or does the model suggest a higher price on an unsold night?

• Competitive Advantage: In the dynamic short-term rental market, keeping a pulse on competitors is vital. Evaluating pricing model performance helps property managers understand how their strategies compare to others in the industry. This knowledge enables them to adjust their pricing algorithms to stay competitive and attract guests while maximizing profitability. This may also identify managers that are worth targeting if you identified significant under pricing performance with a specific competitor. 

• Market Insights: Measuring pricing model performance provides property managers with valuable market insights. By analyzing data on demand patterns, booking trends, and seasonality, managers can identify opportunities to adjust pricing strategies and capture additional revenue during peak periods or off-seasons. It is important to retest older models as well as the market is constantly shifting. You have actuals from the current model you are running but it is helpful to retest and rerun overtime to see if consumer trends have shifted.

Key Metrics for Measuring Pricing Model Performance

To effectively measure the performance of your pricing model, consider tracking these key metrics. To most accurately measure impact you should go back to the price predicted at the date which the unit was booked. More complex evaluation models will look at the elasticity and pacing overtime. More on that below!:

• Price Regret: Does a new model price previously sold days lower than what they sold for? If it does, then that is call Price Regret. This means you regret the price you sold at because there was still value or money left on the table. You can measure this in terms of number of days it happens or the total dollar value of the underpricing. You will want to keep in mind point in time pricing, if the final price suggested is below but you are evaluating zero lead time days compared to when it booked 90 days ago, that is not apples you apples. You will want to compare what the new algorithm suggested the price should be with a 90 day booking window. 

• Price Recall: This metric tracks how the pricing model being evaluated will "recall" an unsold night and price it lower. Price Recall should yield increased occupancy through suggesting lower priced nights for those that did not sell. You can measure the precession of this, how often it recommended a lower priced for an unsold night, and the to value of price declines on unsold nights. Again, keep in mind to evaluate the price over time through the booking window a higher price further out in the booking window but dropping below previous price on unbooked nights would be not by itself be a bad thing.

• Price Surge: This metric often has different names but ultimately how often does the measured model predict a higher price for a sold night. There are a number of ways to cut and evaluate this but ultimately you want to keep occupancy and elasticity in mind. You would not want to reward the model for over pricing a low occupancy time period or when demand is very elastic. However, if the new algorithm is suggesting a higher price much further out in the booking window that may be a good thing.

• Occupancy Rate: Occupancy rate measures the percentage of nights that your property is booked over a specific period. A high occupancy rate modeled with elasticity in mind or observed in reality indicates strong demand and effective pricing strategies.

• Revenue per Available Night (RevPAN): RevPAN is a critical metric that measures the revenue generated per available night in your property. It provides a comprehensive overview of your pricing model's effectiveness. You want to ensure a good model is adding occupancy in lower demand times through dropping rate on unsold nights, and capturing higher ADR in peak demand periods by increasing rate where appropriate. RevPAN and RentPAN are important metrics to track as RentPAN is what owners split so diverging paterns should be noted and tracked. 

Tools and Techniques to Measure Pricing Model Performance

Property managers can leverage various tools and techniques to measure pricing model performance effectively:

• Data Analytics Platforms: Utilize data analytics platforms designed specifically for the travel industry industry. These platforms offer comprehensive insights into market trends, competitor analysis, and performance metrics, enabling property managers to evaluate pricing model effectiveness. There are not many options for the STR world, so you may have to develop some and feed into a Business Intelligence (BI) tool. 

• Comparative Analysis: Conduct comparative analysis by comparing your property's performance against similar listings in your market. This analysis provides insights into how your pricing strategies compare and helps identify areas for improvement. How does the model price against the CompSet, you can compare its pricing curve against the CompSets sold and unsold nights to visualize how it would perform. 

• A/B Testing: Implement A/B testing by using different pricing strategies for subsets of your properties. This allows you to measure the impact of pricing changes on key performance metrics and determine which strategies yield the best results. You can compare both groups period over period performance to see which performed better. Try to capture different types of inventory to avoid selection bias. 

• Guest Feedback and Reviews: Monitor guest feedback and reviews to gain insights into how pricing affects guest satisfaction. Negative reviews related to pricing may indicate the need for adjustments in your pricing model. You may be able to overprice and still sell a night but is it worth the negative reviews if the guest does not feel there is value. 

Measuring pricing model performance is a vital practice for property managers seeking to optimize revenue and stay competitive in the short-term rental market and develop their own pricing with their unique perspectives. By tracking key metrics, leveraging industry tools, and implementing data-driven strategies, property managers can unlock greater success and achieve their revenue goals. Embrace the power of measuring pricing model performance and make informed decisions to drive your property's profitability forward.

Ready to start building your own pricing algorithms? Hungry Robots has the data you need to get started. Schedule time to talk to an expert!