How do you use dynamic pricing to adjust length of stay rates for different segments and channels?

Today, dynamic pricing in the hospitality industry is key, and well leveraged can yield strong revenue performance. Now, I am still impressed by the number of hotels who are actually not dynamically pricing their hotels, reinforcing the need to increase awareness and education in the hospitality industry. And yes, technology can help us increase accessibility and usability to a larger audience.

Dynamic pricing is a strategy where prices are adjusted in real-time based on various factors such as demand, inventory levels, competitor pricing, and market conditions. It allows businesses to optimize revenue by setting prices dynamically to reflect changes in supply and demand.

To apply dynamic pricing to LOS rates: -- Utilize data analytics and demand forecasting tools to identify periods of low occupancy and high demand. -- Adjust LOS rates dynamically based on demand trends, booking patterns, and customer segmentation. -- Implement pricing rules and algorithms that automatically adjust LOS rates across different channels and customer segments.

Talking to the great Fetcherr team, it is quite clear to me that to have a true dynamic pricing that takes effectively LOS into account, you need to base pricing decisions on AI models that have been trained on lots of data, as LOS is a feature that tends to interact with other features like cabin, holidays, etc. In more advanced AI-based pricing systems, like Fetcherr’s, very granular customer segments are defined so that every incident can be priced separately and in high frequency, not just based on the length of the stay, but also depending on, for example, whether the customer stays over the weekend or not. Various A/B tests have proven that LOS is a key indicator for estimating customers' willingness to pay and demand elasticity.

Segmenting customers for LOS rates involves: -- Analyzing customer data to identify different segments based on factors such as demographics, booking behavior, and preferences. -- Tailoring LOS rates and promotions to target specific customer segments, such as leisure travelers, business travelers, or groups. -- Customizing marketing messages and promotions to appeal to each customer segment and encourage longer stays

Monitoring LOS performance requires: -- Tracking key performance indicators (KPIs) such as occupancy rates, average length of stay, and revenue per available room (RevPAR). -- Analyzing booking patterns and trends to identify opportunities for optimizing LOS rates. Utilizing revenue management software or tools to generate reports and insights on LOS performance across different segments and channels.

Testing and optimizing LOS rates involve: -- Conducting A/B tests or experiments to evaluate the impact of different LOS rates and promotions on booking behavior. -- Continuously monitoring performance metrics and adjusting LOS rates based on test results and feedback. -- Experimenting with different pricing strategies, discounts, and incentives to find the optimal balance between occupancy and revenue.