This blog provides a cursory overview of some of the key concepts related to next-generation revenue management practices. The first part talked about the performance metrics. In this final part, we will take a quick look at the remaining two concept: data and intelligent pricing. 

Relevant data sources

When it comes to data, revenue managers today have an embarrassment of riches. There is practically no end to the number of internal and third-party data sources at their disposal. The question is: What data is relevant to the model?

Read more: Going from Raw Data to Trusted Analytics with Connected Data Prep

Almost everyone would agree that the volume and depth of clean historical data related to occupancy, rate and revenue figures (including booking dates, rate codes, arrival dates, departure dates and revenue by day) provides the strongest basis for forecasting accuracy.

Market-level data, including publicly available competitor rate information, also ranks as a must-have data source. Future flight demand, weather reports and geographical information (where guests are arriving from) may be used for forecasting purposes.

Web shopping data (the number of consumers looking at and booking rooms and at what price, as well as the percentage of visitors abandoning the hotel website) may also provide some insights into current and future room demand as well as price sensitivity.

Read more: Automating Financial Forecast for Hotels with Cloud Systems

The number of website visitors tends to correlate to the frequency of last-minute arrivals. Because consumers are shopping beyond hotel websites, there are insights to be gleaned from the travel distribution network, as well.

Another option is “customer worth data” on hotel rewards club members. Yet another potentially valuable data source may be user-generated content in social media. In the end, accuracy in revenue forecasting tends to be a matter of quality over quantity rather than the more the merrier.

Revenue managers may be excited about the ever-growing number of available data sources. But incorporating every last bit of data into their models can be a recipe for disaster. At a certain point, more data can simply mean more noise.

Intelligent pricing

With next-generation revenue management, the idea is to automatically forecast demand and capacity for a perishable product or service and then price that product or service in a way that maximises profits for the business.

Here a key concept to keep in mind is price elasticity of demand. Demand is sensitive to changes in price and price is sensitive to changes in demand. Generally, hotels have a lot of elasticity because the main product in demand — guest rooms — is both perishable and fixed in capacity.

Starfleet Research defines intelligent pricing as the science of making decisions for how to maximise room occupancy at the best possible price while factoring in all the related revenue questions in a real-time or near real-time manner.

Questions that intelligent pricing addresses might include: What is the optimal price to charge in order to maximise revenue, accounting for the fact that demand will change as the price changes? What is the best possible rate for a guest room, taking into account the type of room as well as the length of stay? How can a hotel ensure that discounted price promotions won’t dilute revenue and profits in the long run?

Read more: 5 tips to boost hotel direct revenue

Intelligent pricing addresses these questions by analysing demand forecasts, competitor rates, price sensitivities and various other inputs and factors, including demand drivers like seasonality, day-of-week differences and market dynamics.

Intelligent pricing is forever evolving with new approaches to forecasting demand and dynamically pricing room rates based on expected demand and capacity. For example, with the ability to price room types, channels and dates independently of each other, some hotels are adopting a pricing strategy based on the idea that different prospective guests should be offered different rates depending on which guest segment they fall into as well as which channel they are using for booking their reservation.

The important point is that intelligent pricing can translate into financial outcomes. Consider: A mere $2 reduction in the ADR for a 500-room hotel with a 75 percent occupancy rate would cost a hotel more than a quarter million dollars in lost profit in a single year. Advances in intelligent pricing are changing the revenue management game, enabling hotel operators to better optimise their business.