Human minds are inherently prone to biases. Isn’t it? In hotel revenue management, biases can be your worst nightmares since these can result into imprecise conclusions. And, inaccurate conclusions often equal to missed revenue opportunities.

Look, either you have a crystal ball that empowers you to know how much will be the average length of stay for varied rate categories in your hotel or what will be the occupancy percentage for “x” number of room nights and many more. Does that imply you’ve got to sit back and wait for the results to pan out? Of course not!

That’s why room demand forecasting is so critical for effective planning and quick decision making. In fact, an improvement of 10% in forecasting accuracy can result in a surge of 1.5% to 3% in revenue generated from a revenue management system.

And before you keep reading: why you need room demand forecasting? Check out this blog here.

In this post, let’s discover how you can improve your hotel demand forecast approach and maximize your hotel’s profitability manifold with better pricing.

You already know it – profit maximization is your key KPI as a revenue manager, while that includes optimum room pricing (that’s influenced by demand forecasting) and also cost reduction. The more accurate and clear demand picture you have, the better you can strategize your staffing, front desk, housekeeping, marketing, operations and pricing. This also helps you resurrect your revenue management strategy based on projected upcoming demand.

Let’s face it – demand forecasting is a complex discipline. But you can master it with a smart approach that ultimately helps you understand how to price your hotel rooms optimally to maximize your revenues. Simply put, this strategic management tool helps you become proactive in managing your inventory and prices smartly to boost your hotel’s profitability.

1. Big Data, Big Revenue Opportunities

It’s 2016. Yet, many hotel industry players across the world still rely on their guesswork and instincts for forecasting. However, some smart revenue managers embracing technology strategize using information from tools with scientific algorithms that employ various statistical models like exponential smoothing, moving average etc.

PMS, home to mountains of historical as well as future data, was traditionally used to understand the scope of upcoming demand across different room categories, length of stays, guest segments, and other data points such as booking pace, weather, etc. Hoteliers used to turn to the historical booking information available, recreate past booking curves and compare the pace of bookings. However, those pricing decisions were not reliable.

Fortunately, with more and more technology adoption, Big Data has made inroads into the fabric of the hotel industry and emerged as a game changer for hoteliers. It’s here to stay and has brought about a paradigm shift (look ahead, not back!) in the hotel demand forecasting been done so far.

Today a lot has changed or better to say, more evolved– customer segments, customer behavior, etc. We have piles of competitor pricing information available too. Pro Tip: Not all data is the right data. So beware!

Then we have other data sets that can be taken into consideration while taking pricing decisions:

• Macroeconomic Factors: Some trigger events (either in source market or travel destinations) like conferences, holidays, conventions, events, economic development, citywide transport changes can cause a shift in demand patterns.
• Reviews and Ratings Information: Good reviews lead to a spike in demand that implies you can increase your prices while maintaining occupancy levels.
• Weather Impact: If you run your hotel in a weather-driven market, impact of weather is an important parameter. Good date can boost demand and vice versa.
• Web-shopping regrets and denials: Customer browsing behavior and booking activity/inactivity can reveal good insights for you. By layering in this information into your forecasts, you can get a more accurate picture.

All these factors and wealth of information can help a modern hotelier understand market demand much better and build an accurate demand forecasting picture well in advance to make profitable rate adjustments and sell more inventory at best possible rates.

2. Track Web Shopping Behavior

To be able to build optimal price points, a hotel needs to forecast unconstrained demand. And for that, it’s imperative to look at the hotel’s denials and regrets. And thus, website data is a crucial source for these. If you wish to determine the popularity score for your hotel on a given day, look at your hotel’s website traffic. The valuable web insights can help you get a clearer picture on your current and upcoming true unconstrained demand by unraveling details such as your website visits that reflect the frequency of last-minute arrivals. You will also be able to see as to how many website visitors are you attracting to your hotel’s website at a certain time on a specific day.

If you can analyze the website visitors’ data vs. future date bookings, you can build an accurate future demand picture. You can also determine the price sensitivity of your customers by assessing the prices at which consumers are making bookings and their site abandonment rate (due to rate controls or inventory limitations).

But it’s Not as Easy as it looks! You must be able to capture the accurate difference between denials and regrets, which is tough. Some hotels use CRS data to track this. Internet has also empowered hoteliers like you to collate bulk of consumer shopping data. You can easily find out now as to how many bookers landed up on your website but did not finish the booking.

This customer loss data reflects on the latent demand but only if you have a clear picture of denials and regrets as mentioned above too. However, you can fall prey to miscalculating the latent demand if you use multiple distribution channels as again for every channel you need to clearly distinguish between denials and regrets. As a revenue manager, you can utilize this data to determine the conversion rates and plan the roadmap to recover from the site abandonment.

3. Competitive Intelligence and Competitor Pricing 

Besides the deep analysis of your hotel’s web shopping data, competitive intelligence and competitor pricing can also help you make accurate demand forecasts. You must identify a competitive set (similar to your property size, consumer segment and comparable pricing model) that you need to set your eyes on. Then, glean their demand by fetching and analyzing their room rates using some price intelligence tools across various distribution channels, GDS and their brand websites. If your competitor makes any change(s) to their price, it can impact your demand since it might be the strategy of your competitor to acquire your customers. Thus, competitor pricing can influence price-sensitive consumers. It can also have an indirect impact on your demand if you (as a revenue manager) make rate adjustments to combat the price challenge thrown by your competitors.

Conclusion

Hotel revenue management has emerged as an important discipline that entails ever-changing consumer behaviors, new age channels, varied pricing models, lean booking window, and may more aspects. Amidst all this, accurate demand forecasting is the jumping pad to maximizing your revenue and hotel’s profitability.