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8 Steps to Improving Demand Forecasts
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Courtesy: Eric Stoessel, Vice President of Marketing | News Source:

Because hotel rooms are perishable goods with a shelf life of one day, it’s important for hoteliers to maximize their value. The clearer the picture you have of upcoming demand, the better you can prepare accordingly in many phases of operation, from staffing to marketing to pricing.

Forecasting upcoming demand allows you to identify needs and build a strategy based on projected occupancy. Forecasting is a complex discipline and can be overwhelming at first, but it can be broken down into simple steps.

However, it’s critical for hotel management to have a good understanding of their performance goals in terms of occupancy, rate and ultimately revenue. For example, if a popular event in the area brings a number of new guests to the door, forecasting helps hoteliers understand how to price to maximize revenue. In addition, it’s the first step to understanding when it may be necessary to lower rates to boost occupancy on days with lower demand.

Simply put: A forecast is a basic tool used to run a hotel more effectively and profitably. Hoteliers can begin building daily forecasts by segment rather easily. The following are eight tips for improving demand forecasts:

1. Use the right data

A basic forecast can be as simple as some notes on pen and paper, and as complex as computing algorithms that produce precise and accurate projections. But a forecast is only as good as the numbers that go into building it.

Some hoteliers often make the mistake of biting off more than they can chew. While the amount of data available can be exciting, it’s important to include only what is going to truly make a forecast more accurate.

Beginners start by exporting Excel spreadsheets from their property management system. The first step is to look at historical data from a hotel’s own system that shows occupancy, rate and revenue figures from prior years. The further back a hotel has data, the more accurate a forecast will be. A hotel that has been open just one week will not have as good a base for a forecast as a hotel that has been open for a decade. Three years of historical data provides a great look at business and helps project a more accurate forecast, but even a year or two’s worth of data is helpful.

The most important data to include is booking date, rate code, arrival date, departure date and revenue by day. Once historical data is present in Excel, hoteliers can add, tweak or manipulate the data to make forecasts more accurate. The first numbers to incorporate are upcoming reservations that are already on the books. The more business on the books, the more accurate a demand forecast will be.

Market-level data, such as future flight demand, weather reports and geographical data, such as where guests are coming from, is yet another important source for more complex forecasts.

2. Segment your forecasts

When forecasting, it’s important to segment different parts of your business from the get go. Historical data should be extracted for both group and transient separately, as well as any business that is currently on the books for each. Build a forecast for both group and transient business and analyze them separately before overlapping them further down the line.

In forecasting both group and transient business, looking at prior-year booking pace can give you a good idea of what to expect and how much anticipated demand will actually materialize. New calendar events like conventions may lead a hotel to expect added group demand over prior years.

You can improve the accuracy of forecasts by taking length-of-stay into account. It’s important to measure demand by both arrival day and length-of-stay. Sophisticated managers will prepare multiple forecasts per reservation day based on predicting whether guests will be arriving for one or multiple nights.

If you can further segment your business into clearly defined groups that share booking behaviors, your forecasts will be more accurate and actionable. When possible, break down the transient segment into further subsets of customers and channels with similar behaviors. Do customers pay a similar price when booking through a collection of channels? Do they tend to book at around the same time in a booking window?

For example, customers shopping opaque online travel agencies may shop well in advance and be more price conscious than those booking directly. Forecasting them separately is the first step to yielding them independently of each other.

3. Monitor your hotel website

There are many more complex factors that can determine the accuracy of a forecast. One simplified way of determining the popularity of your hotel on a certain day is by monitoring your hotel’s website traffic.

Tracking web-shopping behavior can get highly complex, but it can provide valuable insight on current and even future demand. It can shed light on how many people are visiting the website, which can help gauge the frequency of last-minute arrivals.

If you can track how many people are visiting the site versus how many are booking for future dates, you can see a much clearer picture of true demand. If you can see at what prices those customers are booking, and more importantly, when they are abandoning the site, you can gain incredible insight into the price sensitivity of those customers.

Getting an idea of how many potential guests are looking at your website is another dataset that can be worked into the forecast.

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