Data is central to the ongoing financial performance of a hotel today. With access to vast amounts of customer data, hotels can gain a deeper understanding of their customers, improve the guest experience, and optimise operations to increase efficiency and profitability. However, not all data is created equal and only the relevant information should be used by hoteliers to support their business decision making.

A key challenge hotels face in managing and analysing data is the sheer volume of information they collect. With so many data points available, it can be overwhelming to know where to start or which data sets to focus on. This is not going to get any easier in the future either, as the volume of structured data being generated is growing at an exponential rate.

Data also constantly evolves as market conditions change. New data is generated constantly, and if a revenue manager has to spend time analysing information manually – it is almost sure that that data points have changed by the time the analysis is completed.

The reality for hoteliers and their revenue management teams is there are far too many data points to analyse. And certainly, too many decisions to be made for any human to undertake accurately, without the assistance of automated solutions. 

How data supports hotel business growth

Data underpins decision making in the hotel sector today and good data can help lead to good business outcomes. For instance, through using accurate data to analyse booking patterns, hotels can identify high-demand travel times and adjust their pricing, leading to increased revenue. Additionally, by tracking on-site behaviour, hotels can identify areas where guests may experience issues and adjust to improve the overall guest experience. If guests frequently complain about slow Wi-Fi, for example, hotels can invest in upgrading their internet infrastructure to improve guest satisfaction and increase the chances of return business.

In addition, data can also be used to optimise operations and improve efficiency. By analysing data on room occupancy and staffing levels, hotels can adjust their staffing schedules to ensure they always have the right number of staff on hand. No hotelier wants to be caught short-staffed and face disgruntled guests who are dissatisfied due to long wait times. Conversely, it is a waste of money for staff to be sitting around underutilised because of not having enough work to do. Hoteliers should use guest demand data to support their staff planning, balance maximising the guest’s experience while keeping labour costs at efficient and profit-oriented levels.

The importance of forecast data

Forecast data and predictive modelling are essential in helping hoteliers plan for the future. It is important to note though, that it is not just about having access to more data in these circumstances but looking at the right data. The data sources that support hotel pricing decisions commonly include stay history, inventory history, future reservations, future inventory, competitor pricing and future rate information.

To build an accurate vision for the future, hotels must gather macro-level intelligence such as economic, search and market demand data to help determine how they impact market trends and travel intent. This information can be used along with granular-level data focusing on the transaction level and include benchmarking rates, channel, cost of acquisition, arrival and departure dates, lead time, length of stay, loyalty contribution—even at the individual travel agency or corporate account level.

The need for automation and analytics

Advanced hotel revenue management analytics use data mining, machine learning and a variable deployment of complex predictive algorithms sets to calculate optimal pricing and inventory decisions for hotels. Analytics assist hoteliers to move beyond their normal revenue management processes into harnessing their data and forecasting capabilities to explore, predict and optimise total revenue performance.

It is important to treat data fairly, but not equally. AI-powered advanced revenue management systems can help hoteliers stay ahead of competition through using the right data at the right time to support pricing and operational decision making.

Analytics within automated revenue management systems enable hoteliers to uncover granular patterns and trends at a micro-level. By determining why specific results are emerging, and if a property can expect them to continue, hoteliers can optimise their revenue opportunities today and into the future.

For more information on how your hotel can attract business from guests in an evolving market, please visit: www.ideas.com

Written by: Murphy Mathew, APAC Solutions Engineer, IDeaS

The views expressed in this article are an opinion only and readers should rely on their independent advice in relation to such matters.

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