Today, data drives decision making in the hotel sector, and high-quality data can significantly enhance business outcomes. Accurate, insightful data enables hotels to better understand their customers, improve guest experiences, and optimise operations—boosting both efficiency and profitability.
Data is crucial for enhancing the financial performance of hotels today, yet the process of collecting and analysing it to improve business outcomes is complex and fraught with potential for human error. Given the vast number of available data points, it can be overwhelming to determine a starting point or decide which datasets to prioritise. This challenge is likely to intensify in the future, as the volume of data generated by (and for) hotels continues to grow exponentially.
As a hotel manager you must recognise that not all data is created equal; only relevant information should guide business decisions. Understanding which data to use in various situations is crucial. So, how do you know which data is relevant in different situations, and how can automation help you surface insights to support better decisions?
Understanding key hotel data types
In hotel management, effectively leveraging various types of data is essential for optimising operations, enhancing guest experiences, and boosting property revenues. Key data types that hotel managers should master include:
Booking (and related forecasting) data
- Crucial for future planning, this data allows you to predict room demand. This data is also an essential input for pricing strategies, marketing campaigns, and revenue optimisation. It also aids in forecasting future income and expenditures, facilitating accurate budgeting. With a clear view of expected revenue and expenses, you can make informed decisions about capital investments, renovations, and other financial commitments.
Long-term forecasting is vital for strategic planning for any hotel, playing a critical role for owners and investors. This data helps hotel chains make decisions about new locations, expansions, or market contractions. It also supports the assessment of entering new markets or investing in new property types.
To create accurate forecasts, you need to rely on various data sources, including a property’s booking history, inventory history, future reservations, future inventory, and other pertinent data.
Additionally, you should incorporate macro-level intelligence such as economic, search and market demand data to help determine how they impact market trends and travel intentions.
Customer data
This comprises of data collected from guests through various touchpoints like booking channels, on-site interactions, feedback forms, and social media. By analysing this data, you can identify patterns in customer behaviour, guest preferences, and satisfaction levels – all of which can enable you to personalise or improve services to help enhance guest stays. For instance, if there are frequent complaints about slow Wi-Fi, you can use this feedback to justify investing in upgraded network infrastructure to improve guest satisfaction and increase the likeliness of repeat business.
Beyond guest perception data, an accurate understanding of each customer’s true value, which extends beyond room-rate expenditure is necessary. To grasp the full value of a guest, it is essential to consider their lifetime contributions, integrating data from all transaction systems. This ideal, holistic view should encompass everything from food services and day spa usage to purchases in guest rooms and gift shops, as well as the costs associated with different booking channels. Recognising your most valuable guests allows you to implement targeted strategies that make these individuals feel appreciated and recognised, fostering long-term loyalty. Examples of this include providing VIP check-in counters for loyalty members, coupled with free Wi-Fi for return guests, and other tailored perks, all of which enhance the guests sense of being valued and encourage repeat visits.
Operational data
This encompasses information on daily hotel operations such as room availability, occupancy rates, staff allocations, and revenue per available room (RevPAR). Such data is crucial for managing day-to-day operations and formulating short-term strategies.
By analysing data on room occupancy and staffing levels, you can optimise staffing schedules, ensuring an appropriate number of staff are available to meet guest needs. Overstaffing leads to unnecessary expenses, while understaffing can result in guest dissatisfaction due to long wait times. By effectively integrating operational and forecast data, you can balance enhancing guest experiences with maintaining labour costs at efficient and profit-oriented levels and operate the hotel in a much more sustainable way.
The need for automation and revenue management technology
Data is constantly churning with changing market conditions, leading to the constant generation of new information. If a revenue manager relies on manual methods for analysing this information, it is almost certain that the data points will have changed by the time the analysis is complete.
The reality for revenue management teams is that the sheer volume of data points to analyse and act upon can be overwhelming. The multitude of decisions required for optimal revenue performance is too complex for any individual to handle well without the assistance of automated solutions.
Advanced hotel revenue management systems (RMS) leverage data mining, machine learning, applied AI, and clever predictive algorithms to calculate optimal pricing and inventory decisions for hotels. These systems enable you to move beyond traditional revenue management processes by fully harnessing data and forecasting capabilities and breaking down the data silos that currently exist in many hotels. This allows you to explore, predict, and optimise total revenue performance.
Today’s RMS technology allows you to identify granular patterns and trends at a micro-level. By determining why specific results are occurring and predicting whether they will persist, hotel revenue managers can effectively optimise revenue opportunities both now and in the future.
