Unleashing the Power of Hotel Analytics: From Data to Decisions
By Hoteliers have not, historically, been all that hot on data analytics; at least outside of finance and marketing. But times are changing. The hotel industry is increasingly recognising that hotel data analytics have an important role to play in increasing efficiency, optimising retention strategies, improving decision-making, and conserving profit margins – all high on the agenda as we head into 2024.
What is hotel analytics?
Hotel analytics is collecting and interpreting data (sometimes called “big data”) to provide insights into operations and performance. Since hotels are complex, multi cost centre businesses, the utility for data analytics in the hospital industry is wide-ranging. Effective hotel analytics can revolutionise everything from inventory and purchasing, to recipe management.
How can hotel analytics benefit your business?
Like any tool, the value of hotel analytics lies in how well it is used. Overall performance is determined by various factors, each governed by a number of different departments. Some, such as finance, will already have a high level of data literacy, whereas departments such as guest services or food and beverage (F&B) might be less familiar with business analytics for hotels.
This can lead to data silos, where each team records their own data, often logging different figures for the same metric, or data analysis at a department level without considering the insight gathered by other departments. For hotel owners embarking on a data project, the first step should be to centralise data collection and analytics.
By centralising data sources, businesses have access to a holistic overview of operations. They can see how demand fluctuations impact each department, and can identify patterns in one aspect of the hotel that impact others. Visualisations of all the customer data in one place also make it possible for those in the hospitality industry to identify potential service gaps.
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Key analytics and metrics by department
One of the first steps in centralising data is to agree on which metrics you will be recording throughout the business, document how they are calculated, and ensure this information is readily available to any staff with responsibility for hotel analytics.
This ensures that every data point recorded is consistent, and means that metrics can be accurately compared across departments.
There are a range of metrics commonly used by each department for hotel analytics, we’ve detailed a few of the most commonly used below.
Front Office
Occupancy rate measures the percentage of hotel rooms occupied on any given night. Understanding planned occupancy rate, as well as actual occupancy, is essential for both predicting demand in other areas of the business – such as health centres or restaurants – as well as tracking no-shows.
The average July occupancy rate in the UK 2021-2023 was around 77%. However, occupancy rates are incredibly changeable depending on season and location, which means national benchmarks are of limited use to individual businesses.
By leveraging hotel analytics to understand what a realistic average is throughout the year for their specific business, hotel owners can increase the accuracy of forecasts and make better decisions regarding reasonable growth targets. They can also utilise dynamic pricing to adjust to changing occupancy rates, as well as competitive context, and increase profits.
Average Daily Rate (ADR) measures the average revenue earned per occupied room. As such, it is directly correlated to occupancy rate and has a significant impact on profitability and hotel revenue.
For those struggling with low occupancy rates or looking to boost ADR, promotions and special offers during quiet times are valuable tools. Hotel analytics shouldn’t be completely internal, take the time to research competitors, determine if they’re offering better value, and adjust your pricing strategies accordingly.
Revenue per Available Room (RevPAR) provides a comprehensive assessment of both the occupancy rate and ADR, and is simply room rate multiplied by occupancy rate. It provides insight into overall revenue and allows for more effective revenue management.
Reservation Conversation Rate (RCR) allows operators to track the number of hotel website or phone enquiries that result in bookings. Using hotel analytics to track these engagements can help to highlight if there are any issues with the customer journey – such as a broken or difficult-to-find booking form.
Operators that want to maximise this conversation rate should consider offering online incentives, ensuring their website is clear and compelling, and that front desk staff are trained to manage enquiries and bookings efficiently and politely.
Check-in and Check-out times: how quickly can guests check in or out? Are they queuing for long periods, or expressing frustration at the process? Both are key points in the guest experience and can have an outsized impact on a guest’s perception of the hotel.
If collecting this data for your hotel analytics programme highlights an issue with either, consider investing in technology to make the process more efficient, optimising staffing levels during peak hours and providing self check-in options.
Read how Four Seasons leverage Fourth’s forecasting model to forecast demand and optimise labour deployment.
Housekeeping
Room Turnover Time measures how quickly rooms are cleaned and made available for the next guest. An excessively slow turnaround time can delay guest checking in, or even reduce overall occupancy.
Hotel managers can reduce turnover time by streamlining the cleaning process and ensuring housekeeping staff are well-trained and that the team is adequately staffed.
Cleaning quality score: Guest feedback surveys are one of the most important hotel analytics tools in your arsenal. They need to be kept concise to maximise engagement, but should absolutely include a section on room and hotel cleanliness.
Operators repeatedly receiving poor feedback on cleanliness can then address specific feedback and implement quality control measures to improve the experience of guests in the future.
Maintenance Response Time is a metric that is often overlooked, but it is critical since it tracks the time taken to address and resolve maintenance issues – often a key contributor to a poor customer experience.
Implementing a maintenance tracking system can make reporting on this metric much easier and allow staff to assess and prioritise more urgent issues.
Food and Beverage
Revenue per Available Seat Hour (RevPASH) is an efficiency measure for F&B operations and shows the revenue generated per seat during a specific period.
Understanding how RevPASH changes throughout the day and week allows operators to optimise F&B revenue. High RevPASH indicates busy periods, ensuring staff turn tables over quickly at these times is the best way to maximise revenue. Conversely, times when RevPASH is low suggest less demand, so training staff to upsell during these shifts is a more effective way to maximise RevPASH.
Table Turnover Rate is another measure of efficiency and shows how quickly tables are cleared and re-occupied. Factoring this metric into your hotel analytics is critical, since your F&B venues have limited capacity the table turnover rate forms the basis for a number of other calculations, such as the labour budget.
You can boost table turnover rate by streamlining service and payment processes, and ensuring you have enough staff scheduled to cover demand.
Menu Item Profitability keeps track of the most and least profitable items on your menu. Understanding this helps kitchen staff to manage inventory, and provides direction on which items to upsell or promote.
Regularly analysing sales data and adjusting pricing for underperforming items is a good way to maximise this, and has the added advantage of helping to reduce food wastage from less popular items.
Inventory management is one of the main applications for hotel analytics programmes. Understanding demand and inventory levels is easier said than done in a business as complex as hotels – inventory represents a huge amount of invested capital, is distributed throughout the business and is drawn on by multiple departments – the bar might stock drinks that account for room service or even spa revenue, for example. Which makes keeping track of stock levels in real time impossible without a centralised analytics system. There are a number of metrics to consider within inventory management:
- Par Level: this is the minimum quantity of each item that a hotel needs to hold to prevent stockouts and reduce waste. Regularly reviewing sales trends and monitoring supplier performance are key to optimising this.
- Inventory Turnover: keeps track of how quickly inventory is sold or used, optimising cash flow while preventing overstocking. Tracking this in real-time with hotel analytics means operators can offer promotions on slow-moving items and make sure they’re sold ahead of expiration dates.
- Stock-to-Sales Ratio: is a measure of the current inventory levels to sales, and is invaluable for guiding inventory management decisions. If managers find this ratio is creeping too high, they can adjust ordering quantities based on forecasted sales and optimise stock levels.
Day Sales of Inventory (DSI): charts the average number of days it takes to sell the entire inventory, this is vital for inventory planning and helps to avoid stock becoming out-of-date. An effective demand forecast is the best way to maximise DSI and ensures you’re not holding more inventory than you’re likely to sell.
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Finance and Accounting
Profit Margin is the percentage of revenue left once all the running costs have been subtracted, and is the key measure of a hotel’s viability.
The goal of hotel analytics is to optimise operational efficiency across the board, and can be an effective tool for maximising profit margin once implemented. Controlling costs and investing in growth strategies are other common options for hotel owners seeking to increase profitability.
Average Daily Spend per Guest does exactly what it says on the tin, and measures how much guests typically spend per day on site. Understanding guest spending behaviour can help to forecast demand throughout the business and identify areas for upselling. For example, if most guests spend in F&B, there may be opportunities to run promotions to encourage them to spend in other departments, such as Spa or Leisure.
Accounts Receivable Turnover measures how effective the hotel is at collecting payments from customers. Effective credit policies, discounts for early payments, and regular credit reviews of corporate clients are all common strategies for optimising this and maximising cash flow.
Guest Services
Customer Satisfaction Score (CSAT) is the metric most hotels live and die by, at least internally. It tracks guest satisfaction over time, and is correlated to online reviews and repeat business, which both have a direct impact on long-term profitability.
CSATs are easily collected via a customer satisfaction survey, and can be helpful for identifying departments that are struggling. Analysing staffing levels in these areas and ensuring staff are adequately trained and resourced is the first step in increasing flagging CSAT scores, but a culture of continuous improvement goes a long way towards ensuring guests consistently have a fantastic experience.
Repeat Guest Rate shows the percentage of guests who have stayed at the hotel more than once, a high repeat guest rate is indicative of a high guest experience, and is a good measure of the overall effectiveness of the business.
A loyalty program that provides returning guests with exclusive promotions can help to optimise the number of guests that return. Similarly, taking the time to provide extra touches for returning guests, such as flowers or a note from the manager in the room, can help them feel valued and enhance their experience.
Response Time for Customer Requests shows the efficiency of service and, by extension, the guest experience. A long response time can be considered indicative of poor service.
To ensure response times are fast, operators should focus on training staff in efficient communication and implement processes that make the prioritisation of requests clear to everyone.
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Hotel Analytics Tools
Hotels are complex, multi cost centre businesses, and understanding exactly which part of the business generates revenue – and which might not – is vital to optimising performance. Effective analytics forms the basis for automation, and tools like Adaco can even allow operators to automatically generate transfers and movements to account for department revenues that rely on input from other areas of the business.
Understanding what your objectives are for hotel analytics should be the starting point for any project, and will help to determine the right tools to invest in.
Operators with excessive labour spends and brands known for high levels of service, for example, might be seeking to understand demand so that they can optimise their workforce. While those struggling to manage rising ingredient costs and availability might be more focused on hotel analytics to help track and manage their supply chain.
Four Seasons, for example, uses hotel analytics to deploy labour to meet customer demand. Leveraging Fourth’s Workforce Management solution, it has been able to increase scheduling efficiency, ensuring a high standard of service without overstaffing.
Conclusion
Hotel analytics is a transformative tool that is empowering operators to understand every aspect of their business, giving them the insight to make data-driven decisions and optimise for success. By harnessing insights from occupancy rates, revenue trends, and guest behaviours, hoteliers can streamline operations, enhance the experience for guests and maximise profitability.
Hotel analytics isn’t just about numbers — it’s about informed strategies that boost revenue, improve efficiency, and elevate guest satisfaction. In a dynamic industry, hotel analytics isn’t a luxury, it’s the key to staying ahead in a quickly evolving hospitality sector.