Hospitality businesses, such as hotels and restaurants, that are still making decisions based on intuition or ‘what worked last season’ are quietly losing guests, revenue, and market share to data-driven competitors.
Hospitality data analytics flips the script by helping you spot booking trends, understand guest behaviour, and act quickly in ways that grow your business.
We have summarised our experience working on data analytics consulting projects in this article, showing with real examples, tools, key metrics, and practical steps.
Hospitality data analytics means analysing and interpreting data to improve the operations of a hotel or a restaurant. The primary data sources include guest, booking, and operations data from the booking and point of sale systems.
You already collect so much data through your POS, booking engine, social media and review platforms. Analytics helps you connect the dots.
It shows what’s working, what’s not, and where you’re wasting time or money.
And it helps you do something about it.
To get the most out of your hospitality data analytics, you should know the key performance indicators (KPIs) that matter most to your business. If you’re unsure, this is a good place to start. Here, we break down the different KPIs you can keep your eye on:
Hotels usually have a restaurant, so all the KPIs below are relevant to them. However, the KPIs in this section are only relevant to hotels.
Hotel data analytics refers to the process of automatic data extraction and analysis to improve the operations and revenue of all the hotel departments.
At Vidi Corp, we had multiple data analytics consulting projects with hotels. For example, last year we worked with an Australian hotel chain that stored its data in RMS Cloud. Our data engineers built an automated process to extract the data from the RMS cloud and store it in a SQL Server database.
Now, a single dashboard gives them access to all their important KPIs: revenue, daily room rate, booking trends, and occupancy levels. At a glance, they can see how each part of their business is performing: rooms, food, drinks, and even commissions.
The second part of the dashboard helps the hotel management to see the total number of bookings per month and the status of those bookings.
The team can also select a metric to see in all the charts below, from Average Daily Room rate, Occupancy rate, RevPAR, RevPOR and Total Gross. These metrics can be analysed by day of the week and compared year over year.
Finally, we analysed the average daily room rate per month for every room category. This analysis is designed to help the management reflect on the pricing decisions and see understand the fluctuations in price throughout the year.
With everything in one place, decisions are quicker and easier. The hotel staff now spend less time pulling reports and more time acting on them. Vidi Corp made the setup simple, and the results speak for themselves.
Restaurant data analytics refers to the process of analysing the restaurant occupancy, costs and revenue to ensure profitability and efficiency of operation.
Our data analysts have delivered many solutions for the F&B departments of the hotels and restaurant chains.
A hotel we worked with wanted to analyse staff cost as a percentage of revenue for breakfast, coffee, lunch and dinner. The analysis highlighted that the highest staff cost as % of revenue was for serving coffee due to the low ticket size. We also found that 2 people were assigned to this task during certain hours, which unnecessarily raised the staff costs.
We also compared the average number of orders with staff working every hour to analyse whether the restaurant managers schedule shifts efficiently with their part-time workers.
The restaurant manager uses this dashboard to track exactly how much each site is giving away in discounts. We analysed the total cost of discounts and also analysed what they are made of e.g. free meals for staff and external discounts to customers.
This analysis is important to create on site level so that it is clear which restaurants from the chain are relying too heavily on discounts to drive sales.
It is also important to analyse which channels drive restaurant sales. For example, our analysis highlighted that sales by à la carte, kids menu and Deliveroo required no discount, whereas Unidays and Testcard sales were mainly discount-driven.
We also analysed the sales by and discounts by restaurant locations to inform the expansion strategy decisions in the future.
For the restaurant group’s ops team, this dashboard replaced a mess of weekly reports with one clean view. It pulls in sales, margins, covers, and spend per head by brand, region, and day of the week.
The restaurant managers used to wait days for weekly sales updates. Now, they get it all in one snapshot: sales, margins, covers, and spend per head across brands. It’s helped them make quick calls midweek, catch underperformance early, and stop problems before they snowball.
This dashboard gave the restaurant group full visibility into how the delivery side of their business is performing, from sales to margins to average order value. In a simple interface, they see results by brand, geography, and site, and improve delivery strategy without flying blind.
This report analyses the performance of two major food delivery platforms, DoorDash and Uber Eats to help understand sales, order trends, customer behaviour, and operational performance. Each dashboard is broken down below for clarity.
This dashboard shows an overall picture of how the business is doing on these platforms. It shows total sales and marketing spend for Uber Eats and DoorDash
This dashboard helps spot trends over time, like whether sales are going up or down.
It shows:
This report analyses how much was spent on promotions via Uber Eats from January to December 2022, with a comparison to January 2023. The goal is to understand:
This helps optimise staffing, operations, and promotional timing.
This dashboard visualises sales performance and marketing efficiency over 13 months, highlighting volatility in spend and declining sales.
In the case studies above, you saw how others use their data to stay ahead. Now, we’ll talk about how yours can start working for you, too.
Raise or drop prices based on demand, seasons, or booking trends so you stop leaving money behind.
See guest preferences and personalise offers, room setups or menus because, as you know, it’s not the food or the bed people pay for, it’s the experience.
Examine your competitors’ pricing, promotions and reviews with analytics to know where you stand, what to improve, and how to outdo them.
Analytics lets you observe trends on which days or seasons are usually busy so that you can plan staff, supplies and inventory ahead.
You not only see which channels converted for bookings or walk-ins, but you also see which ones attracted high-paying guests.
You can keep tabs on delays, complaints, and service times, then fix what’s slowing things down or annoying your guests.
Analytics helps you recognise repeat guests so you can reward them and ensure their return without having to offer discounts all the time.
Know when extra hands need to be called in or when stock needs replenishing, so you are ready without overstaffing or wasting supplies.
Depending on what you want to improve in your hospitality business, you will most likely find yourself carrying out the following types of analytics:
See which items or services bring in the most revenue, how sales trend over time, and where to focus promotions.
Study how well your team is doing. Service speed, table turnover, staff attendance – all of it shows where things are smooth or slow.
Take notice of when people book, how long they stay, if they even show up, and what channels attracted them.
Find out which discounts bring repeat guests and which ones only eat into profits. Not every offer helps your business.
Keep an eye on how money flows daily, weekly, and monthly. Helps you manage cash, stock, and overall business health.
Your data already lives in the tools you use daily. This is a breakdown of the different places you can get data for hospitality analytics:
| Data Source | Data | Use |
| Booking Systems | Check-in/check-out dates, room/table type, booking channel | Observe booking trends, adjust pricing, and plan staff shifts |
| Guest Feedback | Reviews, surveys, ratings, and social media comments | Improve service, fix pain points, and find out what guests love |
| Operational Data | Staff shifts, service time, inventory levels, and wait times | Reduce delays, manage costs, and improve daily operations |
| CRM System | Guest profiles, preferences, and stay history | Personalise offers, track loyalty |
| Market Data Tools | Competitor rates, market demand, and local events | Benchmark pricing, predict high-demand periods |
| Website & Social Media | Page visits, clicks, engagement | Measure campaign success, find top channels |
Once you know where your data is coming from, the next step is choosing a tool that helps you analyse it.
The most common tools for data analytics are Power BI, Tableau, and Looker Studio. This breakdown should guide you in deciding which one of the three is best for your business:
| Tool | Use if | Budget |
| Power BI | You prefer clean visuals, easy report sharing, and already use Excel or other Microsoft tools in your workflow. | Free to $20/user/month |
| Tableau | You need really powerful dashboards, love to explore your data in depth, and want less restrictions on design. | $15 to $70/user/month |
| Looker Studio | You want to use a free tool with good integration to Google Sheets, Ads, or the rest of Google’s products. | Free |
Ironically, data analytics is 80% preparation and 20% actual analysis. This is the point many businesses miss. So, if you want to implement analytics and implement it right in your hospitality business, follow these steps:
Data analytics doesn’t start with ‘data’. It starts with you. Your business – the specific problems you want to solve. So, before anything else, figure out what you want to achieve in your business. It could be to increase direct bookings, reduce labour costs, or improve review scores. This guides everything that comes after.
When the business objective is set, the next step is combining your systems and data sources to see if you have the necessary data to meet it. You also want to make sure the data is accurate, consistent, and trustworthy for further analysis and use.
You probably have useful data sitting in three to five systems. That’s good, but analytics help you better when you’re able to connect all your data logically. To do this, you can use any of the tools mentioned above to integrate data from your key systems (PMS, CRM, POS). Depending on your use case, you may need something custom, i.e. custom connectors, to correctly integrate your data.
This can’t be overemphasised. You need tools that match your team’s skill level, your business goals, and your data size. No point paying for a tool that’s too complex to use or doesn’t connect to your systems. Go back to your objectives, then choose the one that helps you connect, visualise, and act on your data with ease.
You already have the data. Now it’s time to use it to make clearer decisions, improve guest experience, and grow sustainably. If you’d like a smoother, hands-off way to start, reach out to Vidi Corp Data Analytics Consultancy. We’ll help you make sense of your data and turn it into tangible results.
Booking info, guest preferences, service times, reviews, staff shifts, and more.
To improve pricing, plan resources, personalise guest experience, and keep watch on performance.
It involves using your hotel data to cut waste, boost bookings, and improve guest satisfaction.
