Understanding Hotel Analytics
While it is undeniable that there is a tremendous amount of data generated throughout the guest journey, for the vast majority of Hoteliers data analytics still remains an unexplored and overlooked domain. Most of the time they will find themselves trying to find the right balance between improving guest satisfaction and increasing profits. With both competition and customer requirements growing, they would generally rather focus on guest satisfaction than crunching numbers and data. Analytics often fall way down the daily operations list. Almost every industry is supported by software and if a business doesn’t have a deep understanding of their operations, customers and competitors, it is going to be hard to prosper and even harder to profit. Within the hospitality industry, competition is fierce with a constant influx of new supply and the continuing increase of optionality from the sharing economy. A hotelier’s willingness to both collect and analyse data can have a massive impact – not just on profitability but on reputation as well.
The aim of this article is not to provide a review of current data analytics and technologies associated with them, but it rather focuses on what data & data analytics is all about, what makes incorporating them so important and the benefits it can offer thought the entire organisation.
The Importance of Data
The significant role of data and data analytics is becoming an extremely important part of hotel management – and that too for a good reason. Incorporating data analytics ensures that you will be able to leverage on the information collected thought the entire customer journey and utilise it in order to improve service, revenues and profit margins. This will eventually lead in creating a culture where decisions are based on facts rather than gut feeling and moves the whole organisation from a reactive, problem solving approach to a more forward thinking and proactive tactics. Finally, this will lead in eliminating the current silos that exist in many hotels and ensure that everyone works from the same set of numbers and that strategies are aligned to serve the business as a whole.
Often viewed as “just information” Hoteliers can overlook that when data is analysed in the right way it can provide the answers to crucial business questions such as how to ensure revenue optimization and increase occupancy.
Hotel operators are beginning to recognize the importance of data and any hotel with a website or some social media presence already has access to significant quantities of data. However, there is a real need, not only to understand data collection but also how-to analyse it. For example, Google Analytics provide valuable information about how a website is performing and analysing customer feedback data can increase return on investment.
Like all businesses, hotels, too, are constantly generating data – important data that can be leveraged to not only improve the customer experience, but also bring about a significant impact in the revenue and profits of the business. Whether or not your hotel has the resources of a five-star international chain, it is essential for you to start collecting and analysing the data gathered on a daily basis. Using the latest software and systems will allow you to collect important and high quality data in a timely manner, and enable you to use this data to your advantage before it becomes obsolete.
Data analytics technologies will also allow you to make informed and data driven decisions that will prove to be beneficial for your hotel business instead of making decisions on a whim that may or may not be in the best interest of your business. Equipping your operations with the right technologies will also reduce the possibility of errors since all of the decisions that you make for will be based on insights of previous experiences instead of being based on what you feel or results that you expect without any real basis.
One of the biggest challenges faced today in trying to create and implement the right data culture is the reliance on legacy, stand-alone systems which handcuffs their ability of Hoteliers to aggregated and analyse information.
System integration is crucial to ensure that cross departmental data processing necessities are met and total spend can be accurately mapped. A seamless system will ensure constant communication between all outlets and provide with accurate, timely and complete information. Some of the internal systems in any hotel today include: Property Management System, Revenue Management system, Customer Relationship Management, Sales and Catering systems etc., while some of the external sources of data include: STR data, Social media, Rate shopping, Reputation management system etc.
It is all about Data!
Big Vs. Small Data
At the core of it, big data is a large set of data that, through analysis can reveal trends whereas small data exists on a more manageable scale, generated from sources such as a website or a hotel Property Management System.
Big data is a term that is often misunderstood but with big data the word “big” actually means large, thousands or millions of data points in common and almost always coming from external sources to the hotel. Examples of big data are weather, traffic or social media data – giant pools of information that can be sorted to find the relevant information required. Combined with internal data, they can provide a holistic picture and help improve marketing efforts, make loyalty programs more effective, better guest profiling and accurate personalisation, enhanced pricing strategies, efficient inventory management etc.
Small data, while without the name impact of small data, is just as valuable and when properly structured becomes actionable information that can make a quick, significant difference to operations.
But is it all about size? While a big set of data can provide a more thorough and in-depth view, what is even more important is data quality.
The major pillar behind any accurate and valuable analysis is accurate data. It is, therefore necessary that hotels should keep proper records of past events, trends, guest preferences etc., in order to project accurately into the future. Although the diversity of the data points could make the task even challenging, having a data culture in your hotel will make it easier as the importance of accurate data is easily understood and implemented by everyone.
Ensuring that data stored by hotels is accurate can provide significant business value and can not only improve guest satisfaction but lower operational costs and maximise profits.
Structured Vs. Unstructured Data
In addition to the size of data (big and small) there are two ways that data is compiled;
Structured Data – is comprised of data that is clearly organized, labelled or categorized. They provide a streamlined way to easily filter out the data in order to create fast and actionable insights. For example, when a new reservation is added to your property booking system, the information entered on the guest such as arrival and departure dates, room type etc., can be easily filtered to better understand booking tends due to the data being sorted or structured.
Unstructured Data – is data that is presented in a disorganised way that makes filtering and searching difficult, but still have the potential to provide valuable insights to a hotel. In most cases, unstructured data come from external sources. An example of this type of data is Review and ranking info from OTA’s or TripAdvisor, although they are data that cannot be collected, stored and sorted easily, they are nevertheless an extremely valuable aid to decision making.
Types of Data Analytics
While we spoke enough about data and their different forms let’s have a look at the different types of data analytics and what differentiates them.
Descriptive Analytics – is the most straightforward and traditional form of analytics for generating insights. They can be used to describe past events and trends or provide with a picture of how business is performing for the future. Descriptive analytics is used in everyday hotel operations for tasks like populating pick-up reports, performance reports, occupancy statistics etc.
Predictive Analytics – go a step further, they are a form of advanced analytics which is used to make predictions about unknown future events. Predictive data uses large groups of past data to analyse parts trends and predict what may happen in the future. An example of this is Forecasting. Past performance data are used on a very detailed level, usually by day of the week, by segment to provide a guide in producing an accurate estimation of how a specific month, day or segment will perform in the future.
Prescriptive Analytics – go even further than predictive analytics. While Descriptive analytics show what happened and Predictive analytics indicate what could happen, Prescriptive analytics try to guide the process of what should be done in a specific occasion. With the assistance of technologies such as data mining, statistics, machine learning, etc., they analyse current data to make predictions about the future. They are a form of advanced analytics that incorporate algorithms to predict unknown future events. They include big data, such as weather forecast, airline statistics, review scores, ranking etc., to provide with the best possible course of action.
Applications of Hotel Analytics
Data analytics can be a powerful tool for any hotel, from developing customer centred marketing and pricing strategies to increasing ROI.
Personalized marketing and loyalty analytics – by tracking and processing guest behaviour hotels can provide them with personalised offers that can be more effective. An example of this application would be sending an email to a frequent guest to give them a coupon for a free drink on their next visit.
Revenue Management – is the application of disciplined analytics that predict guest behaviour at the micro-market level i.e. selling the right product to the right guest at the right time and the right price. The essence of this application is the understanding of a guest’s perception of value.
Operations Analytics – Energy consumption accounts for a big chunk of the utility costs for a typical hotel. Data can help hoteliers to keep costs controllable without sacrificing guest comfort by using energy more efficiently. Statistics in operations can also be used to better schedule and manage human resources. This will lead not only to saving in payroll but also in increased customer service by efficient staffing
Operations Analytics – Energy consumption accounts for a big chunk of the utility costs for a typical hotel. Data can help hoteliers to keep costs controllable without sacrificing guest comfort by using energy more efficiently.
Investment Management – Another way to use analytics for the hotel industry is for financial performance. An example of this would be refurbishing the lobby and some of the rooms and then monitoring the difference (if any) in booking rates and customer satisfaction to make a data driven decision on future investment.
Today’s digital environment had brought about a new generation of hoteliers looking to monetise their data by acquiring actionable insights. Hotels now have an abundance of new data than previously seen with paper transactions and manual processes and hotel professionals can now gather information through purchased or leased resources.
Data analytics are now much more manageable and distributed analytics can be implemented to increase performance, guest loyalty, reduce waste and improve sustainability. The key to effectively enhancing a guest’s experience through analytics is to collect the data in a non- invasive way, using information from past bookings, third parties and various forms of feedback. Hotel data and analytics are key contributors to building stronger relationships with guests and ultimately driving better guest loyalty, revenue and profitability.