The Importance Of Hotel Business Intelligence Tools – Data analysis is one of the key directions of digital transformation in various industries, including travel. And the hospitality industry is no exception: The hotel industry, by its very nature, runs on a lot of data. Sources range from inventory to distribution channels, from customer behavior data to business records. As the business grows, it is not possible to analyze and track them manually or with spreadsheets.
It exists to solve the problem of capturing and understanding data. It is a set of tools designed to collect data from multiple sources and transform raw information into meaningful form.
The Importance Of Hotel Business Intelligence Tools
Today we will look at the specifics of using BI in the hotel industry. We define the specifics of business intelligence for hospitality, the benefits it brings to businesses, and the pitfalls of integrating with industry-specific systems. We will also look at the provider market to get a clear view of the features on offer.
Hotel Reports And Analytics
Before we start discussing actual BI use cases, let’s look at the key components of all BI systems and which data sources can be used across hotels.
Business intelligence systems take care of extracting data from various sources, transforming it, gathering it in a centralized repository, and finally querying that repository to present the data as meaningful graphs and diagrams that people can use.
Hotel data sources. The data source can be any internal/external system that contains valuable data about your business, metrics, customer information, etc. Property Management System (PMS) and its modules like Revenue Management System (RMS) or Central Reservation System (CRS) and channel management can be considered the main sources of data in the hospitality industry.
In the image above you can see the structure of the PMS and its modules. Each of these modules can also serve as a data source, whether it’s website analytics, a delivery management system, or housekeeping.
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If you look across the industry, different types of PMS structures can be found. Some hospitality businesses may need a separate revenue management module, some may not, combining it with RMS. The number of components and data stored in the hotel determines the general data structure within the organization. With the numerous areas of activity in the hotel business, the data structures will also vary. When it comes to BI, it presents challenges in determining the right data for analysis, but we’ll get to that point later.
Check out the hotel industry data map to get a general idea of the different resources available.
Extract/transform/load or ETL tools. This part of the BI system is intended for the automatic transfer of data from one system to another. In this process, the data is cleaned, enriched with metadata, and structured so that the system and its users can understand it.
Data warehouse/lake. Depending on the process and amount of data, BI systems may require dedicated storage. Warehouse and data lakes are specific types of storage designed to work with large volumes of data.
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BI user interface. Finally, all data is presented through a user interface. These allow us to query the data and visualize it. BI would mostly work with historical data when creating visuals or reports. But in some cases, real-time data can also be processed, e.g. streaming data from IoT devices.
Due to the number of data sources and types of information available, modern BI systems offer a relatively holistic view of hotel activities and metrics. Let’s take a closer look at the main ones, but keep in mind that this list is far from exhaustive.
Hospitality strives for an exclusive and unique approach to each individual customer. Guests can be segmented by demographics, geography, behavior, etc. All of this data comes from website reservations, purchases through POS systems, CRM, or anywhere else where personal preferences are displayed. As a practical use case, customer segmentation can help you consider personalized offers or take advantage of new customer experience opportunities.
Occupancy rate is one of the main hospitality metrics that shows what percentage of units are occupied during a period of time. Getting past occupancy rates from your PMS gives you the ability to analyze what factors have affected it in the past and make forecasts for the future.
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For example, you can compare annual data and analyze what affects occupancy, whether it’s seasonal changes, events, changes in the competitive market, or your own pricing/marketing strategies. This way, you can find out which trends appear regularly and how you can react to them to optimize your income.
Yield management is a complex discipline that considers hundreds of factors to predict optimal prices and create target yields. Revenue management operates several KPIs such as
One area of interest for revenue management is demand forecasting, which relies on hotel bookings and market data. By obtaining market data and using historical information on your own bookings, all KPIs can be taken into account for analysis. If you choose a custom solution, a number of advanced methods can be used, including data from search engines or other publicly available sources to create demand forecasts.
Below you can see an example of a dashboard that provides revenue managers with marketing cost per booking (MCPB) and net revenue growth statistics.
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As machine learning advances, business intelligence data can be used to automate rate changes and introduce dynamic pricing.
Instead of manually analyzing this data, ML models can be trained on your historical data to identify trends and suggest optimal prices for that period.
A single hotel can have hundreds of partner distributors (OTAs, GDSs, bed banks, etc.) that connect through channel managers. When selling rooms through indirect channels, channel managers consider each channel’s distribution costs (commissions and taxes). BI can provide insight into the revenue generated by each channel and compare it to distribution and other costs. This makes it easier to understand which partner distributors bring value to your business.
In addition, if you are bound by rate parity agreements, analysis of distribution channels can help identify distributors that violate rate parity and contribute to revenue leakage. A number of vendors—discussed below—are proposing automatic rate differential alerts on channels that disrupt the status quo.
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Hotels operate in a highly competitive environment. So understanding what your competitors are offering customers is essential. There are a number of ways hotels can access market data, such as using data from market consolidators (STR, HotelMarketData or HotelTechReport) or just scraping the prices of your direct competitors in the region. In any case, BI will represent a competitive advantage for the hotel to help optimize pricing/marketing strategies.
This is just a short list of the problems that modern BI systems solve in the hospitality industry. Unfortunately, there are barriers to adoption. Let’s talk about them.
Despite the benefits that BI can bring to the hotel business, there are some challenges that need to be addressed.
As mentioned above, hotels work with a lot of data sources, each of which stores different information in different formats. To integrate a data platform into your business, you must first determine what data will be used for analysis and what the purpose of that data is.
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The business domain makes the task specific to the hotel industry: Multiple properties can have different infrastructure and types of stored data. So the choice of data sources will depend on the analytical purposes. This task is traditionally handled by a data science team that can analyze the information you have. However, the business side of the selection remains at the discretion of the hotelier.
BI as a technological concept represents several software tools that will be integrated into your internal infrastructure. Linking between systems will allow BI to automatically extract the required data from its source, apply transformation and upload pieces of information to generate reports and visuals.
Integration between the two software systems is provided through an application programming interface or API. It is a type of connector that allows software programs to exchange data and access each other’s functions. When it comes to hotel software, there are three basic categories of systems:
To integrate one software system with another, the API should have an open specification. In the case of a closed API, PMS vendors will be responsible for creating their own integration with each required system. This in itself presents several problems in terms of availability and maintenance.
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What does this mean for the hotel? Simply put, legacy PMS (or no PMS at all) cannot be integrated with third-party software. Closed APIs will also present problems as you will need to contact the PMS provider to create your own API connection, after which you will need to make adjustments once your PMS is updated.
Integration out of the box. Software and BI vendors are specifically addressing the integration problem by developing pre-defined integrations with popular PMSs that have either closed or open APIs.
So now we can discuss some of the leading business intelligence providers who are developing BI software specifically for the hotel industry. The following section will suggest some of the products available on the market and their specific features.
The business intelligence market can be segmented by general purpose tools and hotel analytics providers. For
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