Revenue Management Between AI and Traditional Technology, never lost the Hotel Data in Between.

The adoption of ever-sophisticated integrated revenue management software and technology, particularly with regard to forecasting demand and pricing, is crucial and initial to enabling future demand by using hotel data analysis, which can provide a unique competitive advantage for hotels where they need a kind of technology that involves a daily cycle of diagnostic, predictive, and prescriptive analytics to maximize profit.

The volume of data, as well as where and how to even start analyzing and using it, frightened hotels for a very long time, which led to more than simply underutilization. Effective data utilization can give hoteliers the chance to enhance customer experiences, increase revenue, and set the right strategy.

In general, hotels gather information from internal and external sources. If we start with the internal sources, which, for simplicity’s sake, let us call small data, this “small data is the most familiar to hoteliers and often the most valuable and can be easily managed, such as occupancy data, RevPAR, market penetration index, Average Rate Index, room revenue, etc. Where the majority of the small data comes through hotel operations, it generates a vast amount of data literally every second, such as when a guest makes an online booking. That’s new data. When the guest steps into the hotel and makes a check-in, that’s new data. When a housekeeper marks a guest room as clean, that’s new data. Everything that happened within the guest cycle in the hotel, starting from making the booking till the check-out (you name it), is new data.

With the guest cycle (pre-arrival, arrival, occupancy, and departure), hotels collect guest data with the guest’s permission, but how many truly use it effectively? The valuable facts and figures of guest data appear non-stop, but how do hotels take advantage of them? If the data is not properly administered and most information is either lost or unused, the hotel will lose revenue.

These interactions by our customers leave many types of digital data traces that indicate their locations, spending habits, preferences, and satisfaction levels. These data include search engine queries, website traffic, transaction records, social media posts, and geographic locations.” In addition to all of the above factors, for many businesses in the hospitality industry, something as simple as the weather can impact travel demand. The best practice today is to use Big Data sources to predict the weather as accurately as possible and then use the weather forecast as yet another input into the forecasting model. Accomplishing all of this requires significant effort and assembling a talented team of Big Data engineers.

Big Data Era

Big Data” is the term used to depict the large volume of structured and unstructured data that a hotel operation team collects every day while interacting with the hotel guest, although “Big Data” is a comparatively new concept in the hospitality industry, but There is still a lot of uncertainty as to what Big Data is and how it helps hoteliers get more bookings and revenue; to make it easy Big Data is, quite simply, a huge amount of data – including internal and external data.

The big data is the result of the tremendous growth of social media, Mobile apps, Mobile web and consumer-generated content on the Internet has inspired hoteliers of the so-called big data analytics to understand and solve hotel operation obstacles. However, the overall goal is how to use this data starting by analyzing this big data, hence hotels can gain insights that lead to better business decisions, beat competitors, learn about their customers in-depth, and enhance accurate forecast, in turn, hotels can plan and strategies towards the ultimate desire: increased the hotel revenue and profit.

Big Data and Revenue Management

The evolution of revenue management analysis techniques has always revolved around selling the right product to the right consumer at the right time, at the right price, and through the right channel. What was missing from this formula was big data, which was necessary to complete and perfect modern revenue management.

A few years back, maximizing room inventory and setting room rates were the main tasks of revenue management. The primary responsibility of the revenue manager was to do basic data analysis, identify patterns, and make choices about pricing and inventory control, but due to the advancement of technology over the past decade, the scope of RM has grown as traditional hotel revenue management practices have become significantly more sophisticated while also presenting new methods to increase hotel revenue. A revenue management system (RMS) enables hotels to collect all the data needed to make informed strategic decisions that generate maximum revenue for the hotel. The right system enables revenue managers to track performance data in real time and create realistic and accurate forecasts so that hotels can anticipate demand and make the necessary adjustments to their pricing strategy to maximize the revenue that they are generating.
RMS, Big data, and data analytics have made significant progress in the past decade and affect hotel revenue management in many ways by improving business operations, performance evaluation, risk assessment, and managerial strategic plans. However, and within the hospitality industry either in hotels or resorts   we witness an emerging movement in Big Data and data analytics applications.

Big Data either internal or external data and  data analysis , It all its analysis and RMS cannot, therefore, be the only toolkit for a revenue manager, because customer data reside in different hotel systems, we are looking here for an RMS that can integrate first with the property management system (PMS) to take into account the entire booking information, analytics, and reporting functions, as well as integrate with other internal systems such as the central reservation system (CRS), point of sale (POS), the customer relationship management (CRM) system, competitive rate shopping software, channel management tools, the hotel’s website, and various social media channels, moreover, an RMS can integrate with hotel performance metrics and trends, as well as market and comp set supply and demand analysis, market segmentation, and supply pipeline data.

All of these external systems, tools, and resources can provide valuable data analytics that help provide some visibility into a hotel’s position or market performance relative to the competition. hotel competition or even the entire market. Thus, combining data from various systems and sources is an important issue for hotel revenue management strategies because RMS cannot exist as a standalone application. However, the different systems used by hotels do not always share all the transactional data because hotels typically acquire different systems at different times from different suppliers.

For example, the properties that have meaningfully increased their direct booking rates, overall loyalty, and guest satisfaction have done so by fully committing to a data-driven approach that forges memorable moments across every interaction point along each guest’s journey.

Big Data Customization with AI

The hospitality industry has long been seen as a laggard in adopting modern technology. Whether right or wrong, this perception is widespread and may be poised to grow as we see incredible innovation happening in other verticals, especially with the most recent excitement in the field of AI. Considering the innovation of ChatGPT and it’s impact on hospitality industry , Google Bard, and Amazon’s Go self-service stores, they are all revolutionary large language models that have exploded in attention over the past few months, and all of them are centered on collecting, normalizing, labeling, and modeling incredibly large sets of data—a function known as “data wrangling.”.

It means that AI and big data can unlock opportunities for hotels to boost their direct revenue and operational efficiency while offering instant and personalized guest experiences. Data is everywhere, and for hotels that know how to collect and store it correctly, it can be a major success factor in increasing hotel profit. Hoteliers who understand how to leverage AI tools to become more efficient and effective will become more valuable than ever. Those who don’t educate themselves may find themselves in a more challenging situation.

Big Data Analytics can help hotels correctly predict not only demand and set the correct pricing strategy, but also whether high-rolling guests spending thousands of dollars on expensive food and drinks are merely celebrating a special occasion or if this is the clients’ usual behavior while traveling. This sort of information is crucial in efforts to determine a customer’s lifetime value.

A deep understanding of customer needs through the collection of the right information also enables hoteliers to stay relevant through their ability to offer personalized services to every guest, thus increasing their likelihood to return and increasing guest satisfaction.

When it comes to ensuring that each room is sold at the highest price possible, revenue management is used to focus primarily on setting room prices and optimizing room inventory. Today, Revenue Management strategy goes beyond those aspects, and revenue managers should look for new ways to optimize revenue growth and profitability through dynamic pricing and data integration. Hotels can make the best pricing decisions and maximize profit by combining the power of automation and AI with traditional revenue management talents.

AI-powered revenue management technology acts as the ultimate co-pilot for any revenue manager, so why should any hotel attempt to navigate the future without such a profitable advantage? Unfortunately, many hotel owners tend to confuse personalization with simply selling upgrades or improving their bulk email marketing. Hoteliers need to understand the benefits of true personalization and invest in the necessary tools and technologies to leverage customer data.

How AI Can Assist Revenue Management Data

A recent report from Accenture Co. estimated that AI could potentially double annual economic growth rates by 2035. This has been validated by another study by PwC, which estimates that AI could add $15.7 trillion to the global economy by 2030. Needless to say, AI is already having a massive impact on our society, and every industry should take note.

Artificial intelligence (AI) can significantly enhance hotel revenue management strategies by using predictive modeling to analyze historical data and predict future demand and revenue, optimizing pricing and availability to maximize revenue. AI can also assist in setting corrective dynamic pricing and increasing hotel occupancy levels based on demand analysis. AI can also optimize inventory management by forecasting demand and adjusting room availability accordingly, resulting in increased revenue by selling more rooms at higher prices during peak periods and reducing unsold inventory during off-peak periods. Additionally, AI can personalize pricing and offers to individual guests based on their preferences, past behavior, and demographics, allowing hotels to increase revenue by targeting the right guests with the right offers at the right time. Furthermore, AI can identify opportunities for upselling and cross-selling to guests and optimize pricing and inventory decisions in real-time based on market conditions, guest behavior, and other factors. AI can help hotels identify patterns and anomalies in revenue data that can reveal new revenue opportunities and trends.

Conclusion

The Internet of Things (IoT) and artificial intelligence (AI) are two examples of intelligent devices and systems that can be used in conjunction with big data, Its job is to gather and deliver the facts and knowledge required to create the correct revenue management strategy; hence, automation of repetitive revenue management tasks will be made possible by AI. Analyzing demand trends, consumer behavior patterns, and market segments is part of this process. It also incorporates automated methods for improving the booking process as well as forecasting, reputation management, and pricing automation. You can quickly gather, analyze, and manage massive volumes of data from several sources that will help you comprehend every facet of your hotel’s target market by using the correct tools.

Finally, we predict that AI will assist in evolving data integration and speed the process of identifying ways to bring data from disparate sources together in a unified way to produce meaningful insights.

“Reprinted from the Hotel Business Review with permission from www.HotelExecutive.com”