Role of Artificial Intelligence in Hotel Revenue Management

Every consumer nowadays demands the best price for the sought product or service. The traditional hotel revenue management systems carried out the mathematical evaluation of guest engagement across multiple prices and different channels.  

However, they often lacked data analytics based on non-historical and external factors. These systems showed linear results based on historical data but failed to factor in current market dynamics and guest preferences.

However, contemporary consumers/guests use the internet to quickly compare different prices, services, and amenities. They choose personalization over general treatment as well as go for the best price available.

With ever-evolving tastes, preferences, and market conditions, data analytics could bear the sweetest fruits. Due to this reason, hotels must leverage guest as well as market data to set prices as a contemporary business is all about data.

Prices allow a hotel brand to position itself in the marketplace. Therefore, they could be set factoring in multiple aspects of the hospitality business. This is exactly where AI helps in hotel revenue management.

An AI-powered revenue management system allows hotels to gather insights and projections into guest behaviour, market conditions, and trends, as well as demand patterns. This data streamlines the pricing process and ensures smooth as well as lucrative hotel revenue management.

AI in revenue management is capable of analyzing multiple data sources. This is done to ensure the accuracy of the suggestions as well as predictions, from historical data to real-time data, ML algorithms, demand modelling, various statistical models, etc.   

From different sales patterns and guest footfall to external factors including weather, current events, and public holidays, AI in hotel revenue management considers it all. This data aggregation scope, however, is not possible for hotels still relying on legacy pricing strategies and systems.  

Let’s move on to the top benefits of AI-based Hotel Revenue Management in our next section.

Top 5 Benefits of AI-based Hotel Revenue Management

According to an ET Hospitality World article, the implementation of AI technologies can reduce labour costs in the hotel industry by 10-12%. Not just costs, it helps a hotel elevate guest experience as well as manage revenue in a better way. 

AI in revenue management has been helping hotels offer more personalized prices and packages to guests and optimize their revenue. Thus, there are multiple benefits of an AI-powered hotel revenue management system for dynamic and profitable pricing.   

Some of these benefits of AI in revenue management are:   

1. Gathers data and identifies patterns and trends

AI in hotel revenue management helps hotels gather the right set of data that impacts guests’ spending decisions and hotel revenue strategies. ML algorithms ensure that the data picked up is appropriate as per the human instructions or default settings.

With the right set of data, a hotel is then able to identify guest patterns and market trends. These patterns are based on the changing guest tastes and preferences. However, with such a huge pool of data, it might seem an uphill task to identify patterns.

But it’s not! More often than not, AI-powered revenue management systems are designed to engage with massive amounts of data, translate the relevant amount, and identify guest behaviour and market trends from it.

AI in hotel revenue management can thus process humungous amounts of data in a fraction of time and ML can help compile the relevant data to provide insights as well as predictions relating to revenue strategies.

2. Creation of guest personas

With the help of AI and automation, hotels can create detailed guest personas in their systems, which will help them offer pricing deals and packages to these guests and enhance revenue management.   

The data for these personas, if complied manually or using traditional systems, might not be accurate and might not help hotels optimize their revenue management strategies.   

Moreover, AI in revenue management also helps with the propensity model. This model is a scorecard used to predict guest behaviour or prospect base. With predictive analysis and ML, hoteliers can forecast how guests’ past behaviour and current preferences will create future demand. This helps them to effectively channel cash flows, optimizing revenue strategies.   

With predictive analytics and machine learning, revenue managers can predict how customers’ preferences and past behaviour will lead to future purchases. As a result, they can optimize the revenue channels of a hotel precisely.

3. Identification and elimination of unprofitable guest discounts and segments no longer profitable

Sometimes hotels offer deals, discounts, and other promotional offers that are unproductive or not very well received in the marketplace or ones that are simply not very well-thought-out or analyzed. These efforts then prove to be futile or fruitless.

However, with AI in revenue management, hotels can tell the promotional campaigns that are proving to be productive and profitable apart from the ones that are not bringing any results. Additionally, with AI-enabled data analytics, hotels can identify the top and worst-performing hotel segments or guest services and allocate financial resources accordingly.

4. Helps set the best prices

Pricing in a hotel is one of the key drivers of the business. In the highly competitive hospitality industry, if a hotel fails to adjust its prices with the rising and falling demand, it might face huge losses or just perish eventually.

Thus, to stay relevant and attract guests, a hotel should be able to practice dynamic pricing, to make up for the low periods and gain during the high ones. Prices must be adjusted to the market demand to optimize revenue management. This is possible through AI-gathered data and ML-generated data analytics reports that predict the current and future demand along with guest preferences and market trends.

With time, these ML algorithms become better at engaging with data and predicting trends and demand.

5. Monitoring and identification of potential revenue risks 

With AI in hotel revenue management, hotels can monitor every revenue channel constantly and set alerts for potential risks. This makes the entire revenue management system more effective and secure.

The settings of AI-powered revenue management systems generally ask for metric and condition setting for risks, that define the tolerance level of a business to certain risks. If the conditions match the specific risk situation, the system alerts the business, creating a more aware state of revenue management and much fewer losses.

Conclusion

As artificial intelligence (AI) technology matures, its usage across multiple industries will further increase.

The Hospitality industry, in particular, depends majorly on guests for business. AI is great with guests/customers. It interacts with them, gathers the related data, and then compiles it to give insightful reports. And thus AI is gradually penetrating every segment of hotels.

AI in hotel revenue management systems is allowing hoteliers to optimize the revenue segment and attract more and more guests through the right pricing strategies. It further helps them to identify what’s working and eliminate what’s not, thereby saving resources and reallocating them to better use.

Therefore, the integration of AI with revenue management for the hospitality industry is a boon for hotels.

Confused about which AI-powered revenue management to choose for your hotel?

We have got you covered! 

BOTSHOT RevMaxi is a powerful revenue management tool that leverages AI algorithms to study and evaluate market conditions, demand, and competitor rates and set room rates accordingly, in real time. 

Sounds like your next hotel technology software? Visit - BOTSHOT RevMaxi to read more about this revolutionary product.