How Hotels Use Machine Learning and AI Solutions to Boost Hotel Revenues
Just like any multibillion-dollar industry, the hotel industry is dependent on technology for its day-to-day operations. It is an industry that caters to the wants of the customers more than their needs. Hence, competing hotels employ methods and machines to ensure there’s a constant influx of innovative technology to streamline the processes and increase profitability. One of such compelling technologies is Machine Learning.
Machine learning is a subset of Artificial Intelligence (AI), and it uses data to build models that can predict the result with high accuracy. The real power of Machine Learning comes from the fact that it can predict future events even when certain datasets are absent.
5 Ways Machine Learning Can Help Boost Hotel Revenue
Demand Forecasting
Machine Learning uses Big Data to create models based on hotel history, seasonality, local events, external real-time events, and your own promotions for demand forecasting. It can help in dynamic pricing in hotels by keeping the forecast up to date while taking into account any new factors that have just occurred. This allows you to optimize room offerings and prices to suit the changing demand in the market, thus maximizing profit while maintaining a competitive rate.
Market Segmentation
AI and Machine Learning use huge chunks of data to segregate the hotel market into 3 major segments. This is a crucial step because such types of segmentation allow you to revisit and revise your revenue generation strategy for optimal bookings. The 3 major categories are: –
- Channel Segmentation: This type of segmentation allows you to identify which OTA channel performs the best. You can then optimize your channel management strategy to enhance the sales from that particular OTA and reduce costs that do not give significant ROI.
- Demand Segmentation: This segment is focused on demand. If the demand is high, the room rates are adjusted accordingly. If the demand is low, discounts and promotional offers are rolled out to attract bookings.
- Guest Segmentation: This segment is focused on segregating the guests into categories such as family, solo travelers, business travelers, etc. This enables you to hyper-target them individually with exciting offers and deals, leading to more bookings.
Reviews and Reputation Management
Machine Learning uses Big Data to make your customers’ stay at your hotel better than ever. Additionally, with automated check-ins, you can offer your guests the best customer experience ever at various touchpoints in the customer journey. This ensures that your hotel gets the best reviews, boosting your brand for increased bookings and increased profitability.
Revenue Management
In order to maximize revenue and bookings, revenue managers need to determine the best room rate at a given time. Until recently, this task was done manually by revenue managers – collecting, reviewing, analyzing numerous data sets to calculate the optimal room rate at a given time. In addition to that, they also focus on the yield management of the hotel especially in making pricing decisions. This was a tedious and time-consuming task until Machine Learning took over. Revenue Management Systems (RMS) collects and computes large amounts of complex data automatically and runs it through models to come up with the best possible room rate in real-time.
Knowing Your Customer
The more personally you know your customer, the better you are equipped to exceed their expectations. AI and Machine Learning use Big Data to gather vital information about the customers and create personalized offers based on their preferences. This helps you serve your customers better and create excellent customer experiences.
Author Bio:
Karan Iyer is an end-to-end digital marketer and blogger who inherently understands the hotel industry with his hospitality background. Karan knows how to convert the pain points and challenges of the hotel industry into business opportunities, and that’s what he writes about for his readers. He also shares industry trends, insights and news to help his readers stay up-to-date.
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