How the Hospitality Sector Uses Data Science and AI to Improve Performance

How the Hospitality Sector Uses Data Science and AI to Improve Performance The days of bragging about having a smartphone or personal computer that was online are long gone. Digital technology is becoming more widely available, impacting how people work, unwind, and organize their holidays. Hoteliers must keep up with innovation if they want to meet rising guest expectations. Imagine having to pick between two hotels that are offering rooms at the same cost. The former offers a chatbot that instantly responds to your questions and faces recognition check-in, whilst the latter merely offers comfy rooms. Which lodging would you reserve? The solution is clear.

The qualities stated above are supported by AI and data science. I spoke with data scientists, start-ups, and hotel reps to learn how hotels use AI and data science to assess their performance and offer a unique guest experience.

1. Revenue management The use of data and analytics in revenue management (RM) optimizes product pricing and availability for optimum revenue. In other words, a revenue management specialist looks for ways to sell the appropriate product (in this case, a room) through the right distribution channel at a fair price to a clientele that is prepared to make a purchase.

To determine how successful a property is compared to others in the same price range and type in a specific location, specialists track various data. Average daily rate (ADR), revenue per available room (RevPAR), average occupancy rate, gross operating profit (GOP), and gross operating profit per available room are just a few of the several critical performance metrics that are used to evaluate performance (GOPPAR).

Revenue managers may estimate client behavior and room demand by calculating and analyzing these performance metrics data. This allows them to adjust room rates accordingly. Dynamic pricing is the term for this strategy.

2. Dynamic pricing automation Due to data science, hotels can more correctly forecast demand and client behavior patterns. Because of this, major hotel chains like Marriott International and AccorHotels employ data scientists and analysts. These experts use information about hotels and their rivals to build and implement pricing strategies.

To manage their revenue, some hotels rely on RM solutions. Utilizing machine learning, such software determines the ideal room rate in real-time. These RM systems automatically

combine and analyze vast amounts of internal and external data from numerous sources to find patterns and abnormalities. ●

Rate Insight: gives managers the ability to estimate local room demand using real-time data on past, present, and future competitor rates to determine fair hotel rates. The portal offers data on property ranking and rating performance to professionals. There is also event analytics accessible.

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Party Insight: To find parity concerns, Parity Insight checks prices on popular OTAs and metasearch engines with those on a hotel chain's website. For instance, hotels that offer consistent pricing can lessen their reliance on the online travel agency and prevent guest confusion.

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Revenue Insight: Users of Revenue Insight can get "smarter hotel analytics" that blend past and future performance. The platform compiles data on hotel KPIs, making it simple and quick to compare performance from year to year.

3. Operational analytics : Since the hospitality industry doesn't understand what a day off or holiday is, hotel software systems operate nonstop, producing various forms of visitor and operational data. A property management system records this information, regardless of whether a guest buys a room or orders a Caesar salad in a restaurant, a maid reports a shortage of cleaning supplies, or an event planner books a conference room.

Through operational analytics, hoteliers may monitor internal operations in real-time to identify errors and seek out methods to get better. Businesses can analyze their competitors, predict client behavior for each season, track brand mentions and reputation on social media by looking at user comments, or figure out why website visitors start bookings but don't finish them (churn analysis). Applications for data science vary depending on IT setup and personnel expertise. For detailed information on churn analysis, refer to the data science course.

4. Performance evaluation Hotels can gather operational data from several departments using data visualization tools to track, assess, and enhance performance. The corporate representative reveals how a Texas hotel chain uses iDashboards to increase organizational transparency. The staff members' daily job performance and the bottom line were not in sync since they were using outdated data and reports. They employ the programme in their sales division to keep track of rooms, occasions, and recommendations. The hotel can now link a dollar amount of revenue to the referral programme. Employees can also "own" the dashboards by demonstrating how their particular jobs affect the company.

5. Brand Monitoring It might only take a few minutes for someone to write and post a hotel stay review for other travelers to read. Brands need to analyze and respond to negative remarks as soon as possible because they tend to stick in consumers' thoughts more. Businesses may find it easier to keep up with the rate at which customers are exchanging information about their services by using AI and NLP technologies for customer experience data analysis.

Hope this article was informative enough. If you have any desire to learn more about data science and its techniques, check out the data science course in Mumbai. Learn the in-demand skills and become an expert data scientist.