Top 12 Use Cases of RPA in Hotels & Hospitality Industry in 2024
In 2022, a survey done by Duetto revealed that ~78%1 of hoteliers were expected to increase their hotel tech investment in the next 3 years.
RPA in hospitality industry can support such digital transformation initiatives.
According to industry reports2 , hotels won’t return to pre-COVID financial levels before 2023, if not later. RPA’s capability to automate front office and back office tasks can help the hotel industry navigate such disruptions.
In this article, we will discuss:
- What RPA in hospitality industry is
- 12 use cases of RPA in hospitality industry
What is RPA in hospitality industry?
We define RPA in hospitality industry as leveraging RPA bots to automate front-office and back-office processes of hotels.
Having bots take care of tending to repetitive and manual tasks allows human representatives and the management team to focus on more important tasks that need personalized attention.
We will now go over the top 7 (mostly rules-based) use cases of RPA in hospitality industry.
Many hotels use hospitality software that helps them manage their operations in an end-to-end manner. However, in cases where the hospitality service provider lacks such a solution, they can use RPA bots to automate their operations.
1. Responding to room availability enquiries
RPA-enabled chatbots can answer guests’ questions about room availability and rooms’ features. Instead of the user manually navigating through a website to find this information, the chatbot can transform the experience into a conversational-based one.
It can do that by:
- Asking a series of standard, rules-based questions,
- Getting the answers,
- Searching through the knowledge base for a response (or generating a new one in case of the existence of ML technology),
- And giving the information to the guest.
The benefit of chatbots is that they make room reservation a smoother, 24/7 experience– especially given that the ticket sales office usually aren’t open past the operating hours.
2. Managing reservations
While we weren’t able to find any recent stat on this phenomenon, in 2018, 82%3 of all 148M online reservations (~121M) were done without any human intervention at the other end. The number must have risen since then.
RPA bots can be used to automate room reservations fully (Figure 1):
- They can leverage APIs to show the real-time availability of the rooms by exchanging data between the website and the hotel’s database.
- They can also automatically create guest profiles by extracting their data online and putting in on the CRM.
- They can reconcile the online payment by comparing invoice details with the new guest’s reservation slip.
- Lastly, once the guest’s information has been received and the payment confirmed, the room can automatically be reserved and taken out of circulation.
3. Automated check-ins and check-outs
Some hotels have a check out time of 12PM, some have 12:30, and some have 13PM. If these aren’t communicated clearly with the guests, overstaying past some time (say 15 minutes) could result in additional charges that the guests did not want to have.
From an administrative perspective, too, check-in and check-out times’ miscommunication could affect the preparation of the room for the next guests.
RPA bots can track the check-in and check-out times of each hotel guest. When the checkout time is approaching, the bot can send a push-notification through the hotel’s app, an SMS message, a WhatsApp message, or an email on predetermined intervals to keep reminding the guest of their check out time.
Implemented at scale, such a use case can reduce the workload of the reception desk at large hotels. It also reduces the stress of the travelers who would now not be likely to forget their check out date.
In addition, the messages sent to guests could also include the option to extend your stay with one click to make that experience more seamless as well.
Hotel CRM applications may have missing data fields about customers (e.g. their address, preferences, special requests, previous stays, loyalty program related information, engagement with previous offers etc.) which can be completed with 3rd party services like travel APIs, RPA bots or other data integration solutions. This would bring all guests’ information into a single location facilitating sales, marketing and customer success activities.
Learn more about RPA use cases in marketing.
Dynamic pricing can allow hotels to price their rooms with respect to:
- Days of the week
- Special events and/or festivals
- Competitors’ prices
Especially when it comes to competitors’ prices, RPA bots can be programmed to scrape prices off of competitors’ websites. They would navigate to a competitor hotel’s website, specify the kind of room, look for the price, extract it and store it.
This series of steps were performed by human pricing experts in the past. But thanks to screen recording, unattended RPA bots can replicate such steps at regular intervals quicker and more efficiently. Moreover, they then can adjust the hotel’s room prices on the website automatically with respect to rules-based factors.
Learn more about competitor monitoring automation.
6. Customer Service
81% of travelers4 always or frequently read online reviews before booking a room. However, on TripAdvisor, for instance, in 2020, there were 1M fraudulent reviews (3.6% of the total number of submitted reviews)5 .
So it’s important to both read customer complaints, but also take actions against malicious spammers.
Some customer complaints might fall through the cracks and never be seen. Speaking from experience, I once worked at a hotel that had received a legitimate complaint about a serious issue with a detailed explanation including photo evidence. However, the management hadn’t actually seen it until the review had found its way to the first page of reviews and was scaring potential guests away.
RPA bots can be programmed to extract all the submitted reviews, store and deliver them to responsibles. Moreover, by leveraging OCR and NLP capabilities, they can also “rank” the reviews in terms of:
- Importance – by identifying certain sensitive keywords from the reviews, such as “fire,” “bedbugs,” “overcharge” or such similar words.
- Legitimacy – by cross checking the complainer’s name with the list of guests in previous time to establish that such a person has indeed stayed at the hotel, looking for submitted images, and so forth
- Sentiment – is the complaint mostly positive, requiring an automated reply for acknowledgement? Or is it critical and should be assessed by a human rep? Sentiment analysis capabilities assist in that regard.
This use case is an extension of Intelligent Document Processing (IDP).
RPA in hospitality industry can automate general financial processes that are same across most industries. We won’t go into details, as we have explained RPA use cases in finance before. But the general use cases are:
- Revenue reconciliation
- Payment approval
- Report preparation
- Applying automated discounts to high-frequent guests’ bills
- Automatically adding room service costs to each guest’s bills as they happen in real-time
- Typical finance use cases such as accounts payable, receivable etc.
For more RPA use cases
To learn more about RPA use cases across different industries, read:
To get a more comprehensive look into RPA, download our whitepaper:
And if you want to leverage an RPA solution, head over to our data-driven RPA software list.
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Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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