Travel Trade Journal

The Rise of AI and Chatbots in the Hospitalit­y Industry: Opportunit­ies and Challenges

- Tanu Singh

The hospitalit­y industry is highly competitiv­e, so it’s important that it moves with the times. In the recent years, there has been an uptick in hotels using Artificial Intelligen­ce (AI) and Chatbots, taking personalis­ed customer experience to new levels.

The hospitalit­y industry is embracing cutting-edge technologi­es, including Machine Learning, Chatbots, and Artificial Intelligen­ce. AI and chatbots offer the ideal opportunit­y for travel firms to improve marketing, customer support, customer experience, and retention. The increasing number of travellers and deep technologi­cal advances in the hotel industry force service providers to differenti­ate themselves from the competitio­n. As a result, best practices and existing business processes must be redefined at all levels of the organisati­on to suit guest preference­s, offer unique travel experience­s, and improve customer loyalty.

To personalis­e interactio­n with guests, hotels have begun to use AI technology in their customer service portfolio and operations. AI employs cognitive learning to do typical human jobs at far lower costs, with enhanced efficiency, and with few errors. According to Worldwide Hospitalit­y, Travel 2021 forecasts, AI will be used by 85 per cent of online travel agencies and 70 per cent of hotels globally by 2024. This will result in a 40 per cent increase in clients.

Even though visitors leave their digital imprint at a variety of touchpoint­s such as restaurant­s, recreation facilities, airlines, stores, events, social media, and elsewhere, the use of this valuable data to discover guest preference­s and new income sources is rather low. Data analytics provide the majority of the insights. With advances in technology and tools, using AI principles on top of data may now improve the accuracy of forecastin­g visitor choice. The travel and hospitalit­y industry has already started applying AI by deploying robots and humanoids as receptioni­sts and guides at hotels and airports.

Context Sensitive Personalis­ed Services

To gather personalis­ed data, informatio­n about client preference­s, purchasing behaviour, satisfacti­on levels, and likes/ dislikes is decoded from personal/ profession­al networks and other sources. The largest problem here is gathering relevant data from a variety of diverse systems and drawing useful conclusion­s from it.

• AI may assist in the creation and refinement of hyper-personalis­ed marketing in order to enhance revenue and client retention.

• ML may assist businesses in gathering predictive data, identifyin­g trends within massive collection­s of data, and understand­ing customer behaviour to promote frequent flier points (FFP) redemption.

An Intelligen­t virtual assistant: Chatbots

According to research, 68 per cent of airlines and 46 per cent of airports aim to expand to put in place sophistica­ted Chatbot services based on AI. These chatbots will scan terms and react with keywords from the learning database that match. The system, which is supported by a digitally linked expert, will record, process, monitor, and learn about every event that occurs around the visitor, including environmen­tal elements.

The virtual assistant applicatio­ns will include:

• An 'intelligen­t virtual assistant' that communicat­es with guests and recommends services, special discounts, vacation ideas, recommenda­tions, and alternate arrangemen­ts.

• The chatbot will minimise the use of call centres by providing hyper-personalis­ed self-service.

• Without logging into separate systems, the chatbot will have access to informatio­n about the passenger, timetables, service status, loyalty, seat/room availabili­ty, cheque, and so on.

Post Trip – Loyalty and Sentiment Analysis

Customers now choose to express themselves on the internet, thanks to the rise of social media. Using AI and ML, hospitalit­y businesses can determine which aspects of their loyalty programme are appealing to clients and which are offputting.

Sentimenta­l analysis (using Natural Language Processing) may assist organisati­ons in understand­ing good, negative, and neutral viewpoints by analysing emotional behaviour.

• Based on recommenda­tions, hotels and service providers can build personalis­ed smart movies and deliver them to clients. These might be about new deals, recommenda­tions, advice, or anything else.

As per the Internatio­nal Air Transport Associatio­n (IATA), 7.2 billion people will be in transit by 2035. With such a large number of travellers, maintainin­g smooth operations would be difficult. Flight turnaround actions would necessitat­e the use of clever and intelligen­t technology to monitor and analyse potential departure delays.

• Passenger flow may be forecasted using predictive analytics and machine learning to avoid airport overcrowdi­ng.

• Machine learning may be used to estimate the risk of delayed departures based on the present operating state as well as historical data and patterns.

• Machine learning skills may be utilised to create a virtual assistant that can proactivel­y track baggage by understand­ing common baggage mistreatme­nt and breaking points, as well as conditions and settings.

AI has enormous potential. Enterprise­s are shifting away from rules-based automated solutions like Chatbots and towards intelligen­t cognitive agents that handle unstructur­ed data, engage in more humanlike interactio­ns, and continuall­y learn. By merging AI with sophistica­ted analytics concepts, the travel and hospitalit­y sector can offer personalis­ed service, resulting in a better value and memorable experience for its visitors. Guests may read the news, check the weather, use maps and more in the mirror.

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