The hotel industry is behind the curve when it comes to AI and machine learning. Just compare it to the online entertainment industry where platforms like Amazon, Netflix and YouTube use data from customer behaviour to provide a powerfully tailored experience.
But the case for embracing AI is huge. A recent study showed that AI is expected to reduce hotel costs by 13% while raising revenues by 10%, in an industry where an estimated 73% of activities could be automated.
Let’s look at some of the ways AI can begin to raise the performance of the hospitality ecosystem:
AI in distribution
Hotel distribution is a complex task of choosing the correct distribution channels to sell rooms at the right times and prices to maximise profitability. Doing it successfully depends on having lots of data and being able to analyse it quickly and efficiently that provide meaningful insights. As such it is the perfect match for machine learning. Companies like Booking.com and Hopper are already using this technology to improve distribution, but it needs more uptake across the industry as a whole, especially if travel companies want to compete and remain agile to market conditions.
AI in booking
AI can also improve the customer booking experience, tailoring booking platforms to individual users based on their behaviours and supplied data. Avvio’s Allora is an example of a direct booking platform powered by AI, which guarantees a 25% increase in direct revenue. And Expedia is using machine learning to match the best properties to the best partners, matching travellers’ needs and making predictive recommendations based on customer searches. According to Expedia this has led to typical conversion improvements of 8%.
AI in revenue management
Then there’s revenue management. This again involves the analysis of huge quantities of data to make complex pricing decisions based on numerous factors including demand, time, room rate and availability. As such it is another perfect fit for machine learning. There’s already a number of players out there using AI at the core of their revenue management systems and platforms including Duetto, Pace and OTA Insight.
AI in marketing
Marketing can also be improved with the help of AI. With most travellers starting their travel research on Google, pay-per-click advertising is still hugely important. Machine learning can optimise pay-per-click marketing by targeting the right audience at the right time and making the best bidding decisions based on exposure and volume levels. This needs to leverage essential data as part of the traveller buying journey from the first moment the consumer interacts with the travel brand — therefore you need to harvest and make this data work.
AI and customer service
And this is just the beginning. There are various other fields where AI will reap rewards including fraud detection and customer review sentiment analysis. Not to mention chat bots. Many companies are working on AI customer service assistants to deal with simple enquiries, some of which are scarily indistinguishable from the real thing, a perfect attribute to guest experience at hotels which are being attributed to Concierge services through mobile apps and within omnichannel messaging systems — an area of tech that is exploding in the travel technology market.
Furthermore, these are a natural element to people’s lives as some form of bot in their own home, whether it’s called Alexa, Siri or whatever. It’s not too distant a prospect to imagine one of these virtual assistants automating the booking process by scanning travel sites, comparing prices and even carrying out the booking process itself, just by the simple command “book my holiday between these dates”.
On the AI path
The hotel industry may be behind the curve but the way forward is clear and relatively straightforward. It’s about having big data and quality data and matching that with algorithms that can analyse it effectively. It also requires the right kind of IT personnel who understand the paradigm shift to AI and its benefits. Most of all it requires a shift in mindset across the sector while utilising the existing technology platforms.
Hotels need to start thinking of themselves, not just as places to stay, but as tech companies where to move forward technology needs to be at its heart.
Sciant’s experience implementing AI and machine learning deep within travel and hospitality tech platforms is enabling parts of the market to develop new processes while adapting system delivery to enable hotels to optimise revenue event further. We see huge scope in implementing AI in just parts of the business without having to do a blanket wide approach, and seeing the impact AI can have in pilot projects will give confidence in its application across the business.
AI and machine learning is certainly on its way to being very present in hotel customer service delivery and experience and in optimising and automating operational functions, allowing hoteliers to free themselves of repetitive time-consuming processes to focus on more strategic and creative tasks that will deliver innovation to the hotel sector.