Why slow AI adoption is posing a threat to hotels

Why slow AI adoption is posing a threat to hotels

Personalisation today is a must, not longer a maybe. Research from BCG suggests that brands which create personalised experiences by integrating advanced digital technologies and proprietary data for customers are seeing revenues increase by 6% to 10% - two to three times faster than those that don’t.

The need for personalisation has infiltrated a wide variety of industries. Why do you think you can personalise your Coke with your own name, or get the perfect song recommended on Spotify? The effects of personalisation pay off.

The travel industry has slowly started to go in the same direction. Technologies such as Machine Learning (ML) and Artificial Intelligence (AI) are opening a whole world of possibilities for hotels to embrace technologies that store and retrieve previous booking and stay information to make the next stay a better one.

But even though a hotel is in a perfect position for gathering data about guests’ past preferences and behaviours, the travel industry is still the slowest one at adopting AI for personalisation purposes. This should come as a surprise to anyone everyone - isn't a hotel supposed to be their customer's second home? The chances to interact with and learn from the guests are endless.

If you are using tools to communicate with guests, you most probably have already gathered rich and useful information about your guests’ habits and preferences. It now lies in your hands to use the available technology and start doing personalisation right in one of the industries that need it most.


The paradox of choice and personalisation

There is no doubt that as consumers today we are drowning in choices because of social media and technology being constantly at our fingertips. This often means that we can easily jump from option to option in a matter of seconds if the information in a website or marketplace is not attractive, does not seem appealing enough or simply does not fulfil our needs.

The way in which the amount of choices harms our decision making process and even our well-being has been given a name by psychologist Barry Schwartz, who identifies the phenomenon as the Paradox of Choice. You can view a TedTalk in which Schwartz describes the phenomenon here.

Brands are starting to take this phenomenon seriously. If they want their customers to listen up, they have to adapt to the way in which people today consume information and offerings. In the online retail business for example, those that fail to provide personalised shopping experiences by recommending products and content depending on where the consumer sits within the lifecycle, will most probably lose the customer along the way.

Essentially, ‘one size fits all’ has seized to work. Personalisation is the best way to increase the relevancy of messages. We will look at two companies that take this very seriously.


How are the best making use of personalisation?

Even before Netflix made the jump from mailing DVDs to streaming movies and series online, the company was collecting data and using it to engage with customers about their viewing preferences. They were certainly one of the pioneers using machine learning recommendation engines in order to shape the visitor’s experience by offering relevant shows based on past preferences. By providing better search results, Netflix estimates that it is avoiding cancelled subscriptions that would reduce its revenue by $1B annually.  

However, the company that is known for leading the way of personalisation is Amazon. It is estimated that 35% of all Amazon sales are generated by their recommendation engine. Given this, it is no wonder the commerce giant is continuously improving the way it uses AI to grow its marketplace. Amazon uses machine learning to accurately forecast demands, analyse purchasing patterns, and uses purchasing data to provide tailored product recommendations and promotions.

The huge investment by the biggest tech companies in AI indicates that something is going well. The question is if the hotel industry is taking AI and machine learning as seriously as other industries. Have hotels managed to envision the real benefits of using personalisation yet?


What about hotels?

Even if the tourism and travel industry is characterised by low AI adoption, we are seeing it move fast and fearless when it comes to introducing new communication channels as a means to collect more data and get more personal. Digital technology is changing the way in which hotels connect with guests by creating a relationship before, during and after the hotel stay. Guests are more connected to their hotel than ever. Unfortunately, personalisation is not always a priority when it comes to how this communication is carried out.

A popular travel disrupter that is mastering the art of personalisation is Airbnb. The service’s app has personalisation at its heart. It includes an innovative matching system designed to understand travelers’ preferences and then match them with the homes, neighbourhoods and experiences that meet their needs. With this type of competition, more and more guests booking through OTAs and the immediacy of service and control customers are used to, hotels are under pressure: they can personalise or perish. Personalisation is the answer for hotels looking to maintain or grow their market share in this challenging environment.

As a summary, I can break down the article to three simple call to actions that will help you on your journey towards greater personalisation:

  1. Learn: Make sure you have data collection means in all guest communication tools you use (before, during and after the stay).
  2. Comply: Collect and use all data in a way that complies with GDPR and the guest’s own privacy preferences (we will be addressing this important topic in an upcoming series of posts).
  3. Tailor: Ensure you have the tools that make it possible to personalise your guests' next experience by using intelligent algorithms and machine learning in place.
Subscribe to our newsletter!
Spam protection, sorry for the inconvenience