Customer data and information is critical for tourism companies to provide a unique experience and convenience to hospitality clients.

Data applications in restaurants enable great customer experiences and the same holds true for tourists and travel companies. Accordingly, data science presentsopportunities for hotels to harness value from data and making them competitive.

Apps such as Yelp and Foursquare have brought the restaurant experience to customers through their phones. Ideally, these technology solutions make customer experiences great and allow restaurants to raise their standards. Data science is transforming hotels with restaurant managers hiring digital experts to handle IT departments.

The hotel¹ industry is a space where guests are already using digital assistants such as Alexa and with data science adoption increasing, the time is right for restaurants to evolve into a digital environment.

As hotel rooms become digital with smart lighting and TV systems, it becomes convenient for the guest to use advanced technologies such as voice to control the room.


Artificial Intelligence is not new to the hospitality industry² in the specifics of narrow intelligence. The industry has long had technology capable of providing decision support or executive information around specific and targeted sets of consolidated information. The main example is what we today know as revenue management systems³.

The various companies that have provided software solutions for this domain of expertise have combined information about the future, information about the past and then #algorithms against this information to determine the future state of reservation and booking behavior to forecast lead time and make pricing recommendations.

AI is best suited to take over repetitive tasks and use large amounts of data. AI will, therefore, touch many areas of the hospitality industry. For example, hotels could use AI at the front desk to automate mundane chores like check-in and task management.

Alternatively, hotels could use AI in sales and marketing to intelligently upsell, cross-sell, personalize communications, or customize its website based on a guest’s profile or behavior. Revenue managers will also make use of AI to intelligently set pricing and build out attribute-based pricing models.

Data Analysis in Hotel Operations and Travel

A hotelier’s job has radically changed over the last few decades. Because of integration of the internet and the rise of direct bookings and #online travel agencies, the hotel sector underwent transformation.

Over the next decade, we saw the rise of social media⁵, where guests started to comment and review their travel experience on public platforms, disrupting more and more the relationship with travel providers.

Lastly, in recent years we have witnessed the non-stop growth of ubiquitous technologies, empowering travelers on the move.

All these evolutions have resulted in growing numbers of travel and hospitality industry professionals working with digital technology in-house. Nowadays, even small independent hotels have someone who takes care of the web. However, as the amount of travelers #data⁶ is skyrocketing due to digitized customer journeys, the extent to which it is efficiently used by operators varies greatly and, often, falls short.

The Customer Experience and Data

Nowadays, generating a proper understanding of data and connecting all data sources effectively is paramount in generating competitive advantage, providing superior customer value, and ultimately orientating the future of any business.

Being able to draw from data of both internal and external sources will allow hotels to paint a more accurate picture of how changes in the environment impact the business. Taking over some of the more data driven tasks will allow hoteliers to focus on the application of the forecast and changes that will have positive impacts on the business.

Data Science Approach in the Hospitality Sector

Businesses that generate enormous amounts of data should not only leverage it to understand their current performance but also to generate prescriptive #analytics to orientate their strategy. #Datascience⁸, which may at first seem expensive is actually quite feasible.

Let us explore three areas where a deep and conscious understanding of data could take travel and hospitality firms to the next level.

1. Customer Equation: Differential Value

Travel and hospitality industry professionals around the world are perfectly aware of their competitors’ moves at a local, national, and international level. In a very competitive marketplace, constantly monitoring and understanding competitors’ offers and strategies is critical and is a very common practice.

But data is providing an additional layer: the differential guest value, or in a nutshell: what is the current offer of your business? How can it be positioned with respect to competitors? How can you ultimately differentiate your service from direct competitors?

In Switzerland alone, hotelleriesuisse estimates that more than 90% of accommodations are privately owned and operated. This means that there is a great focus on superior customer value⁹. Data allows hoteliers, to base their choices on real insights rather than on rumors and feelings. Insights about how managers interact at different touchpoints during the customer journey can also help fine-tuning the way hoteliers position their products on the market.

2. Hotel Marketing

Marketing is one of the most evident ways travel and hospitality industry professionals can use data. If using data to improve the competitive advantage of business will impact an organizations’ identity and core values, establishing constant communication streams and engagement with guests throughout their customer journey will not impact your marketing strategy, but will make the whole practice evolve towards integration with day-to-day operations.

3. Operations

Hoteliers can surely start by focusing on mapping their visibility efforts along key touchpoints of the customer journey to maximize engagement with the customer. But data and technology can enable an even deeper experience by activating these touchpoints before a guest sets foot in a property to provide a truly personalized journey. When guests’ preferences and behaviors are tracked and recorded, they can be cascaded to the manager, then distributed to the room divisions and so on.

AI is the Future of Hospitality and Travel

Big data and analytics are playing a crucial role in digital transformation efforts of organizations in general and in the tourism and hospitality industry, thus driving greater effectiveness and efficiency and the strategy to define new business models and bring about successful change.

An organization that can gather data around the above-mentioned digital elements will then be able to transfer that knowledge into the in-room experience. This is the basis for a smart hotel¹⁰, where data is used for the day-to-day, personalized delivery of guests’ value.

This is only a partial synopsis of the possible strategic uses of data science. However, the main message holds true: do not be afraid of data. Data is everywhere and can enhance the competitiveness of your business.

Data can also support product development, marketing and operations while also aiding in the transformation towards “smart” businesses. This is true for any single professional within the travel-value chain, from hotelier and destination manager to service provider.

When applying #AI to the interaction between hospitality brands and travelers, we can arrive at Predictive Personalization: understanding user behavior to predict how to best serve him so that we increase both user satisfaction and hotel revenue. By focusing on a narrow, industry-specific use of machine learning, it’s possible to create predictive algorithms and offer completely new, powerful targeting options like buying intent or user value, and even attempt to find the holy grail of e-commerce: personalized price.

Works Cited

¹Hotels, ²Hospitality Industry, ³Revenue Management Systems, ⁴AI in sales and marketing, ⁵Social Media, ⁶Data, ⁷Data Driven Tasks, ⁸Data science, ⁹Customer Value, ¹⁰Smart Hotel