How to Leverage Data Analytics in the Hospitality Industry

Customers use online services for everything from purchasing plane tickets to making hotel and restaurant reservations. Hospitality organizations use data analytics to unlock insights, improve operations, and maximize profits. Leveraging analytics enables companies in this space to achieve financial and operational efficiencies while delivering personalized services and offerings. As competition increases, and customers enjoy more options, companies must use data to differentiate themselves in a crowded market.

What is data analytics in the hospitality industry?

Data analytics is the process of collecting, analyzing, and using data to gain insights and make informed decisions that can improve the operations and profitability of hotels, resorts, restaurants, and other businesses in the hospitality industry.

The hospitality industry generates vast amounts of data from various sources, including customer bookings, transactions, loyalty programs, social media, and guest feedback. Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience.

For example, hotels can use data analytics to identify booking patterns and optimize room rates, inventory, and staffing levels. Restaurants can analyze data on customer preferences, dining habits, and feedback to improve menu offerings and personalize customer experiences. Data analytics can also help businesses track and measure key performance metrics, such as revenue per available room (RevPAR), customer satisfaction, and loyalty.

These analyses enable businesses to gain insights into their target demographics and tailor services, ultimately increasing customer retention and brand loyalty. Additionally, by uncovering patterns and trends across large data sets, they can identify opportunities for cost savings and measure their performance compared to peers.

What are the benefits of data analytics in the hospitality industry?

As organizations within the hospitality industry collect, aggregate, and transform large data sets, data consolidation enables them to manage data more purposefully and democratize the analytics process. Some of the key benefits of this include:

Simplified data governance

Data governance and data analytics support each other, and a strong data governance strategy is integral to ensuring that data analytics are reliable and actionable for decision-makers. The more data fed into an algorithm, the more accurate the outcome. Over time, data stored in disparate databases or systems becomes unmanageable, especially with no clearly assigned responsible party. By consolidating data, organizations simplify data governance processes, including maintaining data accuracy and timeliness.

For example, Virgin Australia established a data governance framework to ensure that everyone who uses data at the airline works from a common set of definitions, and their data access is governed through a carefully developed set of policies.

Further, companies in the hospitality industry collect and analyze personally identifiable information (PII) that require additional security and privacy protections, like the General Data Protection Regulation (GDPR). Breaking down data silos enables them to identify all sensitive data storage and processing locations so that they can implement the appropriate controls, like limiting access on a need-to-use basis.

Data-driven decision making

Consolidating data in a single location also enables organizations to use their data more effectively when making decisions. Performance statistics give organizations historic insight into key performance indicators like occupancy rates, average daily rate, length of stay, and revenue per available room (RevPAR). Meanwhile, predictive analytics enable them to analyze customer market trends. Combined, these two analytics sets can help organizational leaders make data-driven decisions that compare weaknesses while improving customer stays.

How does consolidating data support self-service? One major online travel agency unified their data landscape with a data mesh architecture. By moving from an island architecture to a singular data landscape, the company granted the product development group the access needed to complete their job functions. This empowered data consumers to find trusted data and put it into action faster, leading to the development of customer-centric, data-driven products through self-service analytics.

Improved ROI

With data stored in a single location, organizations increase the ROI around their investment in analytics. When organizations democratize data, people across the company can leverage analytics, enabling a data-driven corporate culture. As more people use the technology, the organization gains more from their data.

According to a survey by Hospitality Technology, 86% of hotels believe that data analytics can help them increase revenue, while 77% believe it can help them improve guest satisfaction. For this reason, major chains, like Hilton Worldwide and Marriot International, have launched global D&A platforms to offer personalized experiences and promotions for guests.

One report by Amadeus estimates that data analytics can help hotels optimize pricing and inventory management, leading to an increase in revenue per available room (RevPAR). For example, hotels can use data to identify demand patterns and adjust room rates accordingly.

7 use cases for data analytics in the hospitality industry

With data analytics, companies gain valuable visibility into the customer experience, financials, and the larger market. With this data, they can make informed changes to business models, operations, and offerings. Other use cases for data analytics in the hospitality industry include:

1. Optimize revenue and pricing management

By gathering, aggregating, and correlating customer and market data, companies can identify ways to optimize revenue and pricing. With data analytics, organizations can optimize prices based on market demand. For example, by correlating seasonal trends with market data, they can identify better pricing strategies, such as limited-time offers, that enable a competitive advantage.

2. Enhance guest experiences

The hospitality industry’s core service is providing customer-centric experiences. Today, guests have more opportunities — public and private — for sharing feedback. With data analytics, organizations can collect customer experience data from sources like social media, travel websites, surveys, and even written notes.

Comparing this data across brands and geographic locations provides insights into areas of both success and improvement, giving companies a way to meet expectations and provide consistent experiences.

For example, the Marriott International hotel chain uses data analytics to personalize guest experiences, with their loyalty program as a major source of data. They use this data to understand guests’ preferences and behavior, and to offer personalized recommendations and promotions.

3. Improve marketing

Whether looking to build customer loyalty or appeal to new customers, hospitality companies can use data to develop informed marketing campaigns. Increasingly, identifying your audience’s preferred marketing channels and speaking directly to their interests is a best practice the consumer expects. D&A teams can then measure the marketing department’s ROI by analyzing KPIs like:

• Website visitors

• Page views

• Bounce rates

• Conversion rates

• Email open and click rates

By identifying what works and what needs improvement, organizations can pivot to appropriately address their preferred clientele.

As an example Finnair is using data analytics to improve the customer experience by predicting what customers want, what their propensities are for certain actions, and how the airline can recommend the most interesting options for them.

4. Keep a pulse on competitors

In a crowded market like the hospitality industry, companies need to know how they compare to their peers. Data analytics enables organizations to compare pricing, product features, customer reviews, and guest feedback. With these insights, they can identify areas where they have a competitive advantage and ones where they need to improve. Further, these analytics often provide insights into competitor budgets, giving a company an idea of its comparative financial strength.

5. Identify new products and service offerings

By tracking trends, organizations can identify gaps in their product and service offerings. By combining customer experience and market data, organizations can identify new offerings that would retain or grow their customer base, like offering discounts. Additionally, analytics enable hospitality data leaders to identify potential business partners who offer complementary services that appeal to their customer base.

6. Identify new audiences

Data analytics enables companies to identify new audiences. Organizations can look for trends by collecting data about customers, like:

• Age

• Family background

• Income

• Leisure activities

• Purchase history

Using these insights, companies can look for new audience segments that they might not have considered.

As an example, Hilton Worldwide launched a global data and analytics platform in 2020, which uses machine learning and artificial intelligence to provide real-time insights and personalized experiences for guests. The platform analyzes data from a variety of sources, including customer preferences, travel patterns, and local events.

7. Customize on-site services

By analyzing data, organizations can build customized offerings that meet customers’ needs. By analyzing geolocation and purchase history, organizations gain insights into the types of experiences people like, enabling them to offer discounts or recommend local services. By proactively customizing the experience, the organization builds customer loyalty.

How Alation’s data catalog helps uncover valuable insights

With Alation, hospitality organizations can automate the time-consuming, manual processes that slow down analytics. With Alation, you can break down data silos so people can find, understand, and trust data — and collaborate around it with total confidence. With a data intelligence platform like Alation, data and business people can align on key goals and establish a standardized vocabulary across the organization while ensuring that people can access the data they need.

Curious to learn more about how travel companies use Alation to break up data silos?This case study featuring Virgin Australia reveals how their Data Platforms team used Alation to align lines of business, establish a common data language, and launch a governance framework that democratizes data with the appropriate guardrails.