The complete guide to big data analysis in travel

Travel demand is as high as it has ever been.

The World Travel & Tourism Council estimates that global travel spending decreased 49.1% from 2019 to 2020, due to COVID-related restrictions. The recovery started in 2021, however, with the tourism industry showing a 35.6% increase, with most experts agreeing that the travel industry will fully rebound before the end of 2024.

These erratic metrics are best navigated by using the predictive analytics gathered via big data collection and analysis, which help travel-related companies with forecasting both their day-to-day operations and long-term planning in real-time.

What is big data collection and analysis?

Big data is a euphemism that describes mass coordinated efforts to aggregate and utilize large amounts of data from many data sources into one holistic strategy.

Companies will often refer to big data as a singular source of truth, relying on sweeping amounts of data and algorithms to devise marketing strategies, market trends, marketing campaigns, pricing strategies, and demand forecasting.

The purpose of big data is to leverage data analytics tools that are innately complex in order to uncover valuable insights that will improve customer satisfaction.

The following video explains more about what big data is and where it comes from:

How is travel data collected?

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The travel industry collects massive amounts of data about its customers in a variety of ways. Many travel companies will rely on real-time data and advanced analytics to provide a better customer experience with updated flight deals, promotions and travel recommendations.

By tracking customer behavior, it allows the travel company to enhance the travel experience through data-driven decisions. For example, customers who are looking for hotels in Barcelona would likely be more interested in travel packages that include dining options and amenities that are popular with travelers who stayed at similar hotels.

This data comes from a variety of sources, both internal and external. It can be structured, as with the fields and records in a database, or unstructured free-form data. In the travel industry, big data can include information about:

• Customer demographics

• Customer preferences

• Travel patterns

• Flights

• Destinations

• Meals

• Transportation

• Booking activity

• Customer recommendations

• Historical data

How is big data analyzed?

Collecting large amounts of data can be a daunting task, but analyzing this data is an even bigger challenge when it comes to decision-making and visualization. Operational efficiency is a crucial component of taking data and putting those insights into action.

Big data analytics must somehow integrate, organize and make sense of various types and formats of data collected from multiple sources. Data analytics platform providers use a number of cutting-edge technologies to analyze the data, extract actionable insights, and identify important trends. 

Travel analytics solutions work with a variety of advanced technologies, including:

• Artificial intelligence (AI)

• Machine learning (ML)

• Natural language processing (NLP) 

The insights gathered via the use of these technologies are essential to the success of companies in the travel and tourism industry. Travel-related companies that use big data analytics can predict industry trends, forecast potential disruptions, create personalized customer experiences, and extract more revenue from each customer. This provides a major competitive advantage over companies without these key insights. 

What are the uses for big data analysis in the travel industry?

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There are many ways the travel industry can benefit from prescriptive analytics in order to provide a better customer experience. Here are six of the more important ones.

1. Tighter revenue management

To maximize both revenues and profits, travel industry companies must sell the right products to the right customers at the right time, with the right price, and via the right channel. Big data analysis is essential for this. 

By analyzing data about pricing, occupancy rates, current bookings, seasonal trends, local events and holidays, travel-related companies can more accurately predict demand and price their products accordingly. Hotels can adjust room rates on a day-to-day basis. Airlines can tailor pricing for specific routes to specific cities at specific times of the day. Car rental companies can adjust their fleet inventory by city and season. It's all in the service of efficiently satisfying customer demand while maximizing revenue.

2. More targeted marketing

Travelers today expect personalized service – and that includes the marketing messages they receive. By utilizing big data travel, companies can more accurately target the marketing they send to current and potential customers. Travel deals and pricing can be personalized to individual customers based on their interests and history. Travel websites can also offer customized experiences for each user, thus encouraging more clicks and conversions. 

3. Enhanced customer experiences

The personalization enabled by big data analysis extends to the customer experience at all potential touchpoints. By knowing what individual customers prefer and expect, hotels can gain a competitive edge and personalize the available amenities offered to each guest. Travel agencies can tailor more desirable tour packages. Car rental agencies can preselect preferred makes and models of vehicles. Every customer interaction can be enhanced when you know what customers want and need, which you can gain from big data analysis.

4. More effective recommendation systems

The more on-target the recommendations you make on your website, the more conversions you'll achieve, which is where big data comes in. When you know what customers like, you can more easily recommend products and services that meet those needs. Big data analysis provides the information based on customer history and interest that drives more effective recommendations. 

5. Better reputation management

To best manage your reputation with customers, you need to know what you're doing well and what needs improvement. Analyzing the big data collected internally from customer interactions and externally from social media and review sites helps identify a company's strengths and weaknesses. You can use this information to enhance or emphasize specific services and adjust employee training as necessary.

6. Faster responses to social media

Travelers today use social media to talk about hotels, airlines, and other hospitality businesses that provide them with a superior experience. They also use social media to post grievances about those companies that deliver a disappointing or unpleasant experience. 

Collecting big data from social media enables detailed sentiment analysis and customer profiling. It also alerts you to online comments, both positive and negative, and enables you to respond to these comments within minutes of them being posted.

Let Optimizely help you get the most out of big data collection and analysis 

Optimizely helps you get the most out of your travel business' biggest asset: your data. We use big data analytics to help you maintain data governance and collect customer data from a variety of sources to better understand your customers and deliver a more personalized user experience, all from a single dashboard. We'll help you better predict traveler behavior and optimize your company's marketing and sales.