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Predictive Analytics in the Travel Industry: How Airlines and Hotels Leverage PA

Read Time: 4 minutes

The travel industry is one of the most technologically advanced markets in the world, adopting big data and predictive analytics (PA) when the tech was still in its early days. The highly competitive nature of the industry has prompted airlines and hotels to develop apps that leverage this cutting-edge technology in order to satisfy and retain customers.

There are several areas of the industry where PA plays an important role, including determining optimal pricing plans and creating a personalized travel experience. Plus, predictive analytics helps enhance the effectiveness of online marketing and advertising campaigns, saving on overhead costs and increasing an airline or travel agency’s ROI. So, let’s take a closer look at precisely how predictive analytics is transforming the travel industry.

Using Travel Analytics Apps to Optimize Pricing Strategies

The key to a successful pricing strategy is finding the perfect balance between what customers will actually pay for and what will help companies earn the most. Businesses have been applying big data analytics and PA for years in order to find a price that will keep them competitive without overcharging. The high volume of customer data makes it easier for travelers to find the best deal, as clever algorithms monitor market conditions, popular hotspots, flight quality and other factors in order to find the perfect price.

This philosophy is the bread and butter of companies like Trivago or Expedia, which analyze large hotel datasets and present the results in an easy-to-read fashion. By working with hotels and airlines, they reel in customers with optimized pricing strategies that consider factors such as timing, demand and seasonal trends. Plus, these algorithms are becoming increasingly sophisticated, sending timely alerts with fleeting deals consumers can pounce on when downloading certain apps.

One recent success story is Hopper, a popular startup that uses PA to help customers find the cheapest flights. The intuitive mobile app will tell you if all the rooms in a hotel will be booked, as well as generating suggestions for alternative itineraries based on weather forecasts or the expected airport load on a particular day. These algorithms ultimately make the travel experience cheaper and more pleasant.

Personalizing the Travel Experience With PA

Companies are always looking to meet the needs of individuals in order to increase customer satisfaction. PA helps customers find the most fitting travel route with predictive analytics engines that analyze metrics, including the size of the traveling group, hot travel locations for couples, price range, desired weather and other factors that help people make decisions regarding their travel plans.

This technology is especially effective in the hospitality industry as hotels are using big data to develop pre-emptive personalization. Everyone who works in a hotel or resort, from the management team to the front desk staff, can use customer data to develop unique experiences that fit a client’s needs before they make any requests. With these PA tools, hotels can develop an edge over the competition by creating a more personalized experience for travelers.

Airports have also been working towards optimizing the customer experience, as is the case with Amsterdam’s Schiphol Airport. The European hub ranks among the highest in customer satisfaction scores because the airport uses heat maps to examine how travelers make their way through the airport. With this data, they calculate how far travelers are from their departure gate and develop more efficient airport routes to improve the chances of a customer not missing their flight. The Amsterdam team even looks at factors such as noise pollution levels and staff friendliness in order to improve the flight experience.

However, airports still have a ways to go with personalizing the travel experience for consumers. An Accenture study found that 65% of travel executives believe they have yet to create a truly personalized system for customers to enjoy. As such, there is great potential for airports to create even more tailored recommendations for customers with specific preferences by leveraging the power of predictive analytics.

Improved Marketing Campaigns With Predictive Analytics

Big data plays an important role in predictive marketing. Airlines and travel agencies have been ramping up their advertising and marketing campaigns recently thanks to the large amounts of data available from online bookings. PA engines analyze this data, then companies can create ads that more directly target certain types of customers.

A business can monitor a consumer’s activity, such as where they stayed, what they did and what they ate, plus the reviews of their activities. This data can then be used to offer targeted suggestions during a trip or for future vacations, which ultimately improves a business’ conversion rates.

In addition to traditional advertising means, businesses are turning to consumers to bolster an agency or airline’s reputation in the form of reviews, ratings and recommendations. Expedia has been highly successful in synthesizing this data to maximize web and app traffic and conversion rates.

Social media also plays a key role in advertising a flight or hotel since many people share travel-centric reviews and post images of their travel experience online. PA is essential here in the form of sentiment analysis, which is the process of identifying opinions and breaking them down into categories. In the travel industry, sentiment analysis can estimate how positive a post is in milliseconds and automate the process of sharing these reviews to consumers in real-time.

Maximizing Resources in the Travel Industry

With the right technology, businesses can make smarter investments that will yield a higher ROI. In the travel industry, pricing is of paramount importance due to how expensive trips can be, and companies know this. Travel analytics allows these businesses to develop algorithms that examine market conditions and customer preferences to offer them the right price for a trip.

Using big data to create personalized experiences and recommendation engines is key to bringing in customers and retaining them in the competitive flight and hospitality market. Companies can use this information to push the right product to the right customer at the right time with enhanced advertising campaigns that consider a traveler’s individuals needs.

If you want to make your business more competitive in the flight and hospitality sphere, you need a developer with the talent and experience to help you achieve your goals. The team at 7T offers machine learning and predictive analytics services. We’re also well-versed in other emerging technologies, including augmented reality, virtual reality, blockchain, artificial intelligence and natural language processing.

7T is headquartered in Dallas, but we also serve clients in Austin, Houston, and beyond. If you’re ready to discuss your project, we invite you to contact us today.

Reach out to our team today!

Shane Long

As COO and President of 7T, Shane Long brings experience in mobility that pre-dates the term “smartphone” and the release of the first iPhone. His work has helped revolutionize the growth of mobility by bringing to market one of the first graphics processors used in mobile phones, technology that after being acquired by Qualcomm lived well into the 4th generation of smartphones, as well as helped pioneer the first GPS implementations in the segment. With a strong engineering and business background, Shane understands how the rise of mobility and Predictive Analytics is crucial to greater business strategies geared toward attaining competitive advantage, accelerating revenue, and realizing new efficiencies. As the leader of a B2B mobility solutions provider, he partners with business leaders including marketers and product developers to leverage enterprise mobile applications, big data and analytics, and mobile strategy.

Shane earned a B.S. at Texas A&M (whoop!) and studied mathematics as a graduate student at Southern Methodist University.


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