Predictive Analytics in Travel Industry

 By Qing Liu

Predictive Analytics is currently in its heyday. It's impressive to see how beautiful and convenient our lives have become because of these advancements. Predictive analytics has become the technology that companies turn to gain a competitive advantage and provide a fact-based assessment of the future development of the industry. The increased use of predictive analytics stems from the proliferation of big data and the insights these big data sets provide for further business goals. This affects the influx of predictive analytics beyond pure technology and the reach of large enterprises. Tourism is one of them. (Sas.com, 2022)

 

What is Predictive Analytics? 

“Predictive Analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. Our goal is to go beyond knowing what has already happened to make the best possible assessment of what will happen in the future.” (Sas.com, 2022)

Why is Predictive Analytics Important? 

Predictive Analytics studies user behaviour and makes meaningful recommendations, and businesses are turning to predictive analytics to help solve difficult problems and uncover new opportunities.

Common Uses of Predictive Analytics Include:

• Fraud Identification: There are huge numbers of air passengers worldwide every year. This generates many online transactions that require real-time verification. The losses from payment fraud and other related transactions are enormous. Predictive analytics plays an important role in cyberattacks, and predictive analytics, combined with multiple analytical methods, can improve pattern detection, and prevent criminal behaviour.

• Optimize Marketing Campaigns: Predictive analytics are used to identify customer responses and enhance sales opportunities in industries such as travel and help businesses develop quality customers.

• Improve Operations: Forecasting models can also be used to forecast inventory and manage resources. Predictive analytics doesn’t just help airlines set airfare prices. Predictive analytics can also help hotels predict customer traffic.

 

In the travel industry, predictive analytics has many uses, opening up endless possibilities for airlines, airports, travel agencies...and  travellers, such as:

• Alerting and Monitoring Systems: The amount of data that businesses generate and the record is enormous. Humans cannot fully track this data and its anomalies. Businesses can use predictive analytics to monitor and prevent incidents.

• Recommendations and Recommendation Systems: Would you be surprised if a Google page recommends you a wedding ring, for example? This happens because it studies your recent search history and understands your inclination to buy. (Jones, 2019)

• Dynamic Offers on Travel Products: With travellers looking for a personalized experience, it’s important for businesses to use predictive analytics. The system needs to quickly predict what customers want and then adjust offers accordingly. For example, integrate flights, extra bags, hotels, while dynamically adjusting prices and considering competitor offers in real-time.

• Types of Passengers: Leisure and business travellers travel for different purposes and therefore have different needs for price and product quality. Through predictive analytics, companies can leverage an individual’s personality and preferences to create compelling packages, not just Simply choose a room or flight seat to forecast and adjust travel offerings accordingly. (Acuna Agost, 2016)

• Video, Image, and Speech Recognition Systems for Travel Purposes: our human brain responds to stimuli from different senses. They are better suited for understanding natural forms of communication, such as images of sounds, rather than written messages in words. With the development of deep learning and other artificial intelligence algorithms, the processing of such unstructured data is no longer science fiction. Machines are now able to understand images and sounds, in some cases even better than the human brain. This opens up new opportunities for applications in the travel industry: from inspiration (where to go?) to booking automation. (Acuna Agost, 2016)

• Building Loyalty: Predictive analytics also play an important role in building customer loyalty. In travel marketing, leverage past data and current browsing patterns to personalize and optimize each customer’s booking experience.

• Extreme Customization: In the analytics-driven travel industry, predictive analytics can be combined with in-depth customer recommendations and data to inspire purchases and loyalty through customization.

• Maximize Revenue: Strategically price tickets when demand is high, scarcity or strategic price reductions for limited short periods of time all encourage customers to book. (Nitin, 2016)

 

The Target Companies using Predictive Analytics:

• Booking.com uses predictive analytics across divisions to serve different purposes. Test changes made to products or products through randomized controlled trials based on predictive analysis. In building products using data analytics, the company also analyzed how the proposed model would affect the data that would be collected. They also combine data analytics teams with marketing and product development to avoid creating silos and encourage collaboration to build better predictive models.　

• Hipmunk allows users to search for flights from city A to city B via the popular cloud-based instant messaging platform Slack. Integrating existing instant messaging applications into future AI and ML-based technologies shows that intelligent assistants, powered by predictive analytics and millions of user data, are the future of travel.　 (Chatterjee, 2020)

 

Predictive Analytics enables businesses to drive the achievement of their business goals, rather than reactively reacting to industry trends and situations as they occur. While it may seem like magic to those who don't understand how it works, predictive analytics is a veritable gateway to revelatory insights that can transform even the smallest companies into industry giants. With predictive analytics today, businesses can not only understand what happened and why, but also uncover insights into the future.　

Author: Qing Liu

Keywords: #PredictiveAnalytics, #TravelIndustry, #Partners, #travellers, #investors, #resources, #businesses,#goals

Reference:

• Chatterjee, M., 2020. What Are the Use Cases for the Predictive Analytics in the Travel Industry?. [online] mygreatlearning. Available at: <https://www.mygreatlearning.com/blog/what-are-the-use-cases-for-the-predictive-analytics-in-the-travel-industry/> [Accessed 1 March 2022].
• Jones, M., 2019. Predictive analytics in the travel industry: use cases. [online] bigdata-madesimple. Available at: <https://bigdata-madesimple.com/predictive-analytics-in-the-travel-industry-use-cases/> [Accessed 1 March 2022].
• Nitin. 2016. How To Bring Predictive Analytics Into Your Travel Marketing Roadmap. [online] Available at: <https://zetaglobal.com/digital-marketing/predictive-travel-marketing/> [Accessed 3 March 2022].
• Acuna Agost, R., 2016. more examples of predictive analytics in travel industry. [online] bigdata-madesimple. Available at: <https://bigdata-madesimple.com/5-more-examples-of-predictive-analytics-in-the-travel-industry/#:~:text=Predictive%20analytics%20play%20an%20important,the%20% E2%80%9Cfalse%20positive%E2%80%9D%20cases> [Accessed 3 March 2022].
• Sas.com. 2022. Predictive Analytics: What it is and why it matters. [online] Available at: <https://www.sas.com/en_us/insights/analytics/predictive-analytics.html> [Accessed 5 March 2022].