Applications of Data Science & Machine Learning in Travel
Data science is the coming together of various paradigms, algorithms, tools, and machine learning principles to derive descriptive, predictive, prescriptive and machine learning goals to determine hidden data from the raw data
Travel is a growing industry and the constantly increasing numbers of consumers require high data processing. This is where data science algorithms are vital. Travel assisting industries like airlines, hotel industries, reservation and booking websites etc. are being challenged everyday by the broadening arena of the travel customer base. Data science has efficient and marketable uses in the travel and the hospitality industry, which we’ll explore in this article.
One area where data science has proved extremely valuable is Sentiment Analysis. This analysis of customer sentiments depends heavily on review websites. Travel companies looking to increase their business need to carefully analyze how the customers have reviewed their services. Companies also track mentions and emojis customers use for brands on social media to analyze sentiments. It’s critical to understand the real attitude of your customers towards your brand and how likely would they be to recommend your services to others, and data science provides the backbone required to do so.
Providing Personalized Recommendations
Do you know how your social and digital media is aware of your choices and only provides you with the travel companies, packages and destinations that you are more likely to look up? Recommendation engines work on how customers interact with accommodations, transportation and experiences, pre and post-booking. They analyze data mined from past searches and browsing behavior across various geographies, demographics, genres and travel services. The personalization algorithm would rely on the combination of all these data points to build and present recommendations to users that are likely to yield the highest possible conversions.
It will help show the best deals based on customer preferences. E.g. If a customer has a history of showing preference for driving to destinations within a particular radius, the app would suggest the best car rental options taking into account the user’s vehicle preferences and proximity to the planned destination. If the user’s purchase history suggests that they prefer to stay at a hotel overnight for long road trips, the app can suggest ideal hotels along that route. If they prefer to book direct flights, it would show non-stop flights first and then the ones with a layover, and so on.
The data collected can also help craft highly targeted advertising campaigns and present them to the right customer at the right time at the right place. Using this example travel companies can segment their potential customers.
Planning and building itineraries using data science can help in cost cutting, time-management and easier decision making. The new age AI powered bots are trained in the data science tactics required to constantly learn about customer requests and requirements. They can help customers choose what they are looking for more wisely with less time investment and the most cost-effective plans. Every customer’s travel history to every destination’s travel history is taken into consideration by the AI powered machine learning tools to help the executives generate the most fitting plans.
Bots have great applications in customer support too. It can equip support executives with all the information and analysis they need about the customer to help them provide a resolution at the earliest. AI and ML-driven chat bots can automate support and save millions. Bots can learn trigger words and help out with customer queries 24×7. They can also help cut out the language barriers that are often obstacles in dealing with customer queries. According to HubSpot, 71% of people use chat bots to solve their problems faster because they are easier to approach.
In the hospitality sector, Hilton built a bot named Connie that helped guests with whatever questions they had. It is a virtual concierge that helps the guests with their queries regarding dining or tourist attractions. It is an AI enabled bot that stores the data that the guests review and on the basis of that, assists the future guests.
Pricing and Demand Forecasting
Data science helps with predictive analytics that some large travel brands and airlines have been putting their faiths in during the recent years. The dynamic pricing and fare forecasting are the new artillery that helps travel brands optimize revenue and profit from the data served.
Demand in the tourism industry is dependent on the changing seasons which ultimately influence the prices that change along with them. Rooms are priced high during the peak season and low during the off-season.
With the help of the data science, particularly trend analysis, multiple websites can benefit from these constantly learning phenomena to predict future demand and pricing. This helps the industry with:
- Accurate discounting algorithms to minimize losses
- Manage weekend pricing
- Corroborating information on the parent site as well as the third- party booking site
Data science helps with the sales optimization of the brands. Helping sales managers with discovering where the customers want to go to devising personal packages accommodating every demand put forward to the brand for best results; and crowd sourcing data to arrive at prime demands. It can also help them suggest ancillaries based on past behavior and preferences to maximize revenue. The notification systems for some apps like Hopper, generate 90% of their sales.
Data science has helped increase the security functions as well. AI systems can help detect fraud better with practice and fine initializing. They can detect fraudulent payments and fake accounts, loyalty frauds or content abuse too. This cuts down on the risk of online business by recognizing abnormal behaviors.
So if the brands gather in authentic data and are well aware of the nook and crannies of their own product, AI and data science can help boost their sales up drastically.
Data science and its myriad applications discussed above hold the power to bring about a revolutionary change in how customers interact with travel brands and vice versa. Data driven technology helps both the consumers and the brands to make the best possible use of their resources – be it money, time or manpower without cutting out on benefits from both the sides.
With TravelCarma’s Travel iPaaS, tourism companies can automate their sales, marketing and support workflows through a centralized hub that can connect disparate systems and databases for personalization and swift decision making.