AI for vacation planning

by Rabin Poudyal

AI(Artificial Intelligence), also known as the “new electricity” (Jewell, 2019), is becoming the fuel of every new technology getting invented in the 21st century. Every new startup is joining this bandwagon to convert their million-dollar ideas into reality. Although the travel industry does not seem to have anything to do with this scientific technology, the travel giant companies are experimenting where it can fit best to bring it into action. There are many use cases where AI is taking some of the work that was previously done by domain experts. Vacation planning is one of those areas of the travel industry where AI can be expected to play a perfect role due to a plethora of reasons.

Generally, people interact with vacation planning software when they find it difficult to pick an option from myriads of alternatives available or when they are looking for new options they hadn’t explored before. AI can provide personalized suggestions and recommendations in such scenarios. For example, planning a visit to a new place can be daunting since there are a lot of things to be prepared for prior to travelling such as knowing about that particular place, culture, and people. It will take a lot of time to research this information by visitors themselves and pick their preferences. But if this AI comes to play then AI can easily recommend popular and trending activities from those places based on what the visitor likes or previously liked. There are many approaches to build a recommendation system for the travel industry. Some of the common approaches are:

  1. Deep Learning Based:

If we have a huge amount of data readily available, this is the most effective and efficient way to build a recommendation system. This approach does not require much expertise in feature engineering too, since we let an algorithm pick and prioritize features. The input to the algorithm can be the historical data of travellers, their activities and other patterns and output is a model that can predict accurate recommendations based on inputs for new users.

  1. Content based:

In this type of recommendation, we recommend the contents that have very similar attributes. For example, we can recommend hotels that have similar amenities to the one the user is/was searching for.

  1. Collaborative Filtering:

In this type of filtering, we recommend to the visitors what other similar visitors liked. For example, if a 25 years old male adult books a hotel with an infinity pool, it is also likely other males with the same background will book hotels with the same/similar amenities.

Not only can AI algorithms learn to give the best planning experience based on other previous travelers, they can also deal with many visitors at the same time. If this task was to be done by humans, it would be nearly impossible to streamline a lot of requests during peak vacation seasons. The AI-powered conversational assistants can also provide instant and optimized recommendations. For example, visitors generally like to get a quick response to their vacation plan so that they can alter something if they don’t like it. This loop becomes very quick with AI. We can achieve this personalization in scale with minimum cost. 

AI software serving multiple requests synchronously

AI-powered chatbots that sit on our favorite messaging platforms can help to fully automate vacations like booking an Airbnb or hotels and interacting with hotels about the arrival and departure of visitors so that hotels and vacation rentals can easily manage their check-in/checkouts efficiently. Sometimes guests will have to wait for a few hours before they can be welcomed into the hotels but with this AI technology, we can simply alert visitors about the time so that they won’t have to waste the precious time waiting for the room to be ready.

AI can be more helpful for solo travelers as well. When they are not sure about their plan, AI can accompany them. It can also help to predict the perfect time to get the best deals for booking. It can act as a virtual travel guide so that it can assist people where to go and what to do for a particular location. It can also help visitors to carry out activities successfully as well. For example, mountain hiking depends upon the weather conditions of the mountains. If the weather condition is not right then, AI can suggest travel to another similar location so that they won’t have to compromise on the experience they will get.

Vacation does not always go as expected. Visitors will have to change their plans in the middle of their stay due to time or budget constraints. In such a case, AI can automatically optimize the stay/visits to optimize the resources like time and money. Sometimes we feel that the duration we allocated for vacation is not enough and we want to extend the duration. In such cases, sometimes the vacation rentals can charge more than expected. In such cases, AI can provide the best suggestions possible based on the budget we have. Different types of optimization functions can be used for this case. Some of the popular ones are Adam Optimisation and Gradient Descent Optimisation.

Gradient Descent Optimisation
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 Especially for people who don’t travel frequently, predicting cost upfront before travel based on activities or stay is a difficult task. In such cases, experts can give the best suggestions but in this age of artificial intelligence, it can be done by digital domain experts like bots and provide the tentative amount for their personalized travel plan.

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One more win scenario for AI in the travel industry is also that people love to share things with bots rather than with people about their vacations due to privacy reasons. Sharing travel plans with humans might also bring other risks such as information misuse.

The part where AI shines is that it takes parameters like a number of people, amenities, budget, duration of stay, and finds the best deal possible for the particular time. The optimization algorithms behind can be trained to optimize based on the end goal of visitors. For example, these are the common end goals of most visitors – budget, experience, time. If the end goal is clear, AI can help plan vacation in the best way possible.


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All of the above areas of AI in the travel industry are just the tip of the iceberg of what is possible. The new travel industry revolution is the space travel for which AI is going to be an integral part. The virtual sci-fi experience which we used to get from the movies is going to be real soon. AI together with augmented reality are the future of the travel industry which we are yet to experience in near future.

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