Online search is now the first step for a majority of travelers, with some consumers visiting up to 38 sites before booking a ticket.
Yet the travel industry must adapt to newer digital marketing strategies to win over potential customers.
The key to success is delivering ultra-precisely targeted content, leveraging personalized retargeting combined with AI and deep learning.
A single customer looking to book a trip can visits hundreds of travel pages each day. The search often takes weeks before the final purchase is made.
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This means there’s a ton of data flying around that digital marketers need to make sense of.
The number of digital travel touchpoints grows rapidly, as travelers look for better offers via search engines, booking apps, online travel agencies, and deal sites.
However, 39% of leisure travelers and 45% of business travelers believe that they use too many websites to find flights. In addition, 43% of leisure travelers and 51% of business travelers apparently want to spend less time searching for flights.
Airfare, hotel and car rental providers can reduce this overload by serving brand awareness and personalized offers at precisely the right time. This moment is where AI and deep learning can change the game for digital marketers in the travel industry.
Deep learning-based advertising
Deep learning is an innovative branch of AI that closely imitates the work of the human brain in processing data and creating patterns for decision making.
Inspired by biological neurons in our brains, deep learning made it possible to get more reliable, richer, machine-interpretable user descriptions of customer’s buying potential without any human expertise.
The travel industry is distinguished by the fact that a huge amount of information and data is required to target travel customers. And here lies the true potential of deep learning.
Radoslaw Dobrolecki
For example, we were originally based on machine learning algorithms in its retargeting platform.
By adding on a complex layer of AI and deep learning (later on in 100%), offers displayed on our advertising banners are selected more accurately, which in turn increases the effectiveness of client campaigns by up to 50%.
But deep learning algorithms can do even more than this. This technology can equip the advertising industry with predictions of a user’s unique habits and desires.
It simplifies our everyday user experience by bringing deeply targeted ads that contain not only offers or services we’re more likely to buy, but also those which we haven’t seen or products we haven’t even thought about, but the probability of wanting them by this particular user is quite high.
There is a lot to fight for, if you also consider the fact that, when presented with a promotion offer, 30% of people would take a trip even if they weren't planning to go anywhere, and another 25% would consider going to a new destination they had not originally planned.
Different needs, adaptive strategies
When using deep learning in advertising, user segmentation can be a powerful component to target a unique customer journey.
Experienced retargeting providers are able to define specific goals for each group of users, individually adjust the stakes for each of them and bid for them accordingly to achieve the most promising results.
For example, one segmentation practice in airfare divides users between those who searched for flights (and went to the offer page, but did not convert into those who plan the travel in advance), and those who were occasional or last-minute flyers.
The first group will be targeted much earlier with very specific offers. The second group will instead, receive information about the last available seats on the plane. The same goes with business travelers who buy at short notice or a random traveler, who came to a portal from a price comparison site.
It also important to add, that users can be segmented according to places they came from – whether directly from airline sites, online travel agencies or travelers’ site.
There is also the option to segment based on class of seats, for example by creating a segment of users who may convert to first or business class.
Today’s performance-based marketing campaigns can be targeted with so many different variables that you’ll want to discover which ones work best for your business and consumer needs.
In general, user segmentation allows brand to step out of traditional targeting and dig deeper into utilizing all the data – everything to make the message even more personalized.
Cross-selling is mandatory
According to PriceWaterhouseCoopers, travel data carriers must focus on ancillary revenues – including lodging, rental cars, entertainment and personalized itineraries.
Therefore airlines will have to develop their digital marketing capabilities and focus on gathering as much data about customers as possible to create a detailed profile of the traveler – and then transforming it into an individual offer.
When presented with a promotion offer, 30% of people would take a trip even if they weren't planning to go anywhere, and another 25% would consider going to a new destination they had not originally planned.
Radoslaw Dobrolecki
For example let’s assume that a user books a city break in Los Angeles. They’ll need a flight, perhaps a hotel, and local transport, like a rental car. Perhaps they are interested in local events or sightseeing, too.
The travel industry is distinguished by the fact that a huge amount of information and data is required to target travel customers. And here lies the true potential of deep learning.
The more data algorithms have access to, the better results they will bring. Only deep learning-based algorithms can collect, observe and analyze these data, to present a tailor-made banners that works on a highly personal level for each user.
Not just better performance
Many travel companies often focuses only on boosting their performance with retargeting providers. But retargeting gives them also a lot of creative opportunities to promote their brands successfully.
The easiest way is to promote themselves by simple banners encouraging users “to plan their next trip with us” or promoting most attractive destinations in connection with calendar, like travels to exotic countries in winter, or special offers before vacations or national holidays.
More advanced ones can be targeted to people who used travel services over a few months ago.
Another interesting option is to promote destinations with some advantages, like comfortable flight hours, business class seats, free unlimited WiFi, extra loyalty points or the cheapest offers.
Users who have been searching for such things can be easily reached with personalized retargeting.
Data analysis is key
The travel industry is distinguished by the huge amounts of information and data that are available to target travel customers.
Retrieving this data is easy; the real challenge is to analyze that data draw appropriate conclusions from them. And here lies the true potential of deep learning.
The more data algorithms analyze, the better results they will bring. The travel sector must adapt to a mindset of collecting and properly analyzing data, leveraging a complete view of the traveler buying journey like never before.