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5 data science tips for travel companies

Categories: Data science

In this article, we’ll take a look at five key data science tips for travel companies that want to innovate ahead of the curve.

The travel industry has been one of the most responsive sectors in adopting data science and latest technology innovations. Staying relevant in the age of Airbnb and Google’s expansion into travel services is the biggest challenge facing brands in the industry. Those that fail to adapt disappear and we’ve all seen how spectacularly this can happen with the recent collapse of Thomas Cook.

By failing to make the digital transition and adapt to changing technologies, the world’s oldest travel brand proved that even giants can fall if they fail to adapt.

Data science is the next revolution in travel bookings and some companies are already using the technology to cement their position as industry leaders and future-proof their businesses.

Here are five data science tips for travel companies.

#1: Start with hyper-personalisation

Hyper-personalisation uses big data and AI to deliver personalised offers and experiences to individual consumers. By treating customers as individuals and delivering unique services/offers based on their preferences, hyper-personalisation encourages travellers to spend more, while increasing brand loyalty through more enjoyable experiences.

Graph showing how much more travellers are willing to spend for good customer experience.
Travellers are happy to spend more on flights and hotels in exchange for a better experience

[Source]

We’ve mentioned hyper-personalisation as a key strategy for travel brands before. With 86% of travellers saying they value personalised offers, the industry can’t afford to ignore the demand for richer, personal experiences. Those that do will be left behind by the likes of Google, Airbnb and Skyscanner that are all moving to provide this kind of experience for their users.

An example of this in action is Mezi, which was recently acquired by American Express. The platform recreates the travel agent experience for the digital age by providing an end-to-end booking experience for flights, hotels and dining for corporate travellers.

Mezi

Major travel brands are also using hyper-personalisation to enhance the post-booking experience for travellers. Virgin Hotels has launched a personal assistant app customers can use during their stay. They can request extra pillows, laundry pick-ups, a turndown service, valet or even change the temperature of their room using the app. Meanwhile, Delta Air Lines and other airlines are using similar technology to personalise the in-flight experience and reward customers with flight miles or gift them points for any in-flight issues they have.

#2: Use real-time insights for travel recommendations

Another key application of hyper-personalisation is delivering data-driven recommendations – something we’ve all seen on platforms like Amazon, Netflix and Spotify. We’re also seeing this from the likes of Expedia and Airbnb that use AI to deliver personalised recommendations to users.

Recommended hotels

Source

Data science is capable of so much more, though. Booking platform Hopper uses AI to predict travel prices for flights and hotels, up to one year in the future with a 95% accuracy rate. The platform helps travellers choose the best time to make their bookings for the best possible deal.

Hopper booking platform

More than 30 million travellers around the world have used Hopper to track and book trips.

#3: Make the most of predictive analytics

Prices aren’t the only factor that affects people’s travel choices and it’s not the only thing travel companies can use predictive analytics for either. The same algorithms that compare user data to provide relevant recommendations can predict the future actions of users as they progress along the booking process.

This technology increases booking rates, reduces drop-outs and allows brands to deliver more relevant messages every step along the way.

It can also help travel firms overcome barriers getting in the way of bookings. We’ve already seen how Hopper helps travellers get the best deal on their bookings. What makes this so special is that it locks users into the platform because they know they’re going to get the best price by continuing to use the platform. Even if they don’t book now they’re going to come back to Hopper for the booking later.

Research from Expedia (among others) suggests price is the most important factor in travel booking choices. Hopper capitalises on this by making prices its key selling point and all it needs to do is notify users when the right time has come to book their ticket.

Incentive is sky-high.

Not all studies point toward prices being the top priority for travellers, though. Others show safety is the most important factor with holiday-makers wanting to know they’re heading to safe locations. This can mean anything from political unrest, conflict, extreme weather, natural disasters, crime rates and all kinds of other factors – all of which can be predicted, at least to some extent, with data science.

#4: Automate actions based on real-time & predictive data

Data science also has a lot to offer behind the scenes by making your marketing strategies more efficient. We’ve just mentioned how factors like extreme weather and political issues can impact on people’s travel plans but these are also disruptors for travel brands themselves.

The protests in Hong Kong haven’t done much for travel bookings to the island, while the diplomatic fallout between Japan and South Korea has had a major impact on traveller numbers between the two countries. Likewise, the recent floods in Italy have caused all kinds of problems for local businesses, travel-related businesses and tourists.

When incidents happen travel brands need to react and the first step should be automating actions to adapt your marketing strategy. For example, you might want to automatically pause ads for affected locations, redistribute ad spend and adjust budgets to reduce the negative impact. You can also use dynamic pricing to reduce prices for affected areas and possibly even increase them elsewhere to reduce the deficit.

Don’t forget about existing customers and those already in affected locations. You should automate travel advice emails, notifications and whatever else you can send out to help your customers deal with any surprises. Finally, make sure you don’t automate everything for customers who experience problems. Automate rapid responses but make sure you have a human team in place to show your customers they’re not alone in their time of need.

#5: Bring it all together & maximise customer retention

According to BIMA, the biggest challenge modern travel companies face is building brand loyalty. With so much choice available, competitive pricing and the transparency of customer reviews, travellers have little reason to stay loyal to brand names.

The solution to this problem brings us back to hyper-personalisation. A 2018 report by McKinsey found that 69% of customers are more loyal to a travel company that personalises their online and offline customer experiences. Travel is inherently all about the experience and everything brands can do to maximise the enjoyment of these experiences, the stronger brand loyalty becomes.

Examples of hyper-personalisation
Examples of data points that can be used to deliver more relevant messages and build customer loyalty

Source

Positive experiences need to be reinforced with relevant messages, delivered at key moments. These are ultimately the messages that turn previous customers into second-time and repeat buyers. Data-driven recommendations are a powerful tool for this but the leading travel brands are learning more about their customers individually to understand what matters most to them – pricing, convenience, luxury, weather and any combination of personal preferences.

Of course, you need to get your hands on the right data before you can do this. Thankfully, research from Salesforce shows 57% of consumers are willing to share personal data in exchange for personalised offers or discounts – so leverage this incentive.

Data science is changing the way top travel companies engage with prospects and create customer experiences. In the case of emerging platforms like Mezi and Hooper, innovators are putting data-driven personalisation at the heart of their business model, in a way that increases the value of using those apps with every booking.

By improving customer experiences, streamlining marketing strategies and helping travel brands increase loyalty, data science will be key in overcoming the biggest challenges businesses in the industry face. It could be the deciding factor between the travel brands that make it and the ones that don’t.

Interested in data science?

If you’d like to talk about how data science could enhance your digital marketing, talk to our team today on 02392 830281 or email us.

Chris Pitt is Operations Director at Vertical Leap and has over 20 years’ experience in sales and marketing, previously holding senior roles in tax and financial companies, working with customers such as Ernst & Young, Deloitte, KPMG and Groupama. A regular at exhibitions and events across the country, Chris has presented at all the major industry exhibitions as well as providing educational talks at Google’s London HQ.

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