« All Experts

Ask the Experts

We chat regularly with experts and pose them a single question to help share their knowledge and experience with you.
Pete Kelly Commercial Director, UK & Ireland Adara

How can hotels and airlines best use data to optimise the customer journey from searching to booking?

To think creatively about the question, we must think a little bit about what travel data actually is.

Travel data is valuable because it is uniquely predictive: When the consumer buys an airline ticket, it’s likely he will soon purchase a hotel room, a hire car and perhaps tickets to local shows and attractions.

Because it is uniquely predictive, it is also rich. Rich in the content of the consumer data collected; rich in the access points to the consumer on the purchase path; rich also, in the value of the total spends made during the course of a journey.

Finally, travel data is also uniquely personal – no two trips are the same, no two travelers have the same preferences. The most effective offers are the ones that are tailored to meet the needs of the individual traveler when and how he expresses them, on the platform in which he prefers to be connected.

Based on the richness of travel data and its predictive and highly personal nature, there are a multiplicity of opportunities for airlines, hotels and others to capture revenue throughout the cycle. 

Pete Kelly, Adara

Based on the richness of travel data and its predictive and highly personal nature, there are a multiplicity of opportunities for airlines, hotels and others to capture revenue throughout the cycle. 

A key is to measure, track, and monitor a travellers’ preferences and booking patterns across the entire path to conversion. 

This takes intensive research, of course, and the ability to stay connected with the traveller across multiple platforms and touch points.

Doing so, allows one to identify and quantify audience and marketing drivers that impact on the funnel shape en route to conversion.

With that information gathered, a next step is predicting consumers’ intention, readiness, preferences and next most likely actions.

On that basis, we are ready to adapt and optimise recommendations to navigate consumers on paths to conversion – which results in more compelling offers, effective cross-channel communications, and the wise management of inventory and prices. This is our specialisation at ADARA – where we bring more than 80 data partnerships with the world’s leading travel brands into play, for online marketers.

The ultimate endpoint is a holistic picture of traveller’s preferences, wishes and intentions  –  being able to target consumers based on the amount they are likely to spend when booking travel; where they are likely to spend it; and when in the future they are likely to spend more.

The most advanced marketers can personalise the right offer to the right recipient via the right platform, and increasingly, across platforms -- including and especially, mobile. 

That, ultimately, is the rosetta stone for optimising sales revenue.

Let’s consider a concrete example.

Is a banker from London, who is travelling from Frankfurt to Hong Kong and recently bought expensive jewelry online, more or less likely to pay to upgrade his seat on the flight, than a high tech engineer from Berlin who earns the same amount of money and is flying on the same flight?

The answer is not straightforward, and it’s not intuitive.

The banker may be willing to pay for prestige, and legroom.

The technology genius may be willing to upgrade for extra overhead space, and peace and quiet to think about the next big change to his algorithm.

You cannot know which one is more likely than the other to upgrade.

But you can know how a particular traveler is likely to want to transact online, his loyalty status, and the best way to interact with him to make a sale.

And if you know something about his willingness to upgrade on his flight, you might also learn something about the likelihood he will pay for a hotel upgrade, or a spa treatment upon arrival. 

It all begins – with the data.