Search and booking behavior, demographics, psychographics—the list can go on and on when it comes to how much data we collect and use in the travel industry. The advancements in how we understand and leverage that data, especially with the use of Machine Learning, can drastically change the future of the travel industry—and the success of our advertising campaign efforts.
To understand how Machine Learning can help the travel industry, we sat down with Carl Livadas, Sojern’s VP of Engineering and Data Science:
The advances in technology, with cloud computing and so on, have simplified the process of collecting and storing date. The industry, in general, has been able to focus not on collecting the data and processing it, but focusing and applying it in their domains.
So in marketing for example, companies don’t need to spend resources on building the infrastructure—that infrastructure is readily available to them. They just need to figure out how to leverage Machine Learning to exploit and make use of that data.
Even a few folks in engineering or data science can really deliver on a product, because they don’t have to deal with infrastructure work. They can focus on the Machine Learning and applying that data set.
Focusing on the Applications and Outcomes of Machine Learning
The power in Machine Learning comes not from the “machine” but from the “learning”. This is never more apparent than when applied to real-time advertising. With the key learnings from Machine Learning, advertisers have the ability to serve personalized ads to in-market travelers as soon as they display any intent signal.
How Machine Learning Works with Real-Time Advertising
Sojern’s SVP of Enterprise Solutions, Stephen Taylor, and VP of Engineering and Data Science, Carl Livadas, explain:
[Sojern] What does machine learning for marketing look like?
[Livadas] Machine learning in the marketing context involves processing the vast amounts of data that we have, distilling it into models of user behavior, if you may, and then predicting that user behavior for into the future.
[Sojern] How can marketers use machine learning?
[Livadas] We can identify which advertisements we want to show to the users in order to maximize their engagement with those ads and return the value back to our advertisers. We can use Machine Learning to predict the next step within that trip planning process that a user might have.
[Sojern] How can marketers use real-time data with machine learning?
[Taylor] With the power of real-time data, with this intent data, not only do we now know who I should be targeting, but you also know what message I should be using and that with dynamic creative allows personalized messaging.
[Sojern] How does this translate to ads?
[Taylor] I can put the right message in front of them at exactly the right time, with the right creative, with the right price that is relevant to their particular family room or business class seat. All of these things come together to allow real-time messaging that are highly personalized.
Sojern uses Machine Learning to help harnesses the power of our audience network in order to drive highly targeted and personalized ads.