Last week’s Skift Forum Europe covered two top trends for the travel industry: personalization and artificial intelligence. While a lot of companies want to provide “personalization”, most struggle to execute a truly personalized strategy. And when looking for an AI solution to turn data into real relevancy, how do companies cut through the hype? Thomas Cook’s Group Head of CRM, Christian Lang, Skift Editor Jeremy Kressman, and Tinyclues VP Product Marketing François Laxalt, discussed how AI has actually been applied to the travel leader’s campaign strategy in order to embrace personalization at scale.
But for all the talk about how brands are leveraging data to personalize experiences for customers, I’m often surprised at how rarely I receive relevant offers from big travel companies.”
—Brian Sumers, Senior Aviation Business Editor
The panel started with a discussion on why relevancy is accelerating personalization. Laxalt shared his experience of receiving irrelevant communications: “Too often, I receive emails with my first name, that include offers to a destination where I’ve already traveled. It’s personalized, but irrelevant as I rarely go to the same destination twice”. Thomas Cook’s Lang added that, “It’s a real problem for travel companies as research shows that 70% of travelers don’t want to go to the same destination”.
With potential bookers having so many options at their fingertips, ensuring you’re offering a relevant experience is paramount to not losing customers to the competition, and in increasing repeat purchases.
Why is Campaign Relevancy Particularly Hard for Travel & Hospitality?
- Travel offers are complex. Offers often combine booking windows, classes (e.g. luxury vs. economy), star ratings, specific destinations and more!
- Catalogs are full of niche destinations. Promoting these specific, yet strategic, destinations to the whole base could mean hurting customer experience. Not promoting them means you’re missing out on additional campaign revenue.
- Customers are time-sensitive. How do you know which customers are “early bookers”, and which customers are last-minute bookers?
- Interdepartmental demands require a high level of agility. Requests from yield, revenue, and product management teams require a flexible campaign strategy.
Travel Marketing Isn’t Customer Centric
When only 70% of vacationers return to the same destination every year, can previous travel history really predict future travel behavior? Concentrating on past purchase means that you’re missing out on all those who booked a trip to Goa last year, but have decided to fly to Alaska this year. It also means you’re sending irrelevant campaigns on destinations that people are not interested in purchasing – hurting customer engagement.
On top of that, you’re not leveraging all the data you have spent so much time and so many resources acquiring.
How to Win at Travel Marketing Relevancy
Travel thought leaders Skift, recently published a report on the current state of martech solutions in the travel industry. The trend in travel is toward greater martech spend, increased adoption, and positive business outcomes. Martech needs to create only the most relevant and meaningful experiences. The report dives into use-cases and the artificial intelligence equation. David Bessis is interviewed in the report, he discusses how important it is to layer intelligence onto the marketing stack, making marketing decisions more powerful because they’re emerging from deeper links between data types and deeper insights based on the analysis of information that was previously siloed or unidentified.
At Skift Europe, Thomas Cook spoke on stage on their results using deep learning-leveraged martech to optimize the targeting and planning of their omnichannel campaigns. A/B tests in the UK comparing Thomas Cook’s advanced data scientist-led targeting methods to Splio revealed better omnichannel revenue:
- 118% in email revenue
- 26% in Facebook ad revenue per euro spent
Splio allows you to promote any destination, hotel, or offer within any booking window to an audience made up of actual future buyers. The solution finds the best audience for each campaign, no matter where they have traveled. Marketers are now able to leverage all their data points with unique deep learning technology to reach customers they would have never targeted before.