Why travel websites?
Low engagement.
Lack of relevance.
Lots of data.
You’re booking your next holiday or travel adventure, and the itinerary is coming together. You’re excited, right? Until you hit the checkout page. Suddenly, all that excitement? Gone. Generic, boring, lifeless. “your purchase is complete”. These words should add magic, not kill it.
These companies know a lot about you, where, when, why your traveling. But Personalisation? Practically nonexistent. At least, until now.
Problem Area
We noticed personalisation in travel stops the moment you hit ‘book now’—but that’s where it should start
Click to expand
Defining the Gap in Post-Purchase Personalisation
While most travel platforms pour their energy into personalising search and booking, the moment a trip is confirmed, the experience flattens. Across Expedia, Booking.com and even newer AI tools, personalisation stops at the transaction. Everything that follows — confirmation screens, checkout details, pre-trip nudges — becomes generic, despite companies already holding rich contextual data about the traveller. This disconnect became the foundation of the problem space I explored.
For this sprint, we weren’t aiming to reimagine the entire booking journey. Instead, I focused specifically on the post-purchase phase—moments like the checkout screen, confirmation page, and pre-trip reminders.
Brainstorm for AI-Driven Personalisation areas of possible integration
To ground the problem space, I mapped out all the touchpoints where AI could add contextual value using data platforms already collect — from marketing messages to after-purchase support. The diagram below captures that landscape. From this broader field, I deliberately narrowed the scope to a single, high-impact moment: the post-checkout trip confirmation page. It’s the first point where excitement peaks, personal context is richest, and current platforms still default to generic, boilerplate content.
Research
With no time for user interviews, we flipped the script and used existing data as our playground
Click to expand
Research Overview:
Understanding what the landscape is like (data, user journey, and expectations).
Because this sprint was about rapid AI exploration, there wasn’t time for extensive primary research. Instead, I leaned into desk research and focused on one question: what data do travel companies already have, and why isn’t it being used to personalise the moments after booking?
To map this out, I sketched the Travel Data Ecosystem — a visual breakdown of the user information already sitting inside most booking platforms: identity data, trip context, behavioural signals, partner integrations, preferences, and inferred insights.
Travel Data Ecosystem diagram
From mapping the Travel Data Ecosystem and reviewing how major platforms handle post-purchase interactions, a set of clear insights emerged:
Research Insights
- There’s more than enough data already.
So the issue isn’t data scarcity, it’s dormant data. Travel companies already hold huge rich contextual information, but almost none of it gets activated after purchase. (It’s used extensively in recommendation engines pre-purchase ect) - Personalisation follows the transaction, not the experience arc.
Data is heavily used to optimise search, sort, and pricing, but barely used to shape the emotional arc of the journey (anticipation, reassurance, preparation) once the booking is confirmed. - Post-purchase touchpoints are treated as admin, not experience moments.
Confirmation screens, emails, and reminders are designed for verification, not value
Existing Solutuons
Everyone’s personalising the search—nobody’s personalising the journey after you’ve booked
Click to expand
Competitor breakdown
To position this concept, I analysed how major travel platforms currently use data and AI.
.svg.png){kind=logo}
