The Context
EasyJet was a flight company
becoming a holiday brand.
In 2017, EasyJet Holidays was making a significant push to establish itself as a credible holiday brand — not just a flight booking service with a hotel bolt-on. The challenge was fundamental: EasyJet's customers knew how to search for flights. They had no established behaviour around searching for holidays.
Flights are searched with precision — specific dates, specific routes. Holidays are discovered with ambiguity — a vague sense of wanting sun, or culture, or adventure, without necessarily knowing where or when. The existing search-and-filter paradigm wasn't designed for this kind of open-ended exploration.
The Insight
People don't know what holiday they want. They know how they want to feel. Design for the feeling, and the destination follows.
— Insight from customer research that shaped the experience
The insight that unlocked the design was simple but significant: holiday choice is primarily emotional, not rational. Customers weren't starting with "I want to go to Malaga" — they were starting with "I need a break," "I want adventure," or "I want somewhere the kids will love."
This meant the discovery experience needed to work backwards from feeling — using progressive questions to narrow from emotional intent to concrete preferences to specific destination recommendations. It was, in effect, a conversation. Just one designed before conversational UI existed as a concept.
The Design
A conversation in
seven questions.
The discovery experience was structured as a dynamic, progressive question flow — each answer informed what came next, narrowing the possibility space without ever feeling like a filter. The experience felt like talking to a knowledgeable friend, not filling in a form.
Why it mattered
Conversational UX before
chatbots existed.
In 2017, there were no AI holiday recommendation engines. ChatGPT was five years away. The conversational discovery pattern we designed was solving — through careful interaction design and progressive disclosure — exactly the same problem that AI assistants solve today through natural language.
The constraint was the insight. Without access to AI, we had to design the conversation manually — thinking carefully about question sequence, answer framing, and how each response should influence what came next. That rigour produced an experience that felt genuinely intelligent, not because it was, but because the design was doing the work.
Looking at it now, it was an early example of what the industry now calls preference-led or intent-based discovery. We were building it with HTML, JavaScript, and careful UX thinking.
Outcomes
What it achieved.
Still live today
Not archived. Not rebuilt.
Still there.
The experience we designed and built in 2017 didn't just win an award and get archived. It didn't get rebuilt two years later. It’s still live on easyjet.com right now — the original Inspire Me tool, with the same question architecture, the same interaction model, and the same copy we wrote at Valtech nearly nine years ago.
EasyJet has since built a second discovery tool — the Holiday Inspiration Quiz — but they kept the original too. Both are live simultaneously. That’s not a company that forgot to retire something. That’s a company that looked at what we built and decided it was still good enough to keep serving customers in 2026.
Add desktop screenshot when back from holiday
The original Inspire Me tool we designed and built at Valtech in 2017 is still live at easyjet.com/en/inspireme today. The interface, the question architecture, the copy — “I want to... fly from... leave on... stick to a budget... choose my travel style...” — is our work. Unchanged in its fundamental design. It has been serving EasyJet customers continuously for nearly nine years, across hundreds of millions of sessions, on one of Europe’s most visited travel websites.
This kind of longevity is exceptionally rare in digital product design. Most experiences are rebuilt within two or three years. The fact that this one hasn’t been replaced — only supplemented by the newer Holiday Inspiration Quiz — is the strongest possible proof that the underlying design thinking was right.
View the original live experience ↗Reflection
What constraints
teach you.
This project taught me something I've carried through every piece of work since: constraints force clarity. Without AI to do the heavy lifting, we had to think deeply about what questions actually matter, in what order, and why. That thinking produced a better experience than many AI-powered recommendation systems I've seen since.
The award was gratifying, but the more lasting value was the methodology it established — understanding that discovery experiences should start with emotional intent, not categorical filters. That insight applies equally to an EasyJet holiday, a Netflix recommendation, or an energy tariff comparison.
I'm also struck, looking back, by how directly it maps to what I now do with AI agents. In both cases the core design challenge is the same: how do you structure a conversation so that by the end of it, the system knows enough to give you something genuinely useful?