The Context
Searching for flights
is nothing like
discovering a holiday.
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.
Outcomes
What it achieved.
A design legacy
Still live.
Nine years later.
The original Inspire Me tool — concept, naming, interaction model and all — is still live on easyjet.com today. Unchanged in its fundamental design. Serving customers nearly nine years after we built it.
But in 2024, EasyJet went further. They took the original concept and built a second product from it — the Holiday Inspiration Quiz. Not a replacement. A direct lift and evolution, running alongside the original simultaneously. Two live products on one of Europe's most visited travel websites, both traceable directly to a single UX concept originated in 2017.
The interface copy — "I want to... fly from... leave on... stick to a budget... choose my travel style..." — is the original work from Valtech. The Inspire Me name was conceived as part of the UX concept.
View the original
Built in 2024, the Holiday Inspiration Quiz is a direct reproduction of the original Inspire Me concept — same question-led discovery architecture, same preference-to-destination logic. That's not a company that forgot to retire something old — that's a company that built it twice because the idea was right.
View the evolutionReflection
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?