Luismi Bello --:-- · MAD
← Work / 02 / 04 Case study / LATAM Airlines · Concierge

Travel Planner — a reason to come back.

Concierge could hold a conversation, but not your trip. The Travel Planner gives it a memory: save any flight, stay or place — by tapping a card or simply asking — and a scattered trip assembles itself into one plan worth returning to.

Role
Senior Product Designer, AI
Team
Product, AI, Eng, Research
Year
2025–2026 · in production
Methods
Service design · Agentic UX · Research
Bet
+50% 7-day return rate to Concierge
Concierge chat proposing Caribbean destinations as saveable cards
In the chatConcierge recommends flights, stays & places as cards
A saved trip plan named Caribe 2026, with destinations and flights grouped together
In your planOne tap saves them — grouped, dated, yours
01 — Problem

A conversation users never came back to.

ContextConcierge · retention

Planning a trip is complex, asynchronous and scattered: notes in one app, tickets in another, a hotel quote screenshotted in a third. People arrive at the gate already overwhelmed.

Concierge answered questions beautifully — but the moment you closed the chat, everything it found was gone. There was no place to keep things, and so no reason to return. The 7-day return rate sat below target, and the assistant had no unique value to pull anyone back.

A scan of indirect competitors like Kayak.ai exposed the opening: deliver Concierge's promise in one place — turning a smart conversation into a trip you actually own.

7-day return rate
Belowtarget
No reason to come back
Differentiator
None
No unique value vs. chat alone
The bet
+50%
7-day return rate · hypothesis

Give the conversation a memory, and you give the user a reason to return.

02 — Concept

A playlist, for a trip.

The save loopUI + agentic AI

The mental model came from music: saving a recommendation to a trip should feel exactly like adding a song to a playlist. Every flight, hotel, destination and activity Concierge surfaces is a saveable card — bookmark it into a plan and move on.

There are two ways in, and they land in the same place. Tap the save control on a card, or just say it — "guarda ese hotel en mi plan." Concierge's agentic layer performs the save either way, so structured UI and natural language stop competing and start cooperating.

Concierge proposing round-trip flights to Punta Cana as a saveable card
FlightsRoutes, cabins & fares — in cash or miles
Concierge recommending a Caribbean activity, Isla Saona, as a saveable card
ActivitiesPlaces to go, reasoned from preferences
Concierge recommending hotels in Cancún, powered by Booking.com, as saveable cards
StaysHotels, scored — powered by Booking.com

Save it like a song. Tap the card — or just ask.

Even a chat answer is worth keeping

Not everything useful is a card. A great reply — an itinerary, a comparison, a tip — can be pinned straight from the conversation into the plan's highlighted messages, so the reasoning behind a decision travels with it.

A Concierge chat reply with a Save to plan action alongside continue conversation
Guardar en PlanesPin any answer to the plan, right from the chat
03 — The object

Inside a trip plan.

StructurePlan & states

A plan is a lightweight container — a title, optional dates, and a stream of saved cards grouped by what they are. Whatever Concierge surfaces in chat can be promoted into it with one tap or one sentence, then read back as a single, ordered itinerary.

  • 01Title — editable, generated from the first prompt
  • 02Dates — optional; the plan reads fine with or without them
  • 03Grouped itemsdestinations · flights · activities · stays
  • 04Highlighted messages — chat answers worth keeping
  • 05One save path — card tap or prompt, both run the same agentic action
The full Caribe 2026 trip plan, grouping a destination, flight, activity and hotel with highlighted messages
One trip, fully groupedDestinations · flights · activities · stays · highlights
The plans list showing Caribe 2026, Japón soñado en primavera and Navidades en Brasil
All your tripsSwitch plans, or start a new one

Designed for the edges, not just the happy path

A planner is only trustworthy if it behaves when the data doesn't. I designed the full state matrix alongside the ideal flow — a warm first-run, an empty plan that still tells you what to do next, graceful load failures, and skeleton loaders so nothing ever flashes blank.

First-run empty state inviting the user to create their first plan
First run"Create your first plan" — one clear next step
An empty plan with per-section prompts guiding the user to add destinations and flights
Empty planEach section nudges the next save
A load-error state offering a retry
Load errorHonest message, one-tap retry
04 — Validation

Does it bring them back?

ResearchModerated · qualitative

Moderated usability testing pointed twice at the same need: users asked for a drag-and-drop calendar and a way to save and share quotes. Both were really one request — give me a container I can come back to. That request shaped the highlighted-messages pattern and the grouped plan.

After two iteration rounds — mostly sharper feedback states and clearer ownership cues — the major usability issues were resolved. Attitudes were positive, and participants named the planning hub itself as the reason they'd return.

Retention hypothesis
+50%
7-day return rate to Concierge
Usability issues resolved
8 / 9
After two iterations
Status
Live
Shipped to production · May ’26
"I want to come back and keep editing my plan." — Participant 03 · moderated test

A smart answer is a moment. A plan is a reason to return.

© 2026 — Luis Miguel Bello García Senior Product Designer, AI contact@luismi.design
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