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Meet your Paris travelers.Every one of them.

A concept modeled on a 464-experience Paris catalogue and the kinds of signals travelers leave behind. Test a launch, bundle or wet Saturday—and see how the whole room could answer before committing.

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Return on decision.

Three illustrative questions from a Paris season. All 500 simulated personas answer locally, showing how evidence and commercial consequence can stay attached to a verdict.

500 personas waiting · pick a decisionlocal product preview

Left to right: romantics · kids · art · budget · secret Paris · food · VIP · one free evening

Ten customers in a room.
Or all of them.

The focus group sample

10customers in the room
Weeksto an answer
Onequestion, then start over

Liquid Personas sample

500customers in the room
Secondsto an answer
Everyquestion, all month

Now ask everywhere.

The engine is not tied to a city or language. Paris is one tab.

Example cities: Paris, Rome, Barcelona, Amsterdam, London, Palma, Athens, Lisbon, Dubai, New York, Cancún, Tenerife, Marrakech, Crete, Prague, Bangkok, Reykjavík.

Your data.
Our intelligence.

What goes in

  • Bookings & orders
  • Paris catalogue
  • Reviews & ratings
  • CRM & loyalty
  • Support tickets
  • Site & app behaviour
  • Weather & events
Liquid PersonasBrand brain · 500 personas

What comes out

  • Travelers who answer back
  • The objection, before launch
  • 500 answers · one verdict
  • What to change, ranked
  • A line back to the review

The control panel

You decide what the room is allowed to know before it answers.

Sources
Which datasets a run may read.
catalogue + reviews
Recency
How far back a review still counts.
last 18 months
Verified only
Drop reviews with no booking behind them.
on
Market mix
Weighted to the real booking split.
8 markets
Population
500 today, 5,000 when it matters.
500
Citations
No source, no answer.
always on

Every run writes an audit trail: what was read, which sentence drew on which review, and what changed the verdict.

Put your next decision
in the room.

Talk to Copernic hello@copernic.ai