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Hospitality - Case study

Hotel group response time on online reviews dropped from 6 days to under 12 hours

The client

A Thai-owned hotel group with seven boutique properties across the country.

An automated flow that reads every incoming review across booking platforms, drafts a personalized response in the property's voice, and queues it for the GM to approve.

The client

A Thai-owned hotel group with seven boutique properties spread across Bangkok, Chiang Mai, and the south. Each general manager was responsible for replying to guest reviews on Booking.com, Agoda, Google, and Tripadvisor. Most of the GMs were drowning in operational work and review responses kept slipping.

The problem

Reviews were coming in across four platforms per property, around two hundred a month group-wide. Industry research is clear: timely thoughtful responses lift booking conversion. The hotel group knew this. In practice, responses were taking five to seven days on average and were often a few generic templates rotated through. Negative reviews sat unanswered the longest.

The approach

The build pulled every new review across all platforms into a single n8n flow. Each review went through an LLM with a custom prompt for that property: tone, common reference points, the property’s standard apology and resolution patterns, and a policy on what to escalate. The output was a draft response, written in the property’s voice, addressing the specific things the guest mentioned.

The GM saw the draft inside a per-property review queue. Approve, edit, escalate, or reject took thirty seconds per review. Most got approved with no changes. Negative reviews got escalated and the GM responded personally, but with the draft as a starting point so they were not staring at a blank box.

The result

Median response time across the group dropped from around six days to under twelve hours. Booking conversion lifted measurably on the properties where response speed had been worst. The general managers stopped feeling guilty about review pile-up, which was its own quiet morale lift.

Your turn

Every build started as a specific problem.

Whichever one is costing your team the most time right now is usually the right place to begin. Half an hour together, a written read inside a business day, and an honest opinion on whether automation is even the right answer.

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