HospitalityQuick start
Guest review analysis and reply drafts
- The problem
- Hundreds of reviews hide the issues guests keep repeating.
- How AI helps
- Reviews are grouped by theme, trends are summarised weekly and replies are drafted in the property tone.
- Start with
- Language model, review exports.
- Guardrails
- Staff approve every reply before it is posted.
Full details
Example in practice
Two hundred reviews from three platforms are grouped into themes. The weekly summary shows that breakfast waiting time is the top complaint, and reply drafts are ready in the property tone.
How it works
- Export reviews from each platform.
- Group by theme and sentiment using a language model.
- Draft replies from the property tone guide.
- Staff approve replies and share the weekly theme report with department heads.
Data you need
Review exports and the property tone and policy guide.
Measure success
- Review rating trend
- Reply time
- Repeat complaints by theme
- Share of reviews answered
Indicative rollout
Days 1-3: pick one process and collect 20-30 real samples. Week 1: test with an approved AI assistant and compare with the manual result. Week 2: write the checklist and review step, then use it on live work. Timing is indicative and depends on your data and systems.
Data handling
Use approved tools only, keep personal and confidential data protected as required by law (for example the Digital Personal Data Protection Act, 2023 in India), and keep a person responsible for every decision that affects people.