Individual reviews become a picture of the guest experience
AI groups similar comments and shows how they change over time, instead of leaving the team with a long list of unrelated reviews.
Reviews from several platforms
Guests praise the staff and breakfasts, but some weekend reviews mention noise from events.
Topics, trends and matters requiring action
The report separates consistent strengths from growing issues and highlights reviews still awaiting a response.
- topic ranking with examples
- changes in ratings and issues over time
- list of reviews requiring action
A live report instead of reading every review manually
The module organises review content and leads back to the original comments. It does not reduce the guest experience to an average rating alone.
Groups topics
It brings together similar praise, complaints and suggestions regardless of the wording used by the guest.
Shows trends
It compares ratings and topic frequency across platforms and periods.
Flags missed responses
It creates a list of unanswered reviews and flags matters requiring attention.
How is the review analysis created?
Collecting reviews
The central Reputation Panel provides reviews, ratings, platforms, dates and response statuses.
Identifying topics
AI groups comments by areas of the guest experience and sentiment.
Comparing periods
The system shows which strengths and issues are growing, declining or remaining stable.
Passing items on for action
The report leads to specific reviews and feeds the team’s work queue.
Every finding leads to the original review
Topics, trends and ratings remain verifiable. A team interview can explain a change, but it does not replace content published by the guest.
What does AI use?
- review content and rating
- platform and publication date
- response status and history
- optional hotel operational context
What does the team receive?
- topic ranking and example reviews
- trends in ratings and issues over time
- list of reviews requiring a response
Analysis supports interpretation but does not determine causes
A recurring topic may have several causes. The team checks the operational context before drawing conclusions or changing a process.
The user selects the properties, platforms and analysis period, checks the original reviews and decides which findings require action.
The module does not respond to guests, remove reviews, change operational data or present a suspected cause as a confirmed fact.
Reputation described through specific topics
The team knows which parts of the stay guests value most often.
Recurring complaints and changes in them are visible before the next period summary.
Unanswered reviews can be sent straight to an organised queue.
The central Reputation Panel provides a shared set of reviews
The AI platform analyses data from connected platforms. A context interview can add the team’s knowledge to the interpretation.
Related process elements
Frequently asked questions
Does the analysis cover several platforms at once?
Yes. Reviews can be compared together or separately for each source.
Does AI show specific examples?
Yes. Each important topic and trend leads to the original reviews.
Does the module respond to reviews?
No. It analyses them and passes them into the next process; separate modules prepare responses.
Can periods be compared?
Yes. The report can show changes between selected weeks, months or seasons.