What review monitoring does
Review monitoring brings your customer reviews into Paddl, reads each one with AI for sentiment and recurring themes, flags anything that matters for compliance, and links a review back to the shift it relates to. You get the picture in one place instead of checking each platform separately, and you can act on a trend before it dents your reputation.
It lives under Customer > Reviews.
Connecting your platforms
Click Connect Platforms (or Review Platforms in settings) to set up your sources:
TripAdvisor connects now: choose the location and enter its TripAdvisor Location ID
Just Eat, Uber Eats, and G2 reviews can be brought in for context
Google Business Profile and Deliveroo are coming soon and will appear here once available
Once connected, Paddl imports recent reviews automatically. Use Sync now to pull the latest at any time, or Disconnect to remove a source.
Reading the dashboard
The Reviews page shows your average rating, recent volume, and the share of positive sentiment, with an AI summary of what customers keep raising. Filter the feed by platform or by sentiment to focus in. If a batch has not been analysed yet, click Analyse reviews; for an updated written summary, click Generate insights.
What the AI adds to each review
Open a review to see:
Sentiment and themes such as food quality, service, hygiene, value, or wait time
Key phrases pulled from the text, and a short summary
On Shift, the staff and visitors who were working around the estimated visit time, so you have context for what the review describes
Related complaints logged near the same time, linked across so the full story is together
Compliance flags
Some reviews matter beyond reputation. Paddl raises a banner when it spots them:
Flag | What triggers it |
|---|---|
Urgent | A mention of an allergic reaction or food-related illness, which needs immediate attention |
Advisory | General hygiene or cleanliness concerns worth looking into |
Insights and trends
The Insights page goes deeper: a heatmap of ratings by day and time, theme trends over the last 30 days, and a comparison across your locations. It is where a pattern, a dip every Friday evening, or one site pulling the average down, becomes obvious enough to act on.