Turn online reviews into operational intelligence
Import reviews from Google, TripAdvisor, and delivery platforms. AI analyses every review for sentiment and compliance risks, then correlates findings with your shift data to surface patterns you can act on.
Reviews tell you what customers won't say to your face
But only if you can find them, analyse them, and connect them to what's happening in your operation
Reviews scattered across platforms
Google review monitoring, TripAdvisor review tracking, Deliveroo - your reviews are spread across half a dozen platforms. Without multi-platform review monitoring, nobody has time to check them all, so problems mentioned in reviews go unnoticed.
No link to compliance
A customer mentions an allergic reaction in a Google review. Your compliance team doesn't see it because reviews and food safety live in separate systems.
Can't see who was working
A pattern of bad reviews on Tuesday evenings means nothing unless you can see which team was on shift. Without that connection, reviews are just noise.
Reactive, not proactive
By the time you spot a trend in reviews manually, it's been weeks. Without review trend analysis, hygiene complaints pile up while you're reading five-star reviews elsewhere.
Reputation management that connects to your compliance workflow
Paddl is the only platform that bridges online reviews directly into food safety compliance. When a review mentions an allergen reaction, your compliance team knows immediately - not weeks later.
Multi-Platform Ingestion
Connect Google Business Profile, TripAdvisor, and delivery platforms for reputation management across hospitality. Reviews from every source flow into one unified feed, normalised and deduplicated automatically.
AI Sentiment Analysis
Every review is analysed by AI to extract sentiment, themes (food quality, service, hygiene, wait time), and a numerical sentiment score for trending over time.
Compliance Flagging
Mentions of allergic reactions or food-related illness trigger immediate alerts to managers. Hygiene concerns are flagged as advisories. Reviews feed directly into your compliance workflow.
Shift Pattern Correlation
Reviews are automatically matched to which team was on shift during the customer's estimated visit. See which day/time combinations correlate with lower ratings.
Theme Trend Charts
Customer feedback analytics that tracks how themes like food quality, service, and hygiene trend over a rolling 30-day window. Spot improvements or deterioration before they become patterns.
Shift Pattern Heatmap
A visual heatmap shows average ratings by day and time slot across each location. Instantly identify your weakest shifts and strongest performers.
Complaint Cross-Referencing
Reviews are automatically linked to any complaints logged around the same time and location. See the full picture of a customer incident in one place.
Legal & Audit Integration
Reviews are included in legal advice context and audit pack exports. When an incident escalates, every relevant review is already part of your evidence pack.
What our customers achieve
Real improvements from hospitality businesses using Paddl for reputation intelligence
How teams use reputation intelligence
Allergen Incident Detection
A customer mentions an allergic reaction in a Google review. Paddl flags it immediately and notifies the owner, linking it to the relevant shift and any related complaints.
Tuesday Evening Problem
The heatmap reveals that Tuesday evenings at one location consistently get lower ratings. Cross-referencing with shift data shows a pattern the manager can act on.
Hygiene Trend Monitoring
A gradual increase in reviews mentioning cleanliness is caught by theme trend analysis weeks before it would have been spotted manually, giving time to address it before the next EHO visit.
Multi-Location Comparison
Compare average ratings, sentiment, and theme breakdowns across all your locations. Identify which sites are improving and which need attention.
Google Review Monitoring
Connect your Google Business Profile and every new review flows into Paddl automatically. AI categorises each review by theme, detects compliance-relevant mentions like food safety or hygiene concerns, and alerts your team when urgent issues surface. No more manually checking your Google listing every morning.
TripAdvisor Sentiment Tracking
TripAdvisor reviews are imported and analysed for sentiment trends over time. Track whether your food quality, service speed, and cleanliness scores are improving or declining on a rolling 30-day window. Spot deterioration early enough to address it before your overall rating drops.
Review Response Suggestions
AI drafts response suggestions for negative reviews based on the specific themes mentioned. If a reviewer complains about wait times, the suggested response acknowledges the issue and references the operational changes you have made. You review and personalise before posting, ensuring every response feels genuine.
Multi-Platform Dashboard
See all your reviews from Google, TripAdvisor, and delivery platforms in a single unified feed. Filter by platform, rating, date, location, or compliance flag. Compare your performance across platforms side by side to understand where your reputation is strongest and where it needs work.
Frequently asked questions
Which review platforms does Paddl integrate with?
Paddl currently integrates with TripAdvisor, with Google Business Profile and Deliveroo coming soon. All reviews are normalised to a consistent format regardless of source platform, with ratings converted to a 1-5 scale.
How does Paddl detect compliance issues in reviews?
Every review is analysed by AI to detect mentions of allergen reactions, food-related illness, hygiene concerns, and other compliance-relevant topics. Urgent flags (allergen reactions, illness) trigger immediate push notifications to business owners. Advisory flags (general hygiene concerns) are surfaced in the dashboard.
Can I see which staff were on shift when a bad review was written?
Yes. Paddl estimates the customer's visit time from the review publication date and matches it against staff check-in records. The review detail page shows which team members were on duty, along with any complaints from the same time period.
Are historical reviews imported?
When you connect a platform, Paddl imports up to 90 days of historical reviews for context. However, only reviews published after you connect the platform are eligible for AI analysis and shift correlation. Historical reviews are clearly labelled as "imported for context".
How do reviews appear in legal and audit contexts?
Compliance-flagged reviews are automatically included in the legal advice AI context and legal export ZIP. Reviews can also be included as a section in your audit pack, providing a complete picture of your business's reputation alongside compliance records.
How do online reviews affect food hygiene ratings?
While EHO inspectors do not formally use online reviews to determine your food hygiene rating, they are increasingly aware of them. A pattern of reviews mentioning hygiene concerns, allergic reactions, or illness can trigger an earlier-than-scheduled inspection. More importantly, reviews often reveal the same operational issues that lose points during inspections, such as cleanliness, temperature control, and allergen management. Monitoring reviews proactively helps you fix these issues before your next visit.
Should I respond to negative reviews?
Yes. Responding to negative reviews shows potential customers and inspectors that you take feedback seriously. A good response acknowledges the concern, avoids being defensive, and explains what you have done to address the issue. However, never admit liability for food safety incidents in a public response. Paddl AI generates suggested responses that strike the right tone and reference operational improvements without creating legal exposure.
Can reviews help me identify staff training needs?
Absolutely. Paddl correlates reviews with shift data to show which teams or time slots consistently receive lower ratings. If Tuesday evening reviews frequently mention slow service, you can look at the staffing levels and team composition for that shift. This turns subjective customer feedback into specific, actionable training and scheduling decisions.
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