Auto-Tag Reviews by Topic
Knowing you received 40 negative reviews last month tells you far less than knowing 28 of them mentioned wait times and 9 mentioned a specific staff member — that's the difference between a number and an action item. Typani's auto-tag automation categorizes every incoming review by topic the moment it posts so your data is always organized and ready to surface patterns.
What Auto-Tagging Reveals in Your Review Data
Tagging every review by topic transforms your inbox into a structured dataset:
- ✓Topic categories — service, pricing, quality, wait times, cleanliness, staff, and more
- ✓Custom tags — define your own categories specific to your industry or operations
- ✓Sentiment by tag — which topics skew positive vs negative in your reviews
- ✓Tag volume trending — which topics are increasing or decreasing in frequency
- ✓Cross-location tag comparison — is the wait time problem specific to one location?
- ✓Export by tag — filter your review database by topic for deep analysis
Real Examples — See What Typani Generates
Paste any review, get a reply that sounds like a real business owner — not a corporate template.
“The wait was over 30 minutes and nobody mentioned it until I asked. The food was good once it arrived, but the timing killed the experience.”
“Good food with a 30-minute wait that nobody acknowledged — the timing shouldn't take away from a meal that was otherwise worth it. We're working on communicating delays proactively and this is exactly the feedback that drives it. Thank you for the honest breakdown.”
“Jake behind the counter is the reason I keep coming back. Remembers my order, always has a good attitude, makes the whole visit better.”
“Jake is the kind of person who makes a routine stop feel like something worth coming back to. We'll make sure he hears this — and thank you for taking the time to say so specifically.”
Why Tagged Review Data Beats a Review Inbox
An unstructured inbox of reviews is a pile of anecdotes. A tagged review database is structured customer feedback that operations teams can actually use. When you can filter by 'wait time' and see 28 complaints across 90 days, you have the data to justify a staffing change, a process adjustment, or a technology investment — instead of a gut feeling that 'people keep mentioning the wait.'
Typani's auto-tag runs on every incoming review without any manual intervention. Tags are applied immediately using content analysis trained on review language across industries. Your team sees tagged, sortable, filterable reviews from day one — not after weeks of manual categorization.
Start Responding Free
Frequently Asked Questions
Everything owners ask before they start using Typani.
Can I define my own custom tags?
+
Yes. Typani includes a default tag taxonomy that covers the most common review topics, and you can add custom tags specific to your business — 'new menu item feedback', 'parking', 'renovation impact', or whatever is relevant to your operations.
Can a single review get multiple tags?
+
Yes. A review that mentions both wait times and staff attitude gets tagged with both categories. Multi-tag reviews appear in any filter that includes either tag.
How accurate is the auto-tagging?
+
Typani's content analysis is trained on millions of review examples across industries. Accuracy on standard categories typically exceeds 90%. You can always manually adjust or override any tag, and those corrections improve the model for your account over time.
Can I export tagged review data?
+
Yes — filtered by any tag, date range, location, or star rating. Exports are available as CSV for analysis in Excel or BI tools, or as PDF summaries for stakeholder reporting.
Built for busy local business owners
Typani writes on-brand replies to every Google review in seconds, so you can answer them all without giving up your evening.
Generate your first response in seconds
Free to start. No credit card. Works on any Google review.
Try Typani FreeRelated
Explore Typani