NLP Review and Patient-Feedback Intelligence Across a 45-Office Dental Group
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Problem
Feedback nobody could read
A 45-office family dental group received several thousand public reviews and post-visit survey comments every month across review platforms and its own intake system. Office managers skimmed at best a fraction of them, negative reviews sat unanswered for days, and leadership had no way to see whether complaints about billing, wait times or chairside manner were isolated or systemic.
Solution
Automated theme and sentiment engine
We built an NLP feedback-intelligence pipeline that ingests reviews and survey comments nightly, classifies each one by sentiment and operational theme, and routes negative items to the right office manager within the hour. A group-level dashboard trends themes by office and clinician, and a weekly digest gives regional leaders a ranked list of emerging issues before they spread.
Measurable Impact
What changed after launch
Over 6,000 monthly reviews and comments classified automatically, with 91% theme accuracy on a hand-audited sample
Median response time to negative public reviews cut from 5 days to under 12 hours
Billing-related complaints down 27% after the theme dashboard exposed two fixable process failures
Average public rating across the 45 offices improved from 4.2 to 4.5 stars within 6 months
Tech & Tools Used
What powered the build
Ready to Build your Dental Healthcare Business with Natural Language Processing
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