Every completed job triggers an AI that reads customer sentiment and either sends a personalized Google review request — or quietly alerts the manager before a bad review goes public.
Most local service businesses do great work. Their customers are happy. But nobody asks for reviews — it feels awkward, so it never happens.
Meanwhile, the one customer who had a bad experience? They leave a review immediately. Without intervention, that 1-star sits on your Google profile for years, dragging down an otherwise stellar reputation.
The result: 34 total reviews, a 3.8-star average, and a steady stream of potential customers picking a competitor with more social proof — even though your work is better.
How it works — every single time
Within 90 days of deploying the automation, a local HVAC company went from 34 Google reviews to 91 — without anyone on staff manually asking a single customer.
More importantly: two complaints that would have become public 1-star reviews were caught by the manager alert system. Both customers received a call within 24 hours. Neither posted a negative review.
The 4.6-star profile now ranks above three competitors in local search — generating an estimated 8–12 additional inbound calls per month.
If you use Jobber, ServiceTitan, Jane App, OpenTable, or any job management tool with a webhook — this can be wired in within a day.
The demo below lets you simulate both sides: the customer submitting feedback, and the business generating a manual review request. The routing is live — real GPT-4o, real output.