Run the pipeline below. It starts with a closed job and shows the record changing as the system checks sentiment, sends the ask, captures the review, and stops for owner approval.
The useful bit is the routing logic: public ask when sentiment is safe, private triage when it is not, and approval before anything gets published.
Every completed job is a chance to increase trust. The system asks at the right time, routes bad experiences privately, and keeps staff from doing review chores by hand.
When a job is marked complete, the customer gets a timed SMS/email review request with the right link.
Low satisfaction routes to an owner alert or internal feedback path before the public review ask.
AI drafts review responses using service context and tone rules, then waits for owner approval.
Invoice paid, appointment complete, job card closed, or a manual send button can start the workflow.
Happy customers get the public review link. Poor sentiment gets routed to the owner first.
Monthly snapshots show review volume, response time, rating movement, and unresolved reputation issues.
Reviews compound. The system makes sure the ask happens before the customer forgets why they liked you.