Automate the post-job review request for home service companies, fired by the job-complete event and suppressed on any job with an open complaint.
An AI agent for review requests is a 24/7 digital assistant that watches for jobs marked complete, texts the customer who was actually at the property, sends a direct link to your Google review page, and keeps a record of who has already been asked. It stops the request from arriving three weeks late — or never — when the office is buried and nobody remembers which jobs closed clean. Review volume in home services is a timing problem far more than a persuasion problem. A homeowner who has just watched a technician diagnose a dead condenser and get cold air moving again will happily write four sentences in the hour after the van pulls away. The same homeowner, emailed eleven days later in a monthly batch, will not remember which company you were. This agent hangs the request on the completion event in your field-service software, sends one short message from a number the customer recognizes, and stays quiet on any job carrying a callback, a warranty claim or a disputed invoice.
Right moment, right person, right job.
Triggers on the job-complete event in your field-service software rather than a nightly batch
Sends to the contact who was actually on site, not the billing name on the account
Waits a delay you set, so the technician has left but the visit is still fresh
Includes a direct link to your Google review form so nobody has to hunt for the listing
Holds the request back on jobs with a callback, warranty claim or open invoice dispute
Sends one reminder after two days, then marks the customer asked and stops chasing
Most contractors already know they should be asking for reviews. What they do not have is a reliable moment when the ask happens, a reliable person it reaches, and a reliable rule for when it should not go out at all. This agent fixes all three. It attaches the request to the completion event instead of someone's memory, sends it to the person who let the technician in, and pauses on the small number of jobs where the customer is still waiting on something from you.
A simple, three-step flow.
The agent listens for the job-complete status in ServiceTitan, Housecall Pro or Jobber and reads the on-site contact, the service performed and the technician's first name.
Before anything sends, it checks for a booked return visit, an open warranty claim, a queried invoice or a request already sent to this customer, and drops the job if it finds one.
A short text goes out after your chosen delay with a direct review link. One reminder follows two days later if nothing lands, then the customer is marked asked and left alone.
A realistic use case with concrete timing and output.
Scenario: A 6-technician heating and air company closes around 40 jobs a week and had been averaging four new Google reviews a month. A capacitor replacement is marked complete at 2:15pm. At 3:00pm the homeowner who let the technician in receives: "Thanks for having us out today — Marcus said the system is running cold again. If you have thirty seconds, a quick Google review genuinely helps a small crew." with a direct link. She writes four sentences that afternoon and names the technician. The same week two jobs are held back: one has a return visit booked for a noisy blower, the other has an invoice the customer is querying. Both are released once resolved. Monthly review volume moves from four to nineteen with nobody in the office touching a list.
Roles that gain practical value from this AI agent.
You are the technician, the dispatcher and the marketing department, and the review ask is always the thing that gets dropped.
Removes the weekly job of exporting completed work and deciding by hand who is safe to ask.
Keeps review volume steady through the summer rush, when the office has the least time and the most completed jobs.
Recent review count and recency feed local ranking, and a monthly batch produces neither reliably.
Every crew gets the same follow-up, so one branch is not carrying the whole rating.
Going from nine reviews to sixty changes which contractor a homeowner calls first, and early volume compounds.
Key tools and what the AI agent does inside each.
Reads the job-complete event, the on-site contact and the technician assigned, and writes back that a request was sent.
Same trigger for smaller shops, including the invoice status the agent uses to decide whether to hold the request.
Sends the request and the single reminder from your business number, and captures replies into the same thread.
Supplies the short review link that opens the rating form directly, and confirms when a new review has landed.
Keeps the record of who was asked, which jobs were suppressed and why, so nobody is chased twice.
Six practical scenarios that this AI agent excels in.
Common questions about using the AI agent in workflows.
An AI agent for review requests is a 24/7 digital assistant that watches for jobs marked complete, texts the customer who was actually at the property, sends a direct link to your Google review page, and keeps a record of who has already been asked. It stops the request from arriving three weeks late — or never — when the office is buried and nobody remembers which jobs closed clean. Unlike a bulk email blast, it fires per job, reaches the on-site contact, and knows which jobs to leave alone.
Ask every clean job, once, within an hour or two of finishing, by text rather than email, with a link that opens the rating form directly. Most companies fail on volume of asks rather than on wording. Automating the trigger takes you from asking a third of customers to asking almost all of them, which is usually a three to five times increase in reviews.
Long enough after the technician leaves that the customer is not being asked to their face, short enough that the visit is still vivid. Thirty to ninety minutes works for repairs. For installs, wait until the system has run overnight so the customer has something real to say. You set the delay per job type.
The on-site contact recorded on the job, which is often a spouse, a tenant or a property manager rather than the account holder. That person met the technician and can describe the work. If no on-site mobile number was captured, the agent falls back to the account contact and marks the request as lower quality.
It pauses on jobs with an unresolved issue — a booked return visit, an open warranty claim, a queried invoice — and releases the request once the issue is closed. That is a rule about unfinished work, not a filter on opinion. It does not survey customers first and only send the happy ones to Google, which is review gating and breaches Google's policies.
No, and the agent will not write a message that does. Google prohibits incentivised reviews outright. Reviews obtained that way can be stripped from the profile, and repeat offences put the listing itself at risk. The ask stays a plain request with no reward attached.
Yes. It reads the completion event and the job record through the API, so the request carries the correct service, technician name and on-site contact, and it writes back a note that the request was sent. Shops without field-service software can trigger it from a Google Sheet or a Jobber webhook instead.
Automate the post-job review request for home service companies, fired by the job-complete event and suppressed on any job with an open complaint.