How to Measure Review Request Conversion (Requests → Reviews)

Measure review request conversion as new Google reviews divided by review requests sent in the same window. Count the sends. Count the reviews that posted. Divide. If you have clicks, count those too, between the send and the review. Do not treat a rating change as the conversion rate. Rating is a different number. The only owned rate we will cite is a Houston garage-door account: 15.9 percent request-to-review in 45 days. That is an example from that account, not a benchmark you are required to hit.

This is a counting page. It is not a second case study, and it does not invent industry averages. If you cannot count sends, you cannot know whether the ask is working. You only know that the profile moved, or did not.

Define the window before you divide

Pick a window and write it down. A week is fine for a busy shop. 30 days is easier if you close a handful of jobs. 45 days is what the Houston example used. The rule is that the requests and the reviews come from the same window, and you do not move the window after you see the number because you dislike it.

A request is a review ask that actually went out: an SMS, an email, or a WhatsApp message with the direct Google review link, sent after a completed job. A verbal “sure” at the door is not a request until the link is sent. A social post that says “please review us” is not a request you can attribute to a job. A QR tap can be a request if you can count scans or visits to the form. If you cannot count them, do not pretend the QR is in the denominator. Put uncounted channels in a note, not in the math.

A review is a new Google review that posted in the window, or shortly after a request if you are matching by name and date. Matching is imperfect. People review without using your link. People get the link and review the next week. Write the matching rule before you start: for example, a published review counts if it appears during the window and you sent that customer a request in the window, or if the review text matches a job you asked about. Do not count a review twice because you sent a reminder. One customer, one request sequence, one possible review.

The formula, without extra theater

Request-to-review conversion = published reviews tied to requests, divided by requests sent, in the same window. If you sent 100 requests and 16 matching reviews posted, the rate is 16 percent. If you cannot match names, use a cruder pair and label it as crude: new reviews on the profile in the window, divided by requests sent in the window. That version can be high if walk-in reviewers arrived, or low if your requests went to the wrong profile. Say which version you used. Do not mix them month to month.

Clicks sit in the middle if you have them. Requests sent, then link clicks, then reviews. A drop between send and click is a message or link problem. A drop between click and review is the form, the sign-in, or the customer simply leaving. You do not need a fancy funnel graphic. Three columns on a sheet are enough.

What to log on each closed job

Build a sheet with one row per completed job, not one row per hope. Columns that earn their keep: job date, customer first name, channel, request sent (yes or no), send date, reminder sent (yes or no), opt-out, link clicked if you know, Google review posted (yes or no), review date, and star if you want it. Stars are not the conversion rate. They are a quality note. Do not hide a 3-star from the “posted” column because it hurts a mood. It still converted from request to review if it came from that ask.

Count jobs with no request as a separate rate: share of completed jobs that got an ask. A beautiful conversion on 10 percent of jobs means the system is not on. Owners often celebrate a few reviews and never notice that most closes got nothing. Log the miss. The miss is the operational number. Conversion on the asks you did send is the message number. You need both, or you will “fix” the wording when the real gap is that Tuesday’s jobs were never texted.

Opt-outs are not failures of politeness if they are rare and honored. Log them. A jump in stops after you changed the text is a signal the new line is pushy, late, or going to the wrong people. Do not delete those rows to make the sheet look clean.

The public review list is the source for what posted. The Google Business Profile is the source of the profile state. If you use a tool that shows sends, export the sends instead of reconstructing them from a tech’s memory. Memory is how “we ask everyone” survives a week where half the jobs have no row.

How to read the number without inventing a standard

We will not tell you that 15 percent is average, good, or poor for “the industry.” We do not have a public industry table we are willing to treat as fact. We have one owned example. On a Houston garage-door account, request-to-review was 15.9 percent over 45 days, alongside 38 to 59 reviews, a rating move from 4.6 to 4.7, replies under 24 hours, GBP calls up 41.9 percent, and website clicks up 44.4 percent. The quote was: “We didn’t change the service. We changed the follow-up.”

Use that as a worked example of counting, not as a promise. Their 15.9 percent does not mean your next 100 texts will produce 16 reviews. It means that account could see requests and reviews in one window and divide. If your rate is much lower, look at the sheet before you buy a new slogan. Was the link opening the form? Did the text go the same day, or three days later? Did you ask for stars in a way that got ignored? Did you only ask the loudest fans, so the sent count is small and odd? If your rate is higher, do not assume you found a trick. Check that you are not counting reminders as extra reviews, or counting old reviews into a short send window.

Do not convert this rate into a ranking claim. More reviews in a window can sit next to more calls. In Houston, calls and website clicks moved while the follow-up changed. That is reported for that account. It is not a formula that says a point of conversion equals a point of Maps visibility. Profile basics still matter. A broken listing will not be saved by a clean spreadsheet. The checklist for the listing itself is the Google Business Profile optimization checklist. For a wider look at what to watch beyond one ratio, see Google review analytics.

The case study page, if you want the narrative around those figures and not just the division, is the Houston garage-door Google reviews case study. Do not paste their 15.9 percent into your ads as if it were your result.

A weekly review of the sheet

Once a week, not once a quarter, read four lines: jobs closed, requests sent, reviews posted, conversion. Then one sentence on the biggest miss. If requests sent are far below jobs closed, the trigger is the problem. If requests are high and reviews are near zero, test the link on a phone and read the text out loud. If clicks exist and reviews do not, the form or the timing is the problem, not “people in this town do not review.”

Keep rating and reply time off to the side of the conversion math. Reply time matters to the next reader of the profile. It is not the numerator of this rate. A shop can convert requests well and still leave reviews unanswered. Those are two habits. Houston’s replies moved to under 24 hours in the same period as the request work. Track that as its own yes or no: did we reply to new reviews in a day.

If you want a structured look at the profile and the recent review picture before you trust a homemade sheet, check your Reputation Score. The score does not replace the division. It tells you whether the public profile is even in shape to be measured. The free playbook is the closeout sequence you are measuring, written as steps instead of as a ratio.

Change one thing at a time if the rate is ugly. Fix the link, then the trigger, then the words. Do not rewrite the SMS, add a second channel, and shorten the delay in the same week, then credit whichever you like. The sheet only helps if the week is comparable to last week.

Write the window on the top of the sheet in words, not only in a filter. “Requests sent March 1 through March 31. Reviews posted March 1 through April 7, matched to those requests.” If you cannot finish that sentence, you are not ready to quote a percent to a partner or a vendor. The extra week on the review side is only for matching lag you already defined. It is not a way to go hunting for more reviews until the percent looks kinder. Date the sheet. Next month, use the same rule. That is the whole discipline.

Let ReviewNix handle the follow-up after you set the rule

You can measure this with a spreadsheet and the Google review list. Do that if you are the person who sends every text. The sheet gets honest when the send is automatic, because the denominator is no longer “jobs I remembered.” Manual measurement of a manual ask usually overstates how often you asked.

ReviewNix connects to your Google Business Profile and sends a neutral review request by SMS, email, or WhatsApp after a completed job. The dashboard shows the requests, so the send count is not a reconstruction. Reminders are visible, which keeps you from counting a reminder as a second request or forgetting you sent one. Stop and opt-out are logged so those names leave the sequence. AI reply drafts help the reply-time habit that sits next to conversion, not inside the formula. The request itself stays neutral: no 5-star ask, no incentive. You still decide the window and you still do the division. The tool’s job is the follow-up and the record of the follow-up, so the math is about customers, not about memory.

Set it up once. Let ReviewNix handle the follow-up. When you want the send log without building it from texts on a personal phone, use the trial form. Check the Reputation Score if you are measuring a profile you have not looked at as a whole.

Frequently asked questions

What is review request conversion rate?

It is published Google reviews tied to requests, divided by review requests sent, in a window you chose in advance. Count a reminder as part of the same sequence, not as a second request. If you cannot match names, label a cruder profile-level version and do not pretend it is customer-level.

Is 15.9 percent a target I should hit?

No. 15.9 percent is the request-to-review figure from one Houston garage-door account over 45 days. It is an owned example of counting, not an industry standard and not a promise for your shop. Use your own sends and your own reviews.

Should I include jobs where we never sent a request?

Track them separately. Conversion is reviews divided by requests sent. The share of completed jobs that got a request is a different rate. If you mix them, you will not know whether the message is weak or the message never went out.

Does a higher conversion rate mean a higher Google rating or rank?

No. Conversion tells you whether asks become reviews. Rating is the stars on those reviews and the ones you already had. Maps placement is Google’s decision. Do not use this ratio as a ranking guarantee. Count it so you can fix the ask, the link, or the trigger.