Review Machine use cases

See what your customers already say

Most owners have read a small part of their Google reviews. A review scan reads all of them: the themes guests mention, with their exact words; the reviews of 3 stars or lower that still have no reply; the words your customers use; and how your review count compares with the three most-reviewed places like yours nearby. Your team gets a draft reply for each unanswered review to edit and post. Facts many guests confirm help future customers describe their own visit.

People and places in this video are generated by AI. Every Review Machine screen is real, on a demo account with invented customers. Watch it on YouTube
Transcript

0:00 Two hundred reviews, twenty read

Before we send a single invite, we read every review you already have. Two hundred reviews. Honestly, I've read maybe twenty. Nina runs Olive & Ember. Like most owners, she never has time to read them all.

0:15 What guests mention, in their words

So we run a review scan of her Google listing for her. First, what guests mention most, with their exact words. Praise and complaints, side by side. The wood-fired dishes win people over. Weekend waits keep coming up.

0:33 Low-star reviews nobody answered

Next, low-star reviews nobody answered. Each one comes with a draft reply. Her team fills in the details, edits it, and posts it from her Google Business Profile.

0:46 The words guests use, the places nearby

Then the words her guests actually use. And where she stands: the three most-reviewed places like hers, within five kilometers.

0:58 Facts for future drafts

What many guests confirm, like the patio, becomes a fact we use in future guests' drafts. We preview the difference first. Nothing changes until we press Add.

1:11 What to fix first

Okay. Now I know what to fix first. One scan: 212 reviews read, 7 replies to write, 3 new facts. Curious where you stand? Run a free listing check at fractalic.studio.

What the owner does

Five steps, each shown in the video. The stills are frames from the video.

  1. The first page of the Google review report for Olive & Ember, Portland, OR, with the note We run the scan for you.

    We scan your listing

    We collect your public Google reviews and read them for you. Reviewer names are not stored.

  2. What customers mention: themes such as wood-fired dishes, friendly service, the patio and the weekend wait, each with quotes and a praise, complaint or mixed label.

    See the themes

    Each theme shows how many reviews mention it and real quotes, marked as praise, complaint or mixed.

  3. Draft replies to low-star reviews that have no reply yet, with bracketed details for the team to fill in.

    Answer what was missed

    Every review of 3 stars or lower without a reply gets a draft. Your team fills in the bracketed details and posts it from your Google Business Profile.

  4. Where you stand locally: three nearby listings with 640, 388 and 297 reviews next to Olive & Ember with 212, all in the same category within 5 km.

    Know where you stand

    Compare your review count with the three most-reviewed listings in your Google category within 5 km.

  5. Sample drafts with the confirmed facts highlighted, under the note Preview only. Nothing is saved.

    Keep the facts

    Things many guests confirm become facts we use when we help future customers put their visit into words. You see a preview first.

Check my Google listing →

Good questions. Clear answers.

Who runs the review scan?
We do. When you start with Review Machine, our team runs the scan on your Google listing and walks you through the report, so there is nothing for you to set up. For a quick first look before you talk to us, the free listing check on fractalic.studio compares your review count with three nearby competitors in under a minute.
Do you post replies to my reviews?
No. The report gives your team a draft reply for each review rated 3 stars or lower that has no reply yet. Parts in brackets are for you to fill in, such as a contact name. Your team edits the draft and posts it from your own Google Business Profile, so every reply goes out in your voice.
Which competitors do you compare me with?
The three most-reviewed listings in the same Google category within 5 km of your business. The report shows how many reviews each one has and how far away it is. It answers one plain question: in number of reviews, how far ahead or behind are you compared with the places your customers also consider?

More customer stories

A customer's hand holding a phone with a short review draft open for editing, in a living room in the evening. From "I'll do it later" to a posted review in a minute Most happy customers don't refuse to leave a review. They just never get to it. Watch the story (1:12) → Story cover with the words Two minutes every morning: a gym owner checking the Overview screen on her laptop. Two minutes every morning Is it working? Two minutes, one screen. Watch the story (1:12) →

The full sample report: The review audit, a full sample report. All use cases →

Further reading: Google's guidance on requesting honest reviews. Review Machine product page.

All customer stories on YouTube