Free tool
Fake Review Checker, Spot Suspicious Reviews
Paste any Amazon, Trustpilot, Google, or product review and get an instant suspicion score from 0 to 100, plus a plain-English breakdown of every red flag detected. Runs fully in your browser, nothing is uploaded.
Paste a review
Review text
Drop in any product or store review. The check runs entirely in your browser, nothing is sent anywhere.
Words analyzed: 35
Suspicion score
Multiple strong red flags. Treat this review with heavy skepticism and look at the reviewer’s history before trusting it.
5 signals detected
Excessive superlatives & marketing language
Genuine reviews mix praise with specifics. A pile-up of hype words like “amazing”, “best ever” or “highly recommend” is a classic pattern in incentivised or fabricated reviews.
Matched: amazing, best product, best purchase, life-changing, highly recommend, must-have
High ALL-CAPS ratio
Shouting in capitals (“BEST product EVER”) is rare in calm, authentic feedback and common in copy-pasted or emotionally manufactured reviews.
2 fully-uppercase words
High exclamation-mark density
A wall of exclamation marks signals manufactured enthusiasm. Real buyers rarely punctuate every sentence with “!!!”.
6 exclamation marks
No specific product details
Authentic reviews mention concrete details, size, fit, colour, how long they used it, who it was for. The absence of any first-person specifics is a meaningful red flag.
No use-case, attribute or first-person detail found
No balance or nuance
Real experiences usually include a caveat, “great, but the strap is stiff”. Uniformly glowing text with zero downside reads as promotional.
A note on honesty: these are heuristic signals, not proof. No tool, ours included, can definitively detect whether a review is fake. Treat a high score as a prompt to investigate (check the reviewer’s history, verify the purchase), never as a verdict on a real person.
What a fake review checker is, and the method behind the score
A fake review checker is a tool that scans the language of a review for patterns that statistically correlate with fabricated, paid, or incentivised feedback. It does not read minds and it cannot see the reviewer’s account, it works purely from the text you paste in. Our checker applies a transparent set of heuristics, assigns each one a weight, and sums the weights of every pattern it detects into a single suspicion score from 0 to 100. That score maps to three bands: Likely genuine (0–29), Some red flags (30–59), and Likely fake (60–100).
The signals it checks for are the same ones trust-and-safety teams look at first:
| Signal | Why it raises suspicion |
|---|---|
| Excessive superlatives | Hype words like “amazing”, “best ever” and “highly recommend” stacked together. |
| High ALL-CAPS ratio | Shouting in capitals is rare in calm, authentic feedback. |
| Exclamation density | “!!!” on every sentence signals manufactured enthusiasm. |
| Very short / thin text | Too few words to carry any verifiable detail; cheap to mass-produce. |
| Generic template phrasing | “Great product, fast shipping, highly recommend” describes nothing specific. |
| Repeated words or phrases | “Amazing amazing amazing” is padding used to bulk out low-effort reviews. |
| No specific product details | No size, fit, colour, duration of use or first-person context. |
| No balance or nuance | Uniformly glowing with zero caveat reads as promotional, not lived. |
No single signal is conclusive. The score reflects how many fire at once and how strongly.
How to use the fake review checker, step by step
- 1. Copy the full text of the review you want to check, an Amazon review, a product review, a Trustpilot review, or a Google review.
- 2. Paste it into the box above. The suspicion score and red-flag checklist update instantly as you type.
- 3. Read each detected signal and its explanation to understand why the review looks suspicious, the score alone is not the point.
- 4. Use “Copy report” to save the result, then corroborate with reviewer-level evidence (account age, review velocity, verified purchase) before drawing any conclusion.
A worked example
Take the prefilled sample: “This is the BEST product I have EVER bought!!! Absolutely amazing, life-changing, a must-have for everyone…” It fires on five heuristics at once, a stack of superlatives (“BEST”, “amazing”, “life-changing”, “must-have”, “highly recommend”), a high all-caps ratio, three-plus exclamation marks, the word “amazing” repeated, and zero specific details about what the product is, who it is for, or how it was used. Those weights add up past 60, landing it in Likely fake. Now compare a genuine review: “Bought the medium for my husband; the sleeves run a little long but the fabric is soft and it held up after three washes.” It names a size, a recipient, a downside and a durability test, almost nothing fires, and it lands firmly in Likely genuine.
Why fake reviews matter for Shopify merchants
Reviews are one of the highest-leverage trust signals on a Shopify storefront, and that makes them a target. Seeding fake positives (or buying Trustpilot reviews) now carries real downside: the FTC’s review rule allows steep penalties, and Google and Trustpilot run their own detection that can wipe your rating overnight. On the flip side, fake negative reviews from competitors or bad-faith actors drag down conversion. The checker above helps you triage both, but the structural fix is to flood your listings with verified reviews from real, recent buyers so authentic voices dominate. If a damaging fake slips through, our guide on removing a fake Trustpilot review walks through the dispute process.
Common mistakes to avoid
- Treating the score as a verdict. It is a prompt to investigate, never proof. Real customers sometimes write like this.
- Judging text in isolation. The strongest evidence is reviewer-level, account age, review velocity, verified purchase, which lives outside the words.
- Accusing a reviewer publicly. Replying with an accusation based on a heuristic can backfire badly. Report through official channels instead.
- Assuming short means fake. A terse “Fits well, washed great” is thin but can be perfectly real. Weigh it against the other signals.
- Ignoring your own incentives. If you give discounts for five-star reviews, you are manufacturing the exact patterns this tool flags, and breaching most platforms’ rules.
The reliable defence: collect verified reviews automatically
No detector will fully police the reviews on your store, the durable strategy is to make authentic reviews so plentiful that fakes are diluted and easy to spot. Reviewz requests a review from every Shopify customer automatically a few days after delivery, ties each review to a verified order, routes happy buyers to public platforms and captures unhappy feedback privately before it becomes a one-star review. The result is a continuous stream of genuine, purchase-verified social proof, the single best antidote to fakes on either side. For more on how platforms decide what is authentic, see our breakdown of detecting AI-generated reviews.
Built and maintained by the Reviewz team, we help 250+ Shopify stores collect reviews.
Frequently asked questions
How does this fake review checker work?
It runs a set of linguistic heuristics entirely in your browser, no review text is ever uploaded. The checker scans the pasted review for patterns that correlate with fake or incentivised reviews: an excess of superlatives and marketing language, a high ALL-CAPS ratio, dense exclamation marks, very short or generic template text, repeated words, and an absence of specific first-person details. Each triggered pattern adds weighted points to a 0–100 suspicion score, which maps to one of three bands: Likely genuine, Some red flags, or Likely fake.
Can I use this as an Amazon review checker?
Yes. The checker is platform-agnostic, it analyses the text of any review you paste, whether it comes from Amazon, Trustpilot, Google, or a Shopify product page. Amazon reviews are a common use case: paste a suspicious five-star review and the tool flags the same patterns Amazon's own systems weight, such as generic praise, superlative stacking, all-caps bursts, and template-thin wording. Remember that the strongest Amazon signals (Verified Purchase badge, reviewer history, review velocity) live outside the text, so use the score as a triage aid, not a verdict.
Can a tool actually prove a review is fake?
No, and you should distrust any tool that claims it can. Language heuristics surface signals, not proof. A genuinely delighted customer can write in all caps with five exclamation marks, and a sophisticated fake can read perfectly natural. This checker is a triage aid that tells you where to look more closely; the real verification comes from the reviewer's purchase history, account age, review velocity, and whether the order can be matched to a real transaction.
What are the biggest red flags of a fake review?
The strongest signals are: generic praise with zero specific details (no mention of size, fit, use-case or who it was for), a pile-up of hype words like 'amazing', 'best ever' and 'highly recommend', uniformly glowing text with no nuance or downside, repeated phrasing used to pad length, and bursts of all-caps or exclamation marks that manufacture enthusiasm. A single flag rarely means much; several appearing together is far more telling. Reviewer-level signals, many five-star reviews posted in a short window, brand-new accounts, identical wording across products, are even stronger but live outside the text itself.
Why do fake reviews matter for my Shopify store?
Fake reviews cut both ways. Buying or seeding positive fakes can get your store penalised under the FTC's review rule and torched by Google's and Trustpilot's detection systems, destroying the trust you were trying to build. Fake negative reviews, from competitors or extortion attempts, drag down your rating and conversion rate. Either way, the durable fix is the same: collect a steady stream of verified reviews from real, recent buyers so authentic feedback drowns out the noise.
What should I do if a review looks fake?
Don't accuse the reviewer based on a heuristic score alone. First, check whether the review is attached to a verified purchase and review the account's other activity. If it is a fake positive on your own listing, remove or stop incentivising it. If it is a fake negative, gather evidence (no matching order, suspicious account, duplicate wording) and report it to the platform through their official dispute process rather than replying angrily in public.
Beat fakes with a flood of verified reviews
Check a suspicious review here, then collect genuine, purchase-verified reviews from every Shopify order on autopilot, so authentic voices always outnumber the fakes.
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