WakeALL Hydrocolloid Patches for Face, 5 Sizes (8/10/12/14/16mm) - Invisible Round Blemish Patches, Fluid-Absorbing Spot Stickers for Precise Fit, Individually Wrapped, Travel-Friendly 108 Count Box

WakeALL Hydrocolloid Patches for Face, 5 Sizes (8/10/12/14/16mm) - Invisible Round Blemish Patches, Fluid-Absorbing Spot Stickers for Precise Fit, Individually Wrapped, Travel-Friendly 108 Count Box

ASIN: B0D8BZTJHR
Analysis Date: Oct 4, 2025 (re-analyzed Oct 4, 2025)

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.80
Original Rating
4.10
Adjusted Rating

Analysis Summary

The review set shows moderate authenticity concerns with a 28% estimated fake percentage. While most reviews appear genuine, several patterns raise suspicion: 14 of 16 reviews are 5-star (87.5%), creating an unusually positive distribution. Multiple reviews use nearly identical phrasing about 'different sizes' and 'invisible/transparent' patches, suggesting potential coordination. However, the presence of balanced 3-star and 4-star reviews, varied writing styles, and specific product details provides credibility. The reviews show reasonable length variation and include some critical feedback, though the overwhelming positivity and repetitive language patterns indicate potential manipulation.

Review Statistics

505
Total Reviews on Amazon
-0.70
Rating Difference

Price Analysis

Price analysis pending

Price insights will be available shortly.

Understanding This Analysis

What does Grade C mean?

This product has moderate review authenticity concerns. A notable portion of reviews show suspicious patterns. Consider reading reviews carefully before purchasing.

Adjusted Rating Explained

The adjusted rating (4.10 stars) represents what we estimate this product's rating would be if fake reviews were removed. This product's adjusted rating is lower than Amazon's displayed rating (4.80 stars), suggesting positive fake reviews may be inflating the score.

How We Detect Fake Reviews

Our AI analyzes multiple factors: language patterns (generic vs. specific), reviewer behavior (history, timing), temporal anomalies (review clusters), verification status, sentiment authenticity, and statistical outliers. No single factor determines a review is fake - we look at the combination of signals.

Important Limitations

No automated system is perfect. Sophisticated fake reviews can evade detection, and some genuine reviews may be incorrectly flagged. Use this analysis as one data point in your purchasing decision, not the only factor. Reading actual review content yourself is always valuable.

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