168 Pack Rok Hardware Heavy Duty 3/8" (9.5mm) Diameter Self-Adhesive Felt Pads, Furniture/Cabinet Bumpers, 1/8" (3mm) Height, Round, Brown - ROKFELTP38BRN

168 Pack Rok Hardware Heavy Duty 3/8" (9.5mm) Diameter Self-Adhesive Felt Pads, Furniture/Cabinet Bumpers, 1/8" (3mm) Height, Round, Brown - ROKFELTP38BRN

ASIN: B01CF6A65U
Analysis Date: Nov 6, 2025

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.70
Original Rating
4.00
Adjusted Rating

Analysis Summary

The review set shows a moderately suspicious pattern with several legitimate indicators but also some concerning elements. The product has overwhelmingly positive ratings (8 out of 9 reviews are 4-5 stars) with only one 3-star review, creating an unnatural distribution. Multiple reviews mention long-term use (2 years) and specific applications (kitchen cabinets, 3D printed holders, POS displays) which adds credibility. However, several reviews are extremely brief and generic ('Good product, not too thick', 'They are cheaper by buying in bulk') lacking substantive detail. The presence of one moderate rating (3 stars) and varied use cases provides some authenticity balance. The overall pattern suggests a mix of genuine user experiences with some potentially incentivized or low-effort reviews.

Review Statistics

4,865
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 (4.00 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 (4.70 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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