Amartisan 14-Piece Retractable Box Cutter, Utility Knifes for Boxes, Cartons, Cardboard Cutting, 18mm & 9mm Wide Blade Cutter, Very Suitable for Office and Home Use.

Amartisan 14-Piece Retractable Box Cutter, Utility Knifes for Boxes, Cartons, Cardboard Cutting, 18mm & 9mm Wide Blade Cutter, Very Suitable for Office and Home Use.

ASIN: B089G64X83
Analysis Date: Nov 5, 2025 (re-analyzed Nov 5, 2025)

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Review Analysis Results

D
Authenticity Grade
42.00%
Fake Reviews
4.40
Original Rating
3.50
Adjusted Rating

Analysis Summary

This product shows moderate signs of review manipulation with several concerning patterns. The rating distribution is heavily skewed toward 5-star reviews (9 out of 14 reviews), with only one 1-star review and minimal mid-range ratings. Multiple reviews contain nearly identical phrasing about 'breaking off the blade when dull' (reviews 1, 3, 6, 10, 12), suggesting coordinated content. Several reviews are extremely brief and generic (reviews 8, 9, 13) with minimal product detail. The duplicate review from user R28UW9WRVAA7E4 (reviews 6 and 10) is particularly suspicious. However, the presence of legitimate-sounding critical reviews (4, 7, 11, 14) and detailed usage descriptions in some positive reviews provides some balance.

Review Statistics

1,947
Total Reviews on Amazon
-0.90
Rating Difference

Price Analysis

Price analysis pending

Price insights will be available shortly.

Understanding This Analysis

What does Grade D mean?

This product has significant review authenticity issues. Many reviews show patterns consistent with fake or incentivized reviews. Exercise caution.

Adjusted Rating Explained

The adjusted rating (3.50 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 (4.40 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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