KAKEI Chainsaw Chain 20 Inch .325" Pitch .063" Gauge 81 Drive Links- 26RS 81 Fits Stihl (PRE 2023 .063" Gauge) MS291, MS271 Farm Boss, MS261-36390050081, V81 (3 Chains)

KAKEI Chainsaw Chain 20 Inch .325" Pitch .063" Gauge 81 Drive Links- 26RS 81 Fits Stihl (PRE 2023 .063" Gauge) MS291, MS271 Farm Boss, MS261-36390050081, V81 (3 Chains)

ASIN: B0B7B4GL97
Analysis Date: Oct 17, 2025 (re-analyzed Oct 17, 2025)

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.87
Original Rating
4.20
Adjusted Rating

Analysis Summary

The review set shows moderate authenticity concerns with several suspicious patterns. While many reviews appear genuine with specific usage details and varied language, there are notable red flags: 15 of 16 reviews are 4-5 stars (94% positive), creating an unnatural rating distribution. Several reviews use identical marketing phrases like 'cuts like butter' and repetitive 'great chain for great price' language. Review #13 appears to be a corrupted video description rather than a genuine review, and review #15 admits the user hasn't actually used the product yet. However, the majority of reviews contain specific details about chainsaw models, cutting experiences, and comparative performance that suggest legitimate usage. The presence of some 4-star reviews and varied writing styles provides some authenticity balance.

Review Statistics

9,087
Total Reviews on Amazon
-0.67
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 (4.20 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 (4.87 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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