Shilajit Pure Himalayan Capsules (20% Fulvic Acid Supplement) 1,000mg of Authentic Shilajit Extract per Serving, 120 Count (High in Trace Minerals, No Fillers) by Double Wood

Shilajit Pure Himalayan Capsules (20% Fulvic Acid Supplement) 1,000mg of Authentic Shilajit Extract per Serving, 120 Count (High in Trace Minerals, No Fillers) by Double Wood

ASIN: B0B7KFV1NL
Analysis Date: Oct 5, 2025

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Review Analysis Results

D
Authenticity Grade
42.00%
Fake Reviews
4.47
Original Rating
3.50
Adjusted Rating

Analysis Summary

The review set shows moderate signs of inauthenticity with several concerning patterns. While there are legitimate-sounding reviews with specific experiences and balanced ratings, multiple red flags emerge: 1) High concentration of 5-star reviews (10 out of 15 reviews) with overly enthusiastic language and generic health claims, 2) Several reviews contain suspicious elements like 'not being paid' disclaimers and excessive brand loyalty statements, 3) Multiple reviews show formulaic language about energy boosts and mood improvements with minimal specific details, 4) The presence of duplicate/repeated content (review #5 and #14 are identical) suggests manipulation. However, the inclusion of mixed ratings (including 1-star and 3-star reviews) and some detailed, nuanced reviews provides some balance.

Review Statistics

1,053
Total Reviews on Amazon
-0.97
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 (4.47 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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