Wall Mount Mailbox, Large Capacity for House, Outside, with 3 Sets of 0-9 Number Stickers & Flower Planter, Galvanized Steel Rust-Proof Metal Post Drop Box, 15.74"×9.84"×6.41" Black

Wall Mount Mailbox, Large Capacity for House, Outside, with 3 Sets of 0-9 Number Stickers & Flower Planter, Galvanized Steel Rust-Proof Metal Post Drop Box, 15.74"×9.84"×6.41" Black

ASIN: B0CLQXSJMY
Analysis Date: Oct 12, 2025

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Review Analysis Results

D
Authenticity Grade
42.00%
Fake Reviews
4.83
Original Rating
3.80
Adjusted Rating

Analysis Summary

The review set shows moderate signs of inauthenticity with several concerning patterns. Key findings: 1) Extremely high 5-star concentration (10/12 reviews = 83%) with minimal critical feedback, 2) Multiple duplicate reviews from the same users (R2AIVHYZ9T6FA7 and R1UHN1W53SY3MB appear twice with identical content), 3) Several reviews contain suspiciously similar language focusing on decorative elements and installation, 4) Some reviews have unnatural phrasing and excessive enthusiasm that reads like marketing copy. However, there are also legitimate-seeming reviews with specific installation details and practical observations that balance the assessment. The verification status shows a mix of verified (V) and unverified (U) purchases, with both groups containing potentially suspicious content.

Review Statistics

75
Total Reviews on Amazon
-1.03
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 (3.80 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 (4.83 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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