RAVIAD USB C to USB C Cable Short, [2Pack 50CM] 60W 20V/3A PD Fast Charging Data Cable Lead Compatible with iPhone 16 15, Samsung Galaxy S23/S22/S21, Huawei Mate 60 Pro, MacBook Pro/Air, Pixel - Black
RAVIAD USB C to USB C Cable Short, [2Pack 50CM] 60W 20V/3A PD Fast Charging Data Cable Lead Compatible with iPhone 16 15, Samsung Galaxy S23/S22/S21, Huawei Mate 60 Pro, MacBook Pro/Air, Pixel - Black : Amazon.co.uk: Computers & Accessories
Review Analysis Results
Analysis Summary
This product shows moderate signs of review manipulation with several concerning patterns. The review set is extremely homogeneous with 8 out of 9 reviews being 5-star (89%), which is statistically unusual for most products. All reviews are from unverified purchases ('U'), meaning Amazon cannot confirm the reviewer actually bought the product, significantly increasing fraud risk. The complete absence of critical feedback (no 1-3 star reviews) suggests potential review filtering or suppression of negative reviews. While the sample size is small (9 reviews), the uniformity and lack of verified purchases create reasonable suspicion of artificial inflation.
Review Statistics
Price Analysis
This appears to be a budget-friendly USB-C cable option with strong customer satisfaction. Given the 4.89/5 rating from 3,781 reviews, it likely represents solid value in its category. Wait for promotional pricing events or check current price against similar 60W 2-pack cables from reputable brands before purchasing.
MSRP Assessment
Market Position
Buying Tips
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 (4.89 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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