17 Inch Acacia Wood Serving Tray with Handles - Large Wooden Tray for Ottoman, Breakfast in Bed, Dinner, Coffee Table - Decorative Rectangular Tray for Living Room Bedroom Entryway and Kitchen
As an Amazon Associate I earn from qualifying purchases.
Review Analysis Results
Analysis Summary
The reviews show a moderately suspicious pattern with 14 out of 15 reviews being 5-star (93%), which is unusually high for any product. However, the content shows reasonable variation in use cases (serving, crafts, display) and specific details about construction, finish, and functionality. The main concerns are the duplicate reviews (R1QSIXVDA7NXJA and R31Q5BRPRDTSEO appear twice) and several very brief, generic 5-star reviews that lack substance. The presence of one 4-star review with balanced criticism adds some credibility. Overall, while the rating distribution is suspiciously positive, the content diversity suggests a mix of genuine and potentially incentivized reviews.
Review Statistics
About Review Data Collection
We extract as much review data as Amazon makes available at the time of analysis. The amount may vary due to Amazon's rate limiting, regional restrictions, or other factors. Our analysis is based on the reviews we successfully collected.
Want to analyze more reviews? Install the Null Fake Chrome extension to capture and analyze additional reviews as you browse Amazon.
Free, quick to install, and works on Chrome, Edge, Brave, and other Chromium browsers.
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 (4.93 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.