Wrangler Cow Print Wallets Womens Bifold Credit Card Wallet Women's Wallets, Card Cases & Money Organizers Brown Wallet for Women Ladies Female Cash Wallett with Smooth Zipper
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Review Analysis Results
Analysis Summary
This product shows moderate signs of review manipulation with several concerning patterns. The review distribution is heavily skewed toward 5-star ratings (10 out of 14 reviews), with only one 1-star, one 3-star, and one 4-star review. There are duplicate reviews (review 1 and 14 are identical), which is a strong indicator of manipulation. Multiple reviews use repetitive, overly enthusiastic language with similar phrasing about 'beautiful' appearance and 'great quality.' Several reviews are extremely brief and generic ('Very nice wallet,' 'Beautiful wallet, great quality') which are common in fake review campaigns. However, there are also detailed, balanced reviews with specific usage experiences and legitimate criticisms that appear authentic, preventing a higher fake percentage score.
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.
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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 (3.60 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 (4.53 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.
