TORCHSTAR 1700LM Universal Garage Door Opener LED Light Bulb, UL FCC Listed, 15W Ultra Bright, Minimize Interference, 100W Eqv. 120V, A19 Bulbs, E26 Base, 5000K Daylight, Pack of 2

TORCHSTAR 1700LM Universal Garage Door Opener LED Light Bulb, UL FCC Listed, 15W Ultra Bright, Minimize Interference, 100W Eqv. 120V, A19 Bulbs, E26 Base, 5000K Daylight, Pack of 2

ASIN: B075B6WD3B
Analysis Date: Oct 11, 2025

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Review Analysis Results

C
Authenticity Grade
28.00%
Fake Reviews
4.47
Original Rating
3.80
Adjusted Rating

Analysis Summary

The review set shows a moderately suspicious pattern with several legitimate-seeming reviews mixed with some questionable ones. The product has an unusually high concentration of 5-star ratings (10 out of 14 reviews), which is common in manipulated review sets. However, many reviews contain specific technical details about garage door opener compatibility, interference issues, and brand comparisons that suggest genuine user experience. The presence of critical reviews (1-star and mixed 4-star reviews) discussing actual product issues adds credibility. Suspicious patterns include repetitive phrasing about brightness and interference, plus several very brief reviews that lack substantive detail. The overall distribution suggests some potential review manipulation but not overwhelmingly so.

Review Statistics

3,761
Total Reviews on Amazon
-0.67
Rating Difference

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 (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 (4.47 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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