Starter Motor Replacement 19090N 36100-2G100 FS14N1 19306554 336-2125 Compatible with Hyundai Sonata 2009-2014 Santa Fe Sport 2010-2014 Kia Optima 2012-2014 Sorento 2011-2014 L4 2.4L

Starter Motor Replacement 19090N 36100-2G100 FS14N1 19306554 336-2125 Compatible with Hyundai Sonata 2009-2014 Santa Fe Sport 2010-2014 Kia Optima 2012-2014 Sorento 2011-2014 L4 2.4L

ASIN: B0DQV3J3VW
Analysis Date: Nov 8, 2025 (re-analyzed Nov 8, 2025)

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Review Analysis Results

C
Authenticity Grade
35.00%
Fake Reviews
4.50
Original Rating
3.70
Adjusted Rating

Analysis Summary

The review set shows mixed authenticity signals. Positive aspects include reasonable verification rates and some detailed, specific reviews that appear genuine (like review #4 with technical DIY instructions). However, several concerning patterns emerge: multiple 5-star reviews use nearly identical phrasing about 'fitting perfectly' across different vehicle models (F150, BMW X3, Matrix), suggesting potential template use. The Spanish review (#1) appears authentic with local terminology, but the English reviews show some unnatural phrasing and repetition. The single 1-star review (#3) appears genuine with specific failure timeline. Overall, there's likely a moderate percentage of inauthentic reviews mixed with legitimate ones, primarily among the 5-star ratings.

Review Statistics

44
Total Reviews on Amazon
-0.80
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 (3.70 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 (4.50 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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