The Microsoft Office 365 Bible: The Most Updated and Complete Guide to Excel, Word, PowerPoint, Outlook, OneNote, OneDrive, Teams, Access, and Publisher from Beginners to Advanced

The Microsoft Office 365 Bible: The Most Updated and Complete Guide to Excel, Word, PowerPoint, Outlook, OneNote, OneDrive, Teams, Access, and Publisher from Beginners to Advanced

ASIN: B0CGXXYK3H
Analysis Date: Sep 17, 2025 (re-analyzed Sep 17, 2025)

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Review Analysis Results

D
Authenticity Grade
42.00%
Fake Reviews
4.77
Original Rating
3.80
Adjusted Rating

Analysis Summary

Analysis of 235 reviews across 5 chunks. Weighted fake percentage: 42%. Chunk consistency: high. Global patterns: Low verified purchase rate (13.6%). The extremely low verified purchase rate of 13.

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.

2,612
Total Reviews on Amazon
13
Reviews Analyzed
8
Genuine Reviews
5
Fake Reviews
-0.97
Rating Difference

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 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 (3.80 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 (4.77 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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How Our Analysis Works

Detailed explanation of our AI methodology

Spotting Fake Reviews Yourself

10 warning signs to watch for

Frequently Asked Questions

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