How We Do It
Our Methodology
We believe in transparency. Here's exactly how we analyze products and generate our insights.
Reviews analyzed monthly
Data sources
Accuracy rate
Real-time monitoring
Step 1: Data Collection
We collect review data from multiple sources including Amazon, Chewy, Walmart, Target, and independent pet specialty retailers. We also monitor social media platforms like Reddit, Facebook Groups, and Instagram for unsolicited opinions.
Our data sources:
- Amazon
- Chewy
- Walmart
- Target
Step 2: Sentiment Analysis
Our proprietary AI model analyzes each review to determine sentiment (positive, negative, or neutral) and extract key themes. We use natural language processing to identify common phrases and topics mentioned by reviewers.
Positive
Happy pet, improved health
Neutral
No significant change
Negative
Digestive issues, allergies
Step 3: Quality Scoring
We calculate an overall satisfaction score for each product based on multiple factors, including sentiment analysis, review volume, and recency of reviews. Our algorithm gives more weight to recent reviews and accounts for potential review manipulation.
Factors considered:
- Overall sentiment score (40%)
- Review volume and consistency (25%)
- Recency of reviews (20%)
- Verification status (15%)
Step 4: Human Review
While our AI does the heavy lifting, every product analysis is reviewed by a human team member before publication. We verify that the AI's conclusions make sense and flag any unusual patterns that might indicate data issues.
"Our human review process ensures that we catch edge cases and maintain the highest quality standards. We never publish an analysis without human oversight."
— Petazu Data Team
Our Commitment to Transparency
We Don't Test Products
We analyze real user reviews, not lab tests or sponsored content.
We Don't Accept Bribes
Our rankings are never influenced by brand payments or sponsorships.
We Update Weekly
Our data is refreshed weekly to ensure you have the latest insights.