Our Methodology

Transparency matters. Here's exactly how we research, evaluate, and recommend products.

Our Research Process

1. Data Collection

For each product category, our AI system aggregates data from multiple sources:

  • User Reviews: We analyze reviews from major retailers (Amazon, Best Buy, etc.) and review platforms.
  • Expert Reviews: We incorporate findings from professional review sites and publications.
  • Technical Specifications: We gather detailed specs from manufacturer documentation.
  • Pricing Data: We track prices across multiple retailers over time.

2. Analysis & Synthesis

Our AI processes this data to identify:

  • Common praise and complaints across reviews
  • Performance patterns and reliability indicators
  • Value proposition relative to price
  • How products compare within their category

3. Recommendation Generation

Based on our analysis, we identify top picks for different use cases and budgets. We aim to recommend:

  • A "best overall" option for most people
  • A "best value" option for budget-conscious buyers
  • Specialist picks for specific needs (e.g., "best for workouts")

4. Continuous Monitoring

Our recommendations aren't static. We continuously monitor for:

  • New product launches
  • Significant price changes
  • Emerging quality issues (recall notices, widespread complaints)
  • Updated reviews and testing from expert sources

Evaluation Criteria

While specific criteria vary by category, we generally evaluate:

Performance

Does the product do what it's supposed to do, and do it well?

Reliability

Does it hold up over time? Are there common failure points?

Value

Is it worth the price relative to alternatives?

User Experience

Is it easy to use, set up, and maintain?

What We Don't Do

  • Accept payment for reviews: We never accept payment or free products in exchange for coverage or favorable reviews.
  • Let commissions influence picks: We recommend the best products regardless of affiliate commission rates.
  • Ignore negative feedback: If a product has significant issues, we report them — even if it's a top seller.

Limitations

We believe in being upfront about our limitations:

  • We don't hands-on test: Unlike some publications, we don't physically test every product. Our analysis is based on aggregating existing data.
  • AI isn't perfect: While our AI is sophisticated, it can miss nuances that a human expert might catch.
  • Coverage gaps: We focus on popular product categories with substantial data. Niche products may not be covered.

Feedback Welcome

If you spot an error, have a product suggestion, or disagree with a recommendation, we want to hear from you. Email us at [email protected].