Our Process

A transparent look at how we turn millions of real conversations into actionable product recommendations.

1

Data Collection

AI agents continuously monitor real discussions

What We Collect

  • Product recommendations from Reddit threads and comments
  • Context around each mention (why they recommend it, use cases)
  • Community engagement signals (upvotes, replies, awards)
  • Source community expertise level (r/audiophile vs r/AskReddit)
# Example data point
source: "r/headphones"
product: "Sony WH-1000XM5"
sentiment: "positive"
context: "Best ANC I've ever used, comfortable for 8hr work days"
upvotes: 847
replies: 23
2

Sentiment Analysis

Understanding the nuance behind every mention

Not all mentions are equal. Someone saying "I returned my XM5s" counts differently than "The XM5s changed my life." Our AI analyzes the emotional context of every mention.

Positive

"This is the best purchase I've made this year"

Mixed

"Great sound but the app is frustrating"

Negative

"Returned after a week, uncomfortable and overpriced"

What We Extract

Pros (commonly praised)

  • • Build quality
  • • Battery life
  • • Sound quality
  • • Comfort for long use

Cons (common complaints)

  • • Price point
  • • App quality
  • • No water resistance
  • • Touch controls sensitivity
3

Ranking Algorithm

Weighted scoring that reflects real-world value

We combine multiple signals into a single score that reflects how highly real users regard each product.

Ranking Factors

Positive Sentiment Ratio 35%
Mention Volume 25%
Community Expertise 20%
Engagement (upvotes, replies) 15%
Recency 5%

No Paid Placements

Our rankings are 100% based on user sentiment. Companies cannot pay for higher placement. The algorithm treats all products equally.

4

Continuous Updates

Rankings that evolve with real-world feedback

Products change. Quality control issues emerge. New versions release. Our AI continuously monitors discussions to keep rankings current and relevant.

What We Detect

  • Quality control issues
  • New product launches
  • Shifting user sentiment
  • Long-term reliability reports

Update Frequency

  • New data collected daily
  • Rankings recalculated weekly
  • Major issues flagged immediately
  • Historical trends preserved

See the difference for yourself

Browse our categories and discover products that real people genuinely recommend.

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