Quick read
How to read amazon.science quickly
amazon.science looks like technology & computing. Traffic signals point to roughly 398.8K monthly visits. Current AI trust scoring is 5/100.
What to do next
- The stack appears to include Unknown.
- Open the Traffic tab if you need audience scale and geography before outreach.
- Open the Business tab if trust, monetization, or positioning is your first decision filter.
Provider Completeness
45/56 fields populated (80%)
Providers with missing fields
View field-level status
visual: 4/4
All expected fields present
meta: 3/3
All expected fields present
seo: 5/5
All expected fields present
dns: 4/4
All expected fields present
ads: 0/5
Missing: isAdvertiser, advertiserIds, advertiserNames, resultCount, transparencySignals
publisher: 2/5
Missing: adSystems, directCount, resellerCount
files: 2/3
Missing: robotsSitemapUrls
traffic: 10/10
All expected fields present
whois: 6/6
All expected fields present
radar: 2/4
Missing: categories, sourceTimestamp
ai: 7/7
All expected fields present
Why this module matters
Business signals help answer “is this a real opportunity?”
Use the business tab to understand trust, monetization, audience fit, and brand posture before you spend time on outreach, partnerships, or competitive teardown work.
- Trust score and sentiment are your first risk screen.
- Business summary and audience notes speed up qualification.
- Ads and monetization patterns reveal how the site captures value.
Business Intelligence
Business Profile
Amazon Science is Amazon's corporate research division showcasing AI/ML innovations, particularly highlighting their NFL Next Gen Stats partnership that processes millions of tracking data points using 75 machine learning models on AWS to analyze player movements in real-time.
Classification
Trust & Risk
Trust Assessment
Publisher Monetization
Monetization Signals
AI Visual Analysis
IAB Taxonomy
Business Insights
Business Model
Corporate R&D / Technology Research model detected
Trust Level
Low trust with 5/100 score
Audience
Researchers, engineers, potential hires, tech media, enterprise customers interested in AWS AI/ML capabilities, and sports technology enthusiasts
Keep exploring
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