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What we learned from Data Analytics YC applications
Aggregate insights from real applications roasted on YC Roaster — the patterns YC partners look for, and the weaknesses that come up over and over.
Apps analyzed
11
Average score
3.12 /5
Updated
Jun 15, 2026
Score breakdown — Data Analytics average
App Completeness3.91/5
Early Traction2.50/5
Team Quality3.80/5
Market3.36/5
GTM2.52/5
Scalability3.40/5
Monetization2.35/5
Biggest weaknesses
Where Data Analytics applications consistently fall short.
- 1. Monetization2.35/5
- 2. Early Traction2.50/5
- 3. GTM2.52/5
Strongest dimensions
Where Data Analytics applications tend to do well.
- 1. App Completeness3.91/5
- 2. Team Quality3.80/5
- 3. Scalability3.40/5
Score distribution
0-1
1
1-2
0
2-3
0
3-4
10
4-5
0
What our AI judge actually said
Anonymized critique from real Data Analytics applications (shared with founder consent).
“You built a working product in a month but have zero revenue, no usage metrics, and no idea who will actually pay for this.”
6.3/10·Impressive finance expert who can ship fast, but merger arb feels like a feature, not a company.
“You submitted a blank application with just a header, a billion person TAM claim tells us nothing about your actual product or customers.”
0.0/10·Complete the application with real answers before reapplying, we cannot evaluate a company name and tagline alone.
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