Round 1 Winners!
Proof of Usefulness Report

SuppleMetrics

Analysis completed on 3/13/2026

+85
Proof of Usefulness Score
You're In Business

The project concept addresses a relevant market need for verified career metrics in the SaaS industry, but the submission severely lacks verifiable data. Claims such as 'most people have used my product' are entirely unrealistic, and the response quality is exceedingly poor, citing 'Internet' for tech stack and 'everyone' for target audience. With 'marketcap' listed as revenue, it implies a crypto token project or a severe misunderstanding of business metrics. Minimal verifiable traction and highly vague answers place this firmly in the lowest scoring tier.

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Score Breakdown

Real World Utility+50.0
Audience Reach Impact+1.0
Technical Innovation+1.5
Evidence Of Traction+1.25
Market Timing Relevance+20.0
Functional Completeness+0.25
Subtotal+74
Usefulness Multiplierx1.15
Final Score+85

Project Details

Project URL
Description
SuppleMetrics is a career performance metrics platform, enabling senior SaaS professionals to differentiate themselves based on verified career history metrics. We help capture, verify and analyse individuals' historical performance data, providing valuable insights that help search firms position for better roles, support the candidate's interview process and improve the remuneration on offer. Every customer receives their own Metrics-Bio, which significantly enhances a resume or profile with hard data (verified as part of the service), and a powerful narrative that emphasises impact patterns and interprets trends in the users data. Dashboarding then gives users the ability to benchmark themselves with peers, by sector and metric category, better preparing them for important meetings. Our AI will then deliver ongoing insights, imminent webinars, and professional training suggestions based on user metrics falling into lower quartiles for example. As well as being valuable to individual professionals, SuppleMetrics data is important to recruiters & hiring managers because applicants rarely present their prior work history in verified data form, which is after all, the performance language that they will likely be managed by on a daily basis in their new role.

Algorithm Insights

Market Position
Growing utility with room for optimization
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline