The submission represents a legitimate, established quantitative investment firm (Quantbot Technologies), but the Proof of Usefulness is severely impacted by low-quality, inaccurate, and 'troll-like' responses. Claims such as 'everyone' being the audience and 'most people have used my product' are objectively false for a specialized B2B/institutional trading firm. While the firm itself has significant history (founded 2009) and team size (~350), the submission fails to provide verifiable evidence, confuses metrics (listing 'marketcap' for a private partnership), and lacks professional detail, resulting in a minimum baseline score heavily penalized by quality factors.
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Score Breakdown
Project Details
Algorithm Insights
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