Jobble is a verifiable, established gig economy platform with significant traction ($12M+ funding, ~150k gigs filled, 14k partners), solving a genuine market problem. However, the submission quality is critically low, characterized by vague data ('leadership' listed as technology), lazy audience definitions ('everyone'), and hyperbolic/false claims ('most people have used my product'). While the underlying business reality warrants a high tier score (comparable to or exceeding the calibration baseline), the lack of effort and accuracy in the submission data necessitates a severe penalty to the Quality Factors, resulting in a score that reflects a legitimate business presented poorly.
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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