Round 1 Winners!
Proof of Usefulness Report

4-Tell

Analysis completed on 3/23/2026

+112
Proof of Usefulness Score
Gaining Momentum

The submission for 4-Tell describes a collaborative commerce and machine learning platform with a 2009 launch date and a team of 30. However, the application contains vague details, greatly exaggerated claims regarding audience reach ('everyone', 'most people have used my product'), and confusing revenue metrics ('all time marketcap: 2500000'). Because of the lack of verifiable data and poor response quality, the quality factors are heavily penalized, placing the final score on the lower end of the calibration scale for established projects.

Ready to Compete for $150k+ in Prizes?

Move this data into a HackerNoon blog draft to become eligible for your share of $150k+ in cash and software prizes

View All Reports

Score Breakdown

Real World Utility+50
Audience Reach Impact+10
Technical Innovation+22.5
Evidence Of Traction+18.75
Market Timing Relevance+15
Functional Completeness+1.25
Subtotal+117.5
Usefulness Multiplierx0.95
Final Score+112

Project Details

Project URL
Description
The technologies and digital touchpoints that shoppers utilize along their purchasing journey, require a new interaction model for truly effective digital commerce. We believe commerce must be guided by people and supported by machine-learning technologies to enable true collaboration - fostering loyalty, building efficiency and profitability. Where collaborative technology is the engine to engage, guide and capture shopper-specific data as they navigate across a complex network of digital elements; the data gathered and generated creates an opportunity for people to engage in efficient, effective, and personalized collaboration with every customer. Understanding shopper behavior is a critical element to leverage as you enable your salespeople to join the digital conversation. Our Collaborative Commerce Engine enriches real-time shopper data and displays it in user-specific profiles through our Smart Commerce Platform. In showcasing shopper behavior and buying signals, we inspire sales to collaborate more effectively with every individual shopper - driving loyalty, inspiring confidence and, ultimately, boosting business results.

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