GoNsave provides anonymized data analytics for gig platforms, focusing on the movement of people and goods in on-demand delivery and ride-hailing services. This data enables businesses to enhance operational efficiency and improve fleet retention by increasing gig worker engagement and optimizing costs.
Funding
Funding not disclosed
Founders
Product
Problem
Gig economy platforms often lack real-time visibility into competitor pay rates and market dynamics, leading to inefficient worker acquisition and retention strategies. Operational teams struggle to balance competitive pay with cost efficiency, resulting in overspending during peak hours or worker shortages during busy periods. The absence of actionable market data hinders informed decision-making, impacting profitability and market share.
Solution
GoNsave provides gig platforms with an AI-driven pricing recommendation engine that aggregates and analyzes real-time market data, including competitor pay rates, government reports, and demand trends. The platform delivers actionable insights and tools to optimize pay rates, ensuring cost efficiency without compromising worker supply. By tracking and integrating pricing from market players, GoNsave enables platforms to proactively adjust pay strategies, enhance worker engagement, and optimize operational costs. The system's dynamic pricing recommendations adapt to fluctuating demand, market competition, and broader industry pricing shifts, ensuring real-time responsiveness to ever-changing conditions.
Target Audience
GoNsave primarily serves operational teams at food delivery, logistics, and ride-hailing platforms seeking to optimize gig worker pay, improve worker retention, and reduce operational costs.
Features
- Aggregated market data: Tracks and integrates real-time pricing from market players.
- Government reports: Considers regulatory and economic factors impacting pricing.
- Weather & traffic data: Adjusts pricing based on external conditions affecting ride demand.
- Demand trends: Identifies peak hours, historical fare fluctuations, and seasonal variations.
- AI-driven pricing recommendations based on demand patterns and external conditions.
- Real-time monitoring of competitor payout rates to prevent driver churn.
- Customizable dashboards for visualizing key performance indicators and market trends.