Gig work represents a material and behaviorally distinct income segment in 2025. This analysis provides a behavior-based way to identify and segment gig workers using verified wage inflows from linked bank accounts, allowing us to distinguish users who are economically reliant on gig work from those with incidental or supplemental gig income.
Full-time gig workers exhibit fundamentally different behaviors to part-timers across platform usage, income intensity, and payment cadence. Leveraging existing transaction data can help us identify potential new opportunities for existing and new product ideas. This work transforms gig workers from a loosely defined persona into a measurable, actionable customer segment that has already informed and guided product strategy and prioritization.
From a product perspective, the data analysis completed has provided the team with 4 buckets to vet and identify the best path forward.
These 4 buckets are:
Turned abstract transactions into a measurable cohort
Defined gig workers using verified income inflows and income reliance, giving product and data teams a shared, defensible segmentation.
Informed User Interview Questions
Translated insights into targeted interview prompts, enabling validation and opportunity discovery.
Informed product strategy and prioritization
Reframed gig workers as income-volatile users, guiding exploration of products focused on income smoothing, liquidity, and payment flexibility.
Unlocked adjacent product opportunities
Identified short-term staffing agency workers as a structurally similar segment, extending the impact beyond traditional gig platforms.