Case Study: Rebuilding Networking at Scale
I led the design of an AI-powered, self-serve networking experience for enterprise HR teams. Our product replaced tedious setup with a streamlined, outcomes-driven workflow. The project spanned 4 months with a multidisciplinary team, serving HR leaders at companies like Amazon and PayPal.
The Problem
Our company acquired an HR tech platform to accelerate growth, but its networking feature suffered from low adoption. Admins were overwhelmed by configuration complexity and lacked confidence, causing poor engagement and elongated onboarding.
We faced a crucial business risk: simply migrating and scaling the legacy setup meant propagating complexity, leading to disengagement and potential churn during the platform transition.
The goal was bold: create a new networking tool that worked out-of-the-box, was self-serve for admins, and scaled easily, with flexibility where it mattered. Key metric: make setup effortless and results trustworthy.
Design Principles
We led with opinionated defaults guided by research. Confidence over control shaped admin flows—fewer, clearer choices replaced endless options. Behaviors, not configuration, drove design. Admin and employee experiences were treated as equally vital.
Discovery & Insights
Research included a legacy audit, 12 customer interviews, support ticket analysis and user data. We learned that excessive customization hurt outcomes. Admins wanted reassurance, not control, while employees valued agency in networking choices.
Admins feared making mistakes and disengagement often went unnoticed. The solution reframed the product from a configuration exercise to launching a proven networking experience, removing unnecessary complexity and introducing intentional friction where custom setup was harmful.
Switching from ‘configuring a program’ to ‘launching an experience’ freed admins to focus on impact, not checklists. AI-driven defaults and simplicity became central to trust and adoption.
The Solution
We switched from multi-page setup to a streamlined, one-page admin experience. AI filled in program titles and matching criteria, hiding advanced options to subtly guide users toward best practices without removing flexibility.
Transparency became a foundation for trust. Admins could track matches, views, and user actions, while the new analytics dashboard offered clear insights: opt-in rates, profile completeness, match health, and more. The employee experience became participatory—users chose match frequency and partners, boosting engagement and buy-in.
Engagement safeguards prompted users to update profiles and nudge inactivity, automating health without increasing admin burden.
Design Challenges & Trade-Offs
Removing customization was met with resistance from power users. We countered by emphasizing data-driven defaults and introducing friction for advanced changes, positioning proven settings as the optimal path.
The trade-off: giving up perceived control for demonstrably better outcomes. We remained flexible but ensured smart defaults were the easiest way forward.
Success meant shifting the mindset from feature complexity to product confidence.
Impact
In the first rollout, setup time dropped 80%, program launches without success help doubled, and match rates and engagement soared across enterprise customers.
Admins reported newfound confidence launching networking programs, support tickets around setup fell, and participation became more consistent.
Our approach proved that simplicity, guided by insight, could outperform even the most flexible legacy tools.