Case Study: Corporate Health Benefits Platform (Prixa)

A digital-first SaaS that centralizes corporate health benefits into one seamless platform

Context

  • Target user: Employees of enterprise clients (corporate health benefit users)

  • Business environment: Fragmented health journeys — employees accessing different providers across different channels → poor experience + high cost

  • Timing: Corporate clients started demanding measurable ROI & simplicity (post-COVID shift, heavy focus on cost efficiency)

Problem Statement

Employees and HR teams were struggling with a fragmented healthcare experience. They bounced between multiple apps, providers, and manual processes — causing low usage, low visibility, and high claim inefficiency.

We needed to unify the experience into a single digital entry point.

Success Definition

  • Primary KPI: User activation & usage (MAU / activation funnel)

  • Secondary KPI: Cost efficiency (infrastructure + delivery)

  • Time horizon: 3 months post-launch for first measurable adoption wave

My Role & Scope

  • Product Manager — responsible for strategy, problem framing, requirement definition, prioritization, stakeholder alignment

  • Directed ~25 cross-functional team members (engineering, design, QA, ops, infra)

  • Scope across legacy improvement + new product delivery

Constraints & Realities

  • Must continue supporting legacy stack (zero downtime allowed)

  • Limited infrastructure budget (cost pressure)

  • Extremely fast delivery window — first enterprise prospect pipeline already waiting

  • Strict compliance/legal requirements (health data)

Key Decisions & Trade-offs

Unified app vs separate modules

Options Considered: "Add modules to legacy" vs "build clean new SaaS"

Decision: New SaaS → easier to iterate, modern UX, clean data model

Risk Accepted: Migration friction + dual system period

Incremental rollout scope

Options Considered: Full feature parity vs prioritized 80/20

Decision: Ship 80% value first → faster time to market

Risk Accepted: Some stakeholders initially unhappy re: missing minor things

Infra cost model

Options Considered: Auto-scale infra vs reserved capacity

Decision: Optimized reserved capacity → 50% cost cut

Risk Accepted: Needed careful forecasting + usage modeling

Final Solution Summary

  • Delivered a single corporate health benefit SaaS product

  • Prioritized + shipped 45+ new features & bug fixes

  • Implemented Agile rituals + prioritization discipline to remove internal bottlenecks

  • Optimized infra + delivery model to drastically reduce costs

Validation: feature usage analytics, cohorts on activation, client feedback loops (direct with HR teams)

Impact

2,500+

New users within 3 months post-launch

50%

Faster time-to-market for new features

50%

Cost reduction in infra + dev spend

45+

New features & bug fixes shipped

Next Iteration / What I'd Do Differently

  • Introduce pricing experimentation (per member / per claim / per company tiering)

  • Stronger A/B testing protocols earlier

  • Invest in modular configurable benefit packages to accelerate enterprise onboarding

Project Info

Key Responsibilities

Technology