The design journey for Referral Stack began with a commitment to deeply understand the real challenges faced by SaaS teams, digital creators, and affiliate marketers in managing referral and affiliate programs. I initiated the process by conducting comprehensive stakeholder interviews, engaging with both business owners and end users across a spectrum of company sizes and industries. Through these conversations, I uncovered that over 80% of participants struggled with manual tracking and payout processes, while 65% expressed frustration with delayed or inaccurate payments pain points that consistently hindered their ability to scale and trust their affiliate programs.

To further ground our approach, I meticulously mapped user journeys for each primary persona: SaaS founders who needed to launch programs quickly, marketers who required granular analytics, and affiliates who prioritized transparent, timely payouts. By synthesizing these findings, I developed detailed personas and user stories that highlighted not only operational bottlenecks but also the emotional toll of unreliable tools feelings of frustration, lack of control, and missed growth opportunities.

Below are FigJam screenshots illustrating the user flow.

Next, I turned to the competitive landscape, conducting an in-depth benchmarking exercise against leading platforms such as PromoteKit, ReferralCandy, Tolt, and Rewardful. The analysis revealed several critical gaps: competitors often required 20–60 minutes for setup, lacked seamless PayPal integration, and offered only basic or manual fraud prevention. Most platforms also failed to provide a unified, modern interface or support for dark and light modes, which are increasingly expected by today’s users. These insights directly informed our product priorities, pushing us to differentiate Referral Stack with instant onboarding (under 10 minutes), robust PayPal and Stripe support, real-time automated fraud detection, and a flexible design system.

With clear objectives in place, I spearheaded the creation of a comprehensive design system in Figma. This system included reusable components, a carefully curated color palette, accessible typography, and tokenized design variables to ensure scalability and consistency. Both dark and light modes were meticulously crafted to accommodate user preferences and accessibility needs. Every aspect of the design system was thoroughly documented, enabling seamless collaboration and alignment across engineering, product, and marketing teams. This approach significantly reduced design-developer friction, accelerating our build cycles and ensuring pixel-perfect implementation.

Prototyping was an iterative, data-driven process. I developed interactive prototypes for core flows onboarding, dashboard analytics, affiliate portals, and payout management and conducted usability testing with 12 representative users from our target segments.

The feedback was illuminating:

Users consistently valued clarity in navigation, the ability to see real-time performance metrics at a glance, and the simplicity of configuring commission structures. Based on these insights, I refined the user flows, reduced unnecessary steps, and surfaced key actions and data points to minimize cognitive load.

When it came to implementation, the focus was on delivering a truly unified and intuitive experience. Referral Stack’s onboarding was designed to be no-code and frictionless, allowing businesses to launch affiliate programs in less than ten minutes a dramatic improvement over competitors. The platform enabled fully customizable commission structures, supported branded affiliate portals, and allowed for seamless management of multiple programs. Real-time fraud detection and automated payouts via Stripe and PayPal were integrated at the core, with every workflow optimized for both desktop and mobile use.

Throughout the project, cross-functional collaboration was key. I regularly shared the evolving design system and prototypes with the broader team, facilitating rapid feedback and iteration. Detailed documentation and design specs ensured that engineering and QA could execute efficiently, while regular check-ins with stakeholders kept everyone aligned on goals and progress.

The result was a product that not only addressed the acute pain points identified in research but also set a new standard for usability and scalability in affiliate management. Early users reported being able to launch programs 3–5x faster than before - beta rollout test, with a 30% reduction in support queries related to onboarding and payouts. The modern, accessible interface and robust automation features drove higher affiliate engagement and satisfaction, positioning Referral Stack as a trusted solution in a fast-growing $12 billion industry.

Note: User testing and insights are based on feedback from our beta users. The product has not yet been released to the public; we are still actively testing with our beta and waitlist users.