The challenge
Every user was pushed into a funding application
The original onboarding forced every user into the same application flow, whatever their intent, eligibility, readiness or understanding of funding types. It was optimised for data capture, not for confidence or outcomes.
- Users didn't understand funding categories and often chose the wrong path.
- Low-quality leads clogged the system and the funding managers handling them.
- People looking for insights or savings hit friction they never needed.
- The business needed better matching, not more applications.
“It's less steps than what I would have expected. It's really quick.”
My role
Lead designer on onboarding, from discovery to a design system fit for AI.
I ran usability testing, mapped the end-to-end funding journeys, designed the new flow and its AI assistant, and used the rebuild to reset the design system foundations and test them against accessibility standards.
The approach
A system, not a form
- 01
Discovery across regions
Usability testing with business owners in several regions to understand differences in data availability, expectations and tolerance for effort, while keeping one consistent experience.
- 02
Designed for outcomes, not questions
I worked backwards from what funding managers and lenders need to make a decision, so we still captured high-quality matching data without asking for all of it upfront.
- 03
From “what funding?” to “what are you trying to achieve?”
Users struggled with the language of funding. Asking about goals let them drive the journey, feel heard, and gave machine learning a better signal to match on.
- 04
Value beyond funding
People not ready for funding now get business insights and savings opportunities, creating value earlier and keeping them engaged for the long term.
Key features
What shipped
Smarter handling of low-quality leads
We check eligibility straight away. Leads that won't get funded are offered solutions instead of an application they'd be denied. Fewer applications, higher success rates.
An AI funding assistant
Reassurance and support throughout, instant feedback on the business, and a familiar face for returning users. Companies House and Creditsafe data build a company overview and Swoop score.
Conversation over navigation
Users told us the platform felt overwhelming. Letting them direct the journey through conversation cut the noise and removed manual funding-type selection.
Micro-interactions and accessibility
Clear focus and next action, the keyboard ready with a sentence already started, and checks on colour, spacing and copy so the flow passes accessibility marks.
Results
onboarding steps, with high-quality matching data still captured
drop-off after UX audits, service redesign and mobile optimisation
manual overrides in funding managers’ workflow
new design system foundations, ready for an AI-led platform
