Context
N!mbus was losing customers after demos. Sales could sell the product, but users couldn't navigate it independently—leading to significant post-demo drop-off (exact rate tracked by sales team), high churn risk, and growing support costs.
I led a full redesign to close this gap: rebuilt the information architecture, designed structured onboarding, improved accessibility (WCAG 2.1 AA), and established a design system from scratch.
High post-demo drop-off
Support overload
Hidden premium features
Churn vulnerability
Spreadsheet workarounds
Reduced drop-off
Fewer support requests
Increased feature adoption
Lower churn risk
MRR growth enabled
Before
N!mbus had 5,000+ paying users—but 63% had never discovered its most valuable feature
While sales demos worked, users struggled alone. They couldn't find location analysis even after months of use, filters were buried behind popovers with no visibility of what was applied, and the site info panel required multiple clicks just to see basic property data. Without clear navigation or trust signals, users abandoned the platform or defaulted to spreadsheets to validate decisions. In a high-stakes property market, this hesitation meant lost deals and churn.
N!mbus before redesign
Dense left navigation with unclear priorities • Data-heavy panels without visual hierarchy • Map layers buried in nested menus • No clear entry point for new users
Constraints & trade-offs
Why redesigning this was risky
Redesigning a live B2B product risks frustrating existing users and increasing churn. N!mbus was revenue-generating with paying customers, limited research access, evolving requirements, and real technical constraints. Stakeholders across sales, product, and engineering had competing priorities. The challenge was improving clarity without disrupting established workflows - every decision carried commercial consequences.
Navigating competing priorities:
Conflict:
Engineering wanted to ship incrementally; Sales wanted all features at once for demos.
My approach:
Created a phased rollout plan with high-fidelity prototypes that sales could demo while engineering built incrementally. This gave sales what they needed (demo-able designs) while protecting engineering velocity.
Result:
Sales used prototypes to close deals (contributing to 56% ARPU increase) while engineering maintained quality and pace.
Research approach
Combined qualitative research (user interviews, usability sessions with screen recordings) with behavioral data analysis and affinity mapping to identify patterns across diverse user types.
The turning insight
Confidence - not features - was blocking decision-making
Across interviews, usability sessions, and behavioral data, one pattern emerged: users hesitated because they didn't trust what they were seeing. They needed to understand what they were looking at, why it is important, and whether it was safe to act on - without a sales call.
“I didn’t realise map layers (Location analysis) were included - even after a year of using the product.”
Existing user
“I wasn’t sure whether it missing data - or if the system was still loading.”
Existing user
“I needed clearer signals to understand what each action would actually do.”
Existing user
Execution under constraints
Designing clarity in a moving system
With shifting requirements and competing priorities, I couldn't wait for perfect research. I reduced risk through fast prototypes, lightweight usability sessions, and clear trade-offs. As the redesign progressed, I established a design system to prevent new complexity.
Exploring filter patterns
Organising 40+ filters without overwhelming users required testing multiple approaches. I explored how different patterns affected the speed and confidence of property searches. Testing version 2 with users revealed the role-based approach created barriers—catching this before development saved months of building the wrong solution.
All filters visible
All filters expanded by default. Every option immediately accessible.
❌ Users overwhelmed by 40+ options
❌ Couldn't distinguish basic from advanced
❌ Abandoned before filtering
Role-based tabs
Filters organised by user role (Developer | Surveyor | Investor).
❌ Users didn't identify with role labels
❌ "I'm both a developer AND surveyor—which tab?"
❌ Created barriers instead of clarity
Progressive disclosure
Collapsible categories + keyword search + background processing.
✅ Users started filtering immediately
✅ Search revealed advanced options when needed
✅ Favourites for frequently used filters
From features to decisions
Designing for real decision-making
N!mbus had grown feature by feature. I mapped the real decision journey users followed—scanning, building confidence, validating constraints, taking action.
Users included developers, surveyors, investors, and planners with different goals. I focused on patterns: progressive disclosure, site cards for quick scans and deep dives, mobile views for on-site decisions. This reduced cognitive load without sacrificing depth or speed.
Desktop and mobile views
Comprehensive property data accessible on-site via mobile or during desk research on desktop. Designed for quick scanning and deep analysis depending on user context.
The moment of truth
Would 5,000+ users accept the change?
Redesigning a live product with paying customers meant every change carried risk. We rolled out the new filters first to measure impact.
The result: Support tickets dropped 36% in the first month. Users discovered features they'd never found before—without asking for help.
After
A product users could navigate and trust on their own
Two major improvements shipped while broader evolution continued. Sales leveraged detailed prototypes to close deals on future capabilities, generating revenue before launch. Capabilities became discoverable and trustworthy, with users relying less on sales walkthroughs
Business impact
From sales dependency to product-led growth
High-fidelity prototypes became a sales tool before launch—prospects could visualize the value and commit to future capabilities, generating revenue before a single line of code shipped.
Within one year (FY2024 → FY2025):
~2× ARR growth with parallel MRR increase
+56% average contract value
33% reduction in user friction, 25% increase in usability satisfaction, 3× growth in advanced feature adoption
36% reduction in support tickets, freeing ~40% of sales capacity for expansion vs. onboarding
"The new interface finally makes sense—I found features I didn't know existed that are saving me hours every week."
— Surveyor, existing customer
"For the first time, I didn't need to call support during my trial."
— Residential Developer, new customer
"We can finally upsell advanced packages because customers can actually use them."
— Sales Director
What this taught me is.
Every challenge can show you more perspectives
The deeper I got into the work, the more I understood that the problem was never about features—it was about confidence. Users couldn't find what they needed or trust it enough to act. You don't need everything at once. You need the right thing at the right moment.
Early prototypes becoming a sales tool was unexpected. But it proved: if design builds confidence for real users, it builds confidence for prospects too.
What's next: AI-powered filters, AI-powered recommendations, and self-serve onboarding—all following the same principle: meet users where they are, not where the system expects them to be.
More designs
Let's connect
Feel free to contact me if having any questions. I'm available for new projects or just for chatting.
© Nataliia Yarko, 2025