Flowganise
Freelance UX Designer
UX strategy, wireframing, UI design
Figma, NuxtUI (Tailwind)
Background:
Flowganise had already built and launched V1 of their platform – an analytics tool that detects where sites are losing revenue, quantifies the loss and suggests fixes. This was enough to secure first round startup funding, but the founder was itching to keep moving.
They needed help figuring out what V2 should be before anyone wrote a line of code.
This project involved translating complex, data-heavy functionality into simple, decision-ready interfaces. I worked closely with the founder and lead developer, creating a design system and component library (based on NuxtUI / Tailwind CSS) to ensure every design was technically feasible and handoff-ready.
Above: Flowganise dashboard showing open opportunities.
Approach
Analytics tools have a reputation for being overwhelming. Lots of data, lots of dashboards, difficult to understand unless you know what you're looking at.
The idea behind Flowganise is the opposite: it does the analysis for you and tells you what to fix.
The trick was translating a mountain of incomprehensible data into something that felt effortless to a time-poor business owner. They just want to know what's broken and how to fix it.
MVP definition
We workshopped the product together to scope out what to include, how everything connects and what technology is needed to support it.
A Lovable mockup was used to pull ideas together and rapidly make changes, then we stripped it right back to the essentials.
Wireframing
My priority was nailing a clear information hierarchy, intuitive controls and simple language. Their users were confused and frustrated by the analytics tools they were using – we didn't want to add to the noise.
3
Checking In
At this stage the founder was sharing WIP designs with existing customers to help validate the direction before jumping into UI.
We also had regular syncs with the developer throughout to stay grounded in what was buildable.
4
UI and Prototypes
A tokenised design system was build in Figma based off NuxtUI (a Tailwind library), customised to suit the Flowganise brand.
We continued checking in with customers as prototypes took shape, so by the time we reached handoff, we had full confidence in the direction.
Above: An issue detected! The data is there to dig into, but the root cause is what customers need to know most.
Above: Supporting data for the detected issue – clearly presented with a simple explanation of each graph.
Above: The AI analyses data, screenshots, screen recordings and heat maps then generates suggestions on how to fix the problem.
Above: Jumping into a suggestion explains what to do, the UX principles behind why it should work, and a mockup of what the updated screen should look like.
Impact
Version 2 is currently in beta with customers currently signing up for early access.
The rebuild gave the product a coherent structure, some powerful new features and a UI language the developer could implement and extend as the product continues to grow.
Want the nitty gritty?
This case study's pretty light on detail—NDAs and all that. Get in touch if you want to talk shop.