Complex data. Interfaces that make decisions obvious.
SaaS product design is harder than consumer UX. Your users are professionals with specific jobs to do, they're using the product under time pressure, they have deep domain knowledge that shapes their mental model, and they'll judge you by how quickly they can complete their actual task — not how nice the onboarding looks. Dashboard interfaces fail in predictable ways: too many metrics on one screen, unclear hierarchy between primary and secondary information, tables with no clear action path, and charts that are visually impressive but don't answer the question the user is actually asking. We design SaaS products and dashboards around task efficiency first, visual polish second.
What's included
- Complex information architecture for data-dense products
- Dashboard & analytics UI design
- Multi-step workflow & wizard design
- Data visualisation for decision-making
- Role-based interface variations
- Onboarding flows that drive activation
How we deliver
- 1User research with power users & target roles
- 2Information architecture & navigation map
- 3Workflow wireframes validated with users
- 4Hi-fi dashboard & screen designs
- 5Data visualisation component library
- 6Developer handoff with interaction specs
Technologies we use
- Figma
- FigJam
- Recharts
- D3.js
- Framer
- Maze
- Hotjar
- FullStory
- Storybook
Why Origin for SaaS & Dashboard Design
Every chart answers a specific question
We map every data visualisation to the decision it enables before choosing the chart type. Dashboards that look impressive but slow comprehension are a design failure.
Designed for power users, not just new users
SaaS products are used daily by professionals. We design the efficiency layer — keyboard shortcuts, bulk actions, saved views — alongside the onboarding layer.
Role-based interfaces scoped from the start
Different roles have different primary tasks. We design role-based navigation separately, not as the same UI with items hidden.
Industries we serve
“Our analytics dashboard had 40 charts on one screen. Origin ran research with our power users, cut it to 12, and redesigned the hierarchy. Time-to-insight dropped from 4 minutes to 45 seconds by their own measurement.”
Frequently asked questions
- How do you approach a dashboard with many different metrics and data types?
- We start by asking what decision the dashboard is helping the user make. Every metric on the screen should either inform that decision or signal when something needs attention. We then prioritise by role: a CEO dashboard and a support team dashboard showing the same data need very different hierarchies. The process is: define decisions first, map metrics to decisions, design the hierarchy, then apply visual treatment. A dashboard that looks complex usually has a structural problem, not a visual one.
- How do you design for power users who know the product deeply?
- Power users are harmed by the same UX patterns that help new users: they skip onboarding, they already know the hierarchy, and they want the fastest path to their task. We design for two modes: guided (for users learning the product) and efficient (for users who know it). Keyboard shortcuts, bulk actions, saved views, and dismissible onboarding are part of the efficiency layer. Both modes are designed explicitly, not assumed.
- How do you design data visualisation that actually helps users make decisions?
- By understanding what question the chart is answering. Most dashboard charts are chosen for what data is available, not what the user needs to know. We map every visualisation to a specific question: 'Is this metric improving?', 'How does this compare to last period?', 'Where should I investigate first?' — and pick the chart type that answers that question fastest. A line chart for trends, a bar for comparison, a heatmap for frequency distributions. We avoid chart types that look sophisticated but slow down comprehension.
- We have a complex multi-step workflow — how do you design that without overwhelming users?
- Progressive disclosure: show the user only what they need for the current step, and indicate where they are in the larger process. We design wizard interfaces with a clear progress model, sensible defaults that reduce decision load, and the ability to save progress and return. Multi-step workflows fail when users can't see the end, can't save their progress, or are asked for information before they need it. We design around all three.
- Our SaaS has multiple user roles — how do you handle role-based UI?
- Each role has a distinct primary task and a different set of secondary tasks. We design role-based navigation separately — not the same navigation with some items hidden. We also design the permission model into the interface: a read-only user should never encounter an action they can't complete. Role-based UI is scoped and documented in the design system so developers implement it consistently.