Nexus Insurance
Redesigning a data-heavy quotation workflow for insurance brokers around their two goals: quick simulations and formal quotes.
Insurance
B2B
UX/UI
User Research
This case study is based on professional experience in a regulated enterprise environment. Visuals have been deliberately generalized and simplified. The content reflects my design approach and decision‑making.
Role
Team
Project Manager
2 Developers
Insurance brokers (testing and feedback)
Me
Platform
Desktop
Duration
4 months
Insurance brokers quote group insurance for companies, covering several employee categories and coverages in each quote. The existing tool was outdated and fragmented: no status overview, limited validation, and no specific flow based on goal/task.
As the sole product designer, I redesigned the quotation tool around two goal-based flows and a real-time dashboard, turning a fragmented, error-prone process into one built around how brokers actually work.
Impact 1
Shipped and adopted
Launched for insurance brokers in several European markets and adopted after release.
Impact 2
Faster quotation process
Broker-reported: quote completion dropped from ~1 hour to ~30 minutes with the two dedicated flows and the step-by-step approach.
Context
The problem: two goals, one flow, no overview
The existing quotation tool was outdated and fragmented, and did not offer an overview of the tasks and their status.
A group quote isn't one person and one policy: it covers a whole workforce, split into employee categories, each with its own plan design and coverages.
Brokers used the platform for two distinct purposes: simulating a quote and generating a formal one.
A single shared flow meant they had to manually check which mandatory fields applied to their task.
For the business, every expired or incomplete quote was a potential lost deal.
Where Nexus sits
Group insurance runs through four stages: quote, contract setup, employee administration, and claims. Nexus covers the first one, where the deal is won or lost, so speed and accuracy here shape everything that follows.
Broker task analysis
Main findings
Finding 2
No visibility over active quotes
Brokers were missing time-sensitive items. No real-time overview of where quotes stood, what needed action, or which submissions were at risk of expiring.
Finding 3
Complexity without structure
Dense input fields made data entry overwhelming and error-prone, lacking guidance on progression or validation to catch mistakes before submission.
The real problem: the system treated two different tasks the same way, and gave brokers no overview of their work.
My role
How I solved it
Discovery
Starting from the brief, I worked with the PM to understand broker workflows and map where the process broke down.
Design
I led the design development, owned the interaction model and key structural decisions.
Validation
I ran 8 semi-structured sessions with brokers across three focus areas.
Handover
I prepared documentation and assets for the development handoff.
Design direction
Three decisions, one structural logic
The three findings pointed directly to three design principles that became the foundation of the solution.
Before
One long form, with every field marked for either simulation or formal quote.
After
Two entry points. If a simulation has been run, its fields carry over into the formal quote.
Each quote shows its status and next action; expiring quotes are flagged first.
Grouped steps with a progress indicator and inline validation before submission.
Testing against the client's preference
I also designed a single-page form, closer to the old tool, which the client preferred. Testing both with brokers showed the step-by-step flow was clearly easier to understand and less error-prone, which gave me the evidence to override that preference.
Research and validation
Validating the decisions with brokers
8 semi-structured usability sessions conducted with brokers around three focus areas, each tied directly to a key design decision.
Method
Semi-structured interviews
Outcome
8/8 Brokers navigated the two flows without guidance during usability testing, confirming the structure matched their mental model from the first interaction.
Research focus
Focus 1: The two flows
Validate whether brokers immediately understood the distinction between simulation and quote without explanation.
Finding: 8 out of 8 brokers understood the difference and set the right expectations for each flow.
Focus 2: The dashboard
Test whether the status overview and next-action CTAs gave brokers enough clarity, especially if expiring quotes were visible enough.
Finding: Expiring quotes were being missed — action labeling was adjusted, directly shaping the final prioritization logic.
Focus 3: Step-by-step vs one-page form
Identify which approach (single page vs multi-step), testing how they could navigate data entry more accurately.
Finding: Step-by-step was clearly better understood and less error-prone, overriding the client's one-page preference with evidence.
Outcome
What changed
The redesign changed not just how brokers generated quotes, but how they thought about the task itself.
By separating simulation from formal submission and giving brokers a clear overview of their work, the tool became a genuine operational support.
Reflections
What I learned
This project reinforced that simplifying enterprise software doesn't mean reducing complexity: it means structuring it.
Designing for brokers required respecting domain rules while creating systems that guide, rather than constrain, user behavior.
It also showed the value of letting research make the call. The step-by-step vs one-page decision wasn't resolved by opinion, it was resolved by putting both in front of brokers and observing what happened. That's a more powerful argument than any design rationale.
What worked well
Designing for the working day, not just the form
The dashboard turned a data-entry tool into a workspace brokers could run their day from.
Changing course on test findings
When brokers missed expiring quotes in testing, I changed the labels instead of defending the first version.
What I'd do differently
Measure long-term impact
I’d have set up post-launch monitoring with the team to see how the gains held up over time and spot new friction early.
Push for a longer discovery phase
The brief-led process meant limited time to understand broker workflows before designing. More structured discovery upfront might have surfaced the simulation vs quote distinction even earlier.
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