Your analytics product might be accurate and still fail users. This review finds where information gets misread, where decisions stall, and where the structure works against the people using it. Not a visual polish pass.
For teams building dashboards, reporting tools, or internal analytics products
A structural review of how your analytics product organizes information, supports decisions, and handles the gaps where users get stuck or misread results. Not a visual polish pass. Color, typography, and layout only matter after the underlying structure is sound.
Most analytics UX problems are not obvious on first look. They show up when a user tries to answer a real question and the product sends them in the wrong direction — or gives them confidence in a number they should be questioning, or buries the thing they actually need under layers they have to learn to ignore.
A provider-facing dashboard shows patient risk scores, care gaps, and utilization trends. Clinical leadership trusts the data. Care coordinators do not use it.
We would start by watching how coordinators actually interact with the product, not how they describe using it. In most cases like this the problem surfaces within the first session. A risk score displayed without context for how it was calculated or what action it implies is not a clinical tool. It is a number. Coordinators cannot explain it to physicians, so they stop looking at it.
The audit would identify every decision point where the interface creates confusion rather than clarity. Each finding comes with a prioritized recommendation and an annotated wireframe showing the specific fix. Not a general suggestion. A specific fix.
Fixed scope. No surprise hours. Work begins after agreement and scheduling.