Jason Spidle

Principal product designer

Beacon FC

Scouts can review player sentiment and the reports behind it.

Role
Design lead
Studio
Blueshift, 2025
Scope
Dashboard, Search, Analysis
Industry
Healthcare, SaaS

I led design of the dashboard, search, and player comparisons. I used a consistent table layout for sentiment and scout activity, with source discussions linked from each generated summary.

Beacon FC is an anonymized version of an insights product I designed for a life sciences company. I changed the domain and data to soccer scouting to protect confidential information. The design problem and my role are the same.

Beacon FC dashboard with discussion totals, auto-generated highlights, and the roster sentiment table split into my players and rival players
The prototype shows what scouts are saying about each player, with links back to the source reports. Navi, the AI assistant, answers questions about what's on screen. Open the prototype in a new tab
Two Navi answer panels side by side. One explains what is driving Elias Braun's positive sentiment, with an insights summary, three drivers carrying sentiment chips, and the top scouts discussing him. The other ranks the six scouts most active on under-21 prospects by mentions, each with a sentiment chip
One answer lists sentiment drivers first, followed by the scouts discussing them. The other ranks scouts by activity and shows mention counts and sentiment in fixed columns.
The player panel shows what's behind a drop in sentiment, with a link from each post to its source report.
Navi compares Idris Falk and Mateus Oyelaran in a written summary, with paired charts for mention counts and sentiment.
Adding a third player updates the combined analysis, and scouts can save the whole comparison as a named report.
Search labels generated summaries and groups the source posts into tabs so scouts can check the answer.
Beacon FC drawer for Toma Vasquez with his sentiment split and analysis, linked by curves to three scout posts tagged by tone
Scouts can check the generated analysis against the source posts for each sentiment finding.