Sentiment Tracking Dashboard
- Company
- Flashpoint.AI
- Duration
- Jan 2026 (2 weeks)
- Team
- Solo
- Role
- Design Engineer — UI/UX Design & FE Dev
Flashpoint.AI's clients run several research projects at once, each in its own tool, tracking its own topics and demographics. Movement across projects was the thing nobody could see — a topic's trend only existed within its own project, and comparative analysis only existed if someone built it by hand. I designed and shipped the dashboard that makes it the default view.
Some content shown in this project — screens, data, and events — is simulated for demonstration purposes. It does not reflect real product output or actual events, and shouldn't be taken as such.
Every Report Was a Snapshot
Each project's insights arrived as an individual research report. Answering "is this moving?" meant opening several of them, finding the same metric in each, and plotting it yourself. Comparing one project's topic against another's meant doing that twice and lining the results up by hand.
The reports weren't wrong. They just weren't built to be read against each other, and the work of connecting them fell on the user every single time.
The Trend Is Already Assembled
The dashboard turns filed reports into a live analytical surface, with topics on a shared timeline, segments a filter away, and projects readable side by side.
Trend, not snapshots
Selected research topics sit on one timeline, so a rise or a drop is visible before you read a single number.
Tailor the analysis to what you need
Filter by research topic, category, demographic, or region — the cross-analysis is a control, not a re-export.
Projects, side by side
Select the projects you want to compare and read them against a common scale, without reconciling two different report formats first.
Two Instruments, One Timeline
The dashboard collects data from two tools on the Flashpoint.AI platform. Each measures a different type of sentiment, but both track how a sentiment moves over time.
Tracking Poll
Measures how voters feel about a topic, sampled repeatedly over time.
Message Test
Measures whether specific campaign or marketing language actually lands with a target audience.
What the Dashboard Had to Satisfy
Movement at a glance
User goal
Understand how sentiment is moving without manually building a trend.
Business goal
Help clients move from newly fielded research to confident decisions faster.
Product goal
Make trend analysis the default by surfacing every topic as a time series first.
All in one
User goal
Compare results across studies without switching contexts.
Business goal
Increase product adoption by making the platform the primary workspace for ongoing research.
Product goal
Bring Tracking Poll and Message Test into a unified reporting experience with a consistent structure for comparison.
Answers, not datasets
User goal
Reach the specific insight that answers the question immediately.
Business goal
Reduce the analyst effort required to support reporting requests.
Product goal
Make insights instantly explorable through built-in dimensions instead of requiring exports or custom analysis.
Built for the Decision, Not the Dataset
The point is to help users decide faster, with better information. Rather than starting with raw datasets and requiring analysts to reconstruct the story, it surfaces the movement, highlights what changed, and provides evidence where it's needed.
Campaigns
See whether sentiment on an issue is moving, and whether the messaging is landing, while there's still time to change it.
Business research
Track consumer sentiment the same way — project to project, market to market, on one timeline.
The Final Dashboard
Selected topics appear on a navigable time-series table. Users filter by research topic, category, demographic, or region, or select the projects they want to compare — and the comparison is simply there, already built.
What Used to Take an Afternoon of Exports
Tool exports and written research reports still exist — they're still produced, and they still matter as the detailed record. What changed is the layer that sits on top of them.
| Task | Before | After |
|---|---|---|
| Check campaign health | Open the latest report and locate the relevant metrics | Open one dashboard and immediately see what changed |
| Compare projects | Review reports individually | Compare projects side by side |
| Answer stakeholder questions | Ask an analyst or create a custom pull | Filter the report to the needed segment |
| Decide next steps | Interpret charts before drawing conclusions | Start with surfaced insights and drill into evidence only when needed |
Interested in working together?
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