Capture reality. Prioritize correctly. Validate early.
Unify raw feedback, automate inbox triage, and test narratives before committing to discovery.
1. Gather Feedback
Feedback
Intake, triage, cluster, synthesize — the continuous feedback loop
118 of 229 items
Merged accounts hide hypotheses; discovery signals drop
After we added the workspaces and tenants to the system most things have get fixed. One thing still broken: Hypotheses. When a user gets merged into an existing account the existing hypotheses are not visible to him. Also the signals deviate. In the discovery area the signal is reduced to 0 (and had values before). In the signals it still shows the correct number (thats good and correct).
Add Ctrl/Cmd+Enter to submit modal messages
For modals that just accept a message it would be very good to have a STRG + ENTER action (analog for iOS) to quickly close the tab and finish the editing action.
Parallel generation race condition
When two browser tabs are open on the same theme, ai starts generating the learning - this happens in parallel - but it shouldn't. This is a race condition. One browser tabs / UI must win. The issue might also besides additional AI costs that orphaned items are generated.
Sitewide SEO metadata and structured data issues
### **Critical Issues (must fix)** - **Duplicate title tags across all pages** — Every page except /blog and blog posts uses the identical title...
Feedback isn't just a ticket
User feedback isn't meant to sit in a siloed support queue. It is a critical signal that informs the continuous product loop.
By routing feedback through the Signal layer, Outcomet can:
- Surface recurring thematic complaints instantly.
- Prioritize discovery based on real user volume.
- Connect qualitative issues with quantitative usage drops.
The inbox becomes a structured pipeline, reducing manual triage and accelerating insights.
2. Validate with Stories
Stories
Manage narrative arcs and aggregated analytics
Stories Catalog
An early signal collector
A story isn't just a marketing asset—it's an early signal collector. You push something out into the wild and observe what comes back to validate early hypotheses.
- Is there a real need?
- Do people actually care?
- Do I improve in telling the story?
Track the engagement of your narrative before committing resources to Discovery.
Create a Story
Publish a post, launch an idea, or share a new hypothesis.
Capture Signals
Automatically gather engagement, comments, and reactions.
Extract Themes
Turn scattered comments into structured, quantifiable themes.
Feed Decisions
Link insights directly back to opportunities and strategy.
3. Capture Raw Signals
Signals
Canonical metrics and KPIs powering your product decisions.
This is your product reality
Signals are not just charts.
They are structured inputs.
You're looking at a system that collects:
- signals from product usage
- signals from users
- continuous feedback from tools
All in one place.
Instead of scattered dashboards and ticketing systems, everything becomes part of a shared signal layer.
Key Capabilities
Consolidated Collection
Capture diverse signals from various tools seamlessly.
Triage & Structuring
A single source of truth that turns noise into clarity.
Theme Mapping
Cluster and refine related signals to uncover systemic patterns.
System-wide Usage
Feed these validated inputs directly into discovery.
Signals don't create value on their own.
They feed discovery.
They inform strategy.
They shape capabilities.
This is where everything starts.