mohitagw15856
63 lines
2.5 KiB
Markdown
63 lines
2.5 KiB
Markdown
---
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name: multi-source-signal-synthesiser
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description: Synthesises user signals from multiple research sources into a
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unified insight brief, reconciling conflicting feedback. Use when user has data
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from multiple sources, needs to "make sense of all this user data", "what are
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users really telling us", "synthesise our research", or has conflicting feedback
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from different channels.
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metadata:
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author: Mohit Aggarwal
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version: 1.0.0
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category: discovery
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tags: [user-research, synthesis, discovery, insights]
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documentation: https://github.com/mohitagw15856/pm-claude-skills
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---
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# Multi-Source Signal Synthesiser Skill
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## Purpose
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Reconcile user signals from multiple sources — interviews, support tickets, NPS,
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app reviews, sales calls — into a unified, weighted insight brief that surfaces
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the underlying need rather than the surface-level request.
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## Source Weighting (default — adapt to your context)
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- Direct research (interviews, usability tests): weight 5
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- Support tickets (unprompted pain signals): weight 4
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- NPS verbatims: weight 3
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- App store reviews: weight 2
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- Sales call summaries (filtered through sales lens): weight 2
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- Anecdote or single report: weight 1
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## Process
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1. Accept inputs from any combination of the source types above
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2. Tag each signal by source and apply weight
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3. Look for CONVERGENCE: same underlying need appearing across 3+ sources
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4. Look for DIVERGENCE: contradictory signals suggesting user segmentation
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5. Distinguish surface request from underlying need
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(e.g. "faster export" may mean "I don't trust the data will be there when
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I need it")
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6. Produce ranked insights by weighted frequency
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## Output Format
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### User Signal Synthesis — [Date / Period]
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**Sources included:** [list]
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**Total signals processed:** [n]
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#### Insight 1: [Underlying need, not feature request]
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- **Confidence:** High / Medium / Low (based on source diversity and weight)
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- **Evidence:** [Signals from each source supporting this]
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- **Conflicting signals:** [Any contradicting evidence and how to interpret it]
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- **Product implication:** [Specific, not generic]
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[Repeat for top 3-5 insights]
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#### Divergent Signals (Possible Segmentation)
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[Where user groups appear to have genuinely different needs]
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#### What the Data Does NOT Tell Us
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[Gaps that require further research before acting]
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## OpenClaw Configuration
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Connect to: Notion (research docs), support inbox, NPS tool, app review feed.
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Schedule: weekly synthesis run, diff output showing new signals only.
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