161 lines
3.3 KiB
Markdown
161 lines
3.3 KiB
Markdown
# GreenLens Pro Pain Mining Machine
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## Goal
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Turn real plant-owner pains into content, ASO, influencer, landing page, and
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product opportunities.
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## Why This Exists
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GreenLens Pro should be driven by what users actually worry about:
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yellow leaves, brown spots, root rot, overwatering, underwatering, pests,
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curling leaves, and not knowing what to do next.
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## Plugins And Skills
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| Need | Use |
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|---|---|
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| Review/comment exports | Coupler, CSV exports, Codex |
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| App Store optimization | `app-store-aso` skill |
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| Content clustering | `content-strategy` skill |
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| Copy and hooks | `copywriting` skill |
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| Support/outreach drafting | Gmail/Fyxer plugin |
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| Product issue creation | GitHub plugin |
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## Data Sources
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Use any available source, but label the source for every pain:
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- App Store competitor reviews
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- Google Play competitor reviews
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- Reddit plant-care threads
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- TikTok or Instagram comments
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- Google autocomplete or People Also Ask exports
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- Support emails or user feedback
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- Existing GreenLens analytics or onboarding responses
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## Pain Taxonomy
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Cluster each item into one primary category:
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- Yellow leaves
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- Brown spots
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- Root rot
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- Overwatering
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- Underwatering
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- Curling leaves
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- Drooping leaves
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- Pests
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- Light problems
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- Soil and repotting
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- Beginner confusion
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- Diagnosis trust
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- Price/paywall objection
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- App usability issue
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## Scoring Model
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Score each pain from 0-100:
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| Factor | Weight |
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|---|---:|
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| User urgency | 30 |
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| App fit | 25 |
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| Content virality | 20 |
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| ASO/search value | 15 |
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| Product learning value | 10 |
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Prioritize urgent, visual, diagnosis-driven pains where GreenLens can credibly
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help the user decide what to check next.
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## Weekly Output
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Produce:
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1. Top 20 pains.
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2. Top 10 social hooks.
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3. Top 5 ASO keyword opportunities.
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4. Top 5 blog or landing page ideas.
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5. Top 5 product issues or feature hypotheses.
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6. Top 10 influencer angles.
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## Codex Pain Mining Prompt
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```text
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Run the GreenLens Pro Pain Mining Machine.
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Use:
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- docs/automations/greenlens-pain-mining-machine.md
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- app-store-aso skill
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- content-strategy skill
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Input source: [reviews/comments/export/pasted text]
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Market: [US / DE / global]
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Platform focus: [iOS / Android / both]
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Tasks:
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1. Extract raw plant-owner pains.
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2. Cluster them into the GreenLens pain taxonomy.
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3. Score each pain by urgency, app fit, virality, ASO value, and product learning.
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4. Convert winners into:
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- social hooks
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- ASO keyword ideas
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- blog/landing page ideas
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- product issues
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- influencer outreach angles
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Do not invent source quotes. If evidence is weak, label it as hypothesis.
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```
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## Output Template
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```markdown
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# GreenLens Pain Mining Report
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## Source Summary
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## Top Pains
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| Rank | Pain | Source | Score | Why it matters |
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|---|---|---|---:|---|
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## Hook Backlog
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## ASO Opportunities
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## Product Issues
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## Influencer Angles
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## Next Actions
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```
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## Product Issue Template
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```markdown
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Title: [Feature or improvement]
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User pain:
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[What the user is struggling with]
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Hypothesis:
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If GreenLens [change], users will [outcome].
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Acceptance criteria:
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- [criterion]
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- [criterion]
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- [criterion]
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Measurement:
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- activation
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- scan completion
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- paywall conversion
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- retention
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```
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## Success Criteria
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- Every recommendation traces back to a real pain or explicitly marked hypothesis.
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- Top pains can feed both ASO and social content.
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- Product issues are concrete enough for GitHub.
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