# GreenLens Pro Pain Mining Machine

## Goal

Turn real plant-owner pains into content, ASO, influencer, landing page, and
product opportunities.

## Why This Exists

GreenLens Pro should be driven by what users actually worry about:
yellow leaves, brown spots, root rot, overwatering, underwatering, pests,
curling leaves, and not knowing what to do next.

## Plugins And Skills

| Need | Use |
|---|---|
| Review/comment exports | Coupler, CSV exports, Codex |
| App Store optimization | `app-store-aso` skill |
| Content clustering | `content-strategy` skill |
| Copy and hooks | `copywriting` skill |
| Support/outreach drafting | Gmail/Fyxer plugin |
| Product issue creation | GitHub plugin |

## Data Sources

Use any available source, but label the source for every pain:

- App Store competitor reviews
- Google Play competitor reviews
- Reddit plant-care threads
- TikTok or Instagram comments
- Google autocomplete or People Also Ask exports
- Support emails or user feedback
- Existing GreenLens analytics or onboarding responses

## Pain Taxonomy

Cluster each item into one primary category:

- Yellow leaves
- Brown spots
- Root rot
- Overwatering
- Underwatering
- Curling leaves
- Drooping leaves
- Pests
- Light problems
- Soil and repotting
- Beginner confusion
- Diagnosis trust
- Price/paywall objection
- App usability issue

## Scoring Model

Score each pain from 0-100:

| Factor | Weight |
|---|---:|
| User urgency | 30 |
| App fit | 25 |
| Content virality | 20 |
| ASO/search value | 15 |
| Product learning value | 10 |

Prioritize urgent, visual, diagnosis-driven pains where GreenLens can credibly
help the user decide what to check next.

## Weekly Output

Produce:

1. Top 20 pains.
2. Top 10 social hooks.
3. Top 5 ASO keyword opportunities.
4. Top 5 blog or landing page ideas.
5. Top 5 product issues or feature hypotheses.
6. Top 10 influencer angles.

## Codex Pain Mining Prompt

```text
Run the GreenLens Pro Pain Mining Machine.

Use:
- docs/automations/greenlens-pain-mining-machine.md
- app-store-aso skill
- content-strategy skill

Input source: [reviews/comments/export/pasted text]
Market: [US / DE / global]
Platform focus: [iOS / Android / both]

Tasks:
1. Extract raw plant-owner pains.
2. Cluster them into the GreenLens pain taxonomy.
3. Score each pain by urgency, app fit, virality, ASO value, and product learning.
4. Convert winners into:
   - social hooks
   - ASO keyword ideas
   - blog/landing page ideas
   - product issues
   - influencer outreach angles

Do not invent source quotes. If evidence is weak, label it as hypothesis.
```

## Output Template

```markdown
# GreenLens Pain Mining Report

## Source Summary

## Top Pains
| Rank | Pain | Source | Score | Why it matters |
|---|---|---|---:|---|

## Hook Backlog

## ASO Opportunities

## Product Issues

## Influencer Angles

## Next Actions
```

## Product Issue Template

```markdown
Title: [Feature or improvement]

User pain:
[What the user is struggling with]

Hypothesis:
If GreenLens [change], users will [outcome].

Acceptance criteria:
- [criterion]
- [criterion]
- [criterion]

Measurement:
- activation
- scan completion
- paywall conversion
- retention
```

## Success Criteria

- Every recommendation traces back to a real pain or explicitly marked hypothesis.
- Top pains can feed both ASO and social content.
- Product issues are concrete enough for GitHub.