/install newsletter-audience-intelligence
Newsletter Audience Intelligence
Turn subscriber, reply, survey, source, and click data into sponsor-ready audience proof and operating decisions.
Core Rule
Use connected analytics, subscriber data, source attribution, survey answers, replies, sponsor history, and issue history when available. Do not invent audience metrics, demographics, reader quotes, locations, job titles, or intent signals.
Inputs
- Newsletter name, category, audience, geography or market
- Current subscriber count, opens, clicks, replies, source attribution, and survey data if available
- Reader segments or tags already used
- Sponsor, paid conversion, growth, or content-quality goal
- Known acquisition sources: Meta, Reddit, X, LinkedIn, TikTok, referrals, swaps, events, search, or organic
- Connected workspace, analytics export, or manual data if available
Workflow
- Separate known data from assumptions and missing data.
- Identify useful audience segments by source, geography, role, interest, behavior, lifecycle, or purchase intent.
- Compare segment quality using engagement, clicks, replies, conversions, and sponsor fit.
- Extract sponsor-proof bullets without overclaiming attribution.
- Flag weak or missing proof needed before selling sponsors or scaling acquisition.
- Recommend 3-7 survey, onboarding, reply, or tagging improvements.
- Save or hand off audience insights, segment notes, and next data collection steps for the connected workspace.
Output Format
When a reusable artifact is useful, follow templates/audience-proof.md.
Include:
- Audience-quality summary
- Known data vs missing data
- Segment table
- Sponsor-proof bullets
- Weak proof or risk notes
- Data collection plan
- Connected-workspace handoff notes
Segment table columns:
| Segment | Evidence | Value to operator | Sponsor relevance | Confidence | Next data to collect |
|---|
Guardrails
- Do not infer demographics from stereotypes or category assumptions.
- Do not treat subscriber count as sponsor proof by itself.
- Keep exact metrics separate from qualitative signals.
- If data is thin, output a collection plan instead of pretending there is a strong audience story.
- Do not export, delete, tag, or modify subscribers without explicit approval and an available workspace/API tool.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install newsletter-audience-intelligence - After installation, invoke the skill by name or use
/newsletter-audience-intelligence - Provide required inputs per the skill's parameter spec and get structured output
What is Newsletter Audience Intelligence?
Use when the user asks to understand newsletter audience quality, segment readers, summarize survey/reply/click data, prove sponsor value, create media-kit p... It is an AI Agent Skill for Claude Code / OpenClaw, with 40 downloads so far.
How do I install Newsletter Audience Intelligence?
Run "/install newsletter-audience-intelligence" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Newsletter Audience Intelligence free?
Yes, Newsletter Audience Intelligence is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Newsletter Audience Intelligence support?
Newsletter Audience Intelligence is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Newsletter Audience Intelligence?
It is built and maintained by Dmitriy (@freeman14); the current version is v1.0.0.