newsletter-sponsorship-finder

Find newsletters relevant to a target audience/industry for sponsorship opportunities. Discovers newsletters through web search, newsletter directories, and industry research. Returns newsletter name, author, estimated audience, topic focus, sponsorship rates (if available), and contact info.

381 stars

Best use case

newsletter-sponsorship-finder is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Find newsletters relevant to a target audience/industry for sponsorship opportunities. Discovers newsletters through web search, newsletter directories, and industry research. Returns newsletter name, author, estimated audience, topic focus, sponsorship rates (if available), and contact info.

Teams using newsletter-sponsorship-finder should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/newsletter-sponsorship-finder/SKILL.md --create-dirs "https://raw.githubusercontent.com/gooseworks-ai/goose-skills/main/skills/capabilities/newsletter-sponsorship-finder/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/newsletter-sponsorship-finder/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How newsletter-sponsorship-finder Compares

Feature / Agentnewsletter-sponsorship-finderStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Find newsletters relevant to a target audience/industry for sponsorship opportunities. Discovers newsletters through web search, newsletter directories, and industry research. Returns newsletter name, author, estimated audience, topic focus, sponsorship rates (if available), and contact info.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Newsletter Sponsorship Finder

Find and rank newsletters for sponsorship opportunities targeting a specific ICP. Uses web search, newsletter directories, and competitor intelligence to build a prioritized list of sponsorship targets.

## Quick Start

```
Find newsletter sponsorship opportunities for [client]. Target audience: [description]. Industry keywords: [keywords].
```

Or with optional filters:

```
Find newsletter sponsorship opportunities for [client].
Target audience: CTOs and DevOps engineers at startups.
Industry keywords: cloud, AWS, DevOps, infrastructure, FinOps.
Budget: $500-2000/placement.
Geographic focus: US.
```

## Inputs

- **Target audience description** (required) — e.g., "CTOs and DevOps engineers at startups"
- **Industry keywords** (required) — e.g., "cloud, AWS, DevOps, infrastructure, FinOps"
- **Budget range** (optional) — for filtering newsletters by sponsorship cost
- **Geographic focus** (optional) — e.g., "US", "Europe", "Global"
- **Output path** (optional) — where to save results, defaults to `clients/<client>/leads/newsletter-sponsorships-YYYY-MM-DD.md`

## Cost

Free — all discovery is WebSearch-based. No API keys required.

## Dependencies

```
pip3 install requests
```

Optional helper script for Substack directory search:

```bash
python3 skills/newsletter-sponsorship-finder/scripts/search_newsletters.py --keywords "cloud,AWS,DevOps" --output json
```

## Process

### Phase 1: Define Target

Accept from user:
- Target audience description (e.g., "CTOs and DevOps engineers at startups")
- Industry keywords (e.g., "cloud, AWS, DevOps, infrastructure, FinOps")
- Budget range (optional, for filtering)
- Geographic focus (optional)

### Phase 2: Discovery (run searches in parallel)

#### A) Direct newsletter search (WebSearch)

Run these searches:
- `"[industry] newsletter"`
- `"[industry] weekly newsletter developer"`
- `"best newsletters for [target audience]"`
- `"[industry] newsletter sponsorship"`
- `"advertise in [industry] newsletter"`

#### B) Newsletter directory search

Search Swapstack/Paved/SparkLoop for relevant newsletters:
- `"site:swapstack.co [industry]"`
- `"site:paved.com [industry]"`
- WebFetch on directory result pages to find listings in the target niche

#### C) Industry-specific discovery

- Search for `"[industry] blog"` and `"[industry] content creator"` to find people who likely also have newsletters
- Search for `"[industry] newsletter" site:linkedin.com` posts
- Search for Substack newsletters: `"site:substack.com [industry keywords]"`
- Optionally run the helper script: `python3 skills/newsletter-sponsorship-finder/scripts/search_newsletters.py --keywords "[keywords]" --output json`

#### D) Competitor sponsorship research

- Search `"[competitor name] sponsor newsletter"` or `"[competitor name] advertise"`
- Check competitor websites for "As seen in" or press pages
- This reveals which newsletters competitors already sponsor (proven audience match)

### Phase 3: Enrich Each Newsletter

For each discovered newsletter, use WebFetch to visit the newsletter page and try to find:

1. **Name** — Newsletter name
2. **Author/Organization** — Who runs it
3. **URL** — Signup page or archive
4. **Estimated audience** — subscriber count (often mentioned on sponsorship pages or About pages)
5. **Topic focus** — What it covers
6. **Frequency** — Daily, weekly, monthly
7. **Sponsorship info** — Rates, format (dedicated send, banner, classified), contact
8. **Audience quality** — Is the audience primarily decision-makers or junior folks?
9. **Social proof** — Notable sponsors, testimonials

### Phase 4: Score & Rank

Score each newsletter (0-10):
- Audience overlap with target ICP (+3 max)
- Audience size (+2 for 10K+, +1 for 5K+)
- Sponsorship availability confirmed (+2)
- Reasonable pricing for budget (+1)
- High engagement signals — open rates mentioned, active community (+1)
- Competitors sponsor it — proven audience match (+1)

### Phase 5: Output

Save results to the specified output path as markdown:

```markdown
# Newsletter Sponsorship Opportunities
**Target audience:** [description]
**Industry:** [keywords]
**Date:** YYYY-MM-DD

## Tier 1: Must-Sponsor (Score 8+)
| Newsletter | Author | Est. Audience | Frequency | Sponsorship Rate | Contact | Score |
|-----------|--------|--------------|-----------|-----------------|---------|-------|

## Tier 2: Strong Fit (Score 5-7)
| Newsletter | Author | Est. Audience | Frequency | Sponsorship Rate | Contact | Score |
|-----------|--------|--------------|-----------|-----------------|---------|-------|

## Tier 3: Worth Exploring (Score 3-4)
| Newsletter | Author | Est. Audience | Frequency | Sponsorship Rate | Contact | Score |
|-----------|--------|--------------|-----------|-----------------|---------|-------|

## Competitor Sponsorship Intel
| Competitor | Newsletters They Sponsor | Notes |
|-----------|------------------------|-------|

## Next Steps
1. Reach out to Tier 1 newsletters for rate cards
2. Request media kits from Tier 2 newsletters
3. Set calendar reminder to refresh this list quarterly
4. Monitor competitor sponsorships monthly
```

## Tips

- Run once per client to establish a sponsorship pipeline
- Refresh quarterly as new newsletters launch frequently
- Check competitor sponsorships monthly — if a competitor starts sponsoring a newsletter, it validates the audience
- Combine with `agentmail` to automate initial outreach to newsletter operators
- Use `company-contact-finder` when a newsletter's sponsorship contact is not publicly listed
- Newsletters with 5K-50K subscribers often offer the best ROI for B2B sponsorships — large enough audience, small enough for personal touch

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