How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-youtube-micro-influencersBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
Finding YouTube Micro-Influencers
Searches YouTube for channels in a specific niche, then filters by subscriber count to surface micro-influencers (typically under 100K subscribers) who have high engagement relative to their audience size. Ideal for affiliate programs and brand sponsorships where micro audiences convert better.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| Parameter | Type | Required | Default | Notes |
|---|---|---|---|---|
startUrls | array | Optional | [] | YouTube URLs — channels, playlists, Shorts, search results |
youtubeHandles | array | Optional | [] | YouTube channel handles (e.g. @kurzgesagt) |
getTrending | boolean | Optional | false | Retrieve trending videos |
keywords | array | Optional | [] | Search keywords |
gl | string | Optional | us | Country code for results (e.g. US, GB) |
hl | string | Optional | en | Language code (e.g. en, de) |
uploadDate | string | Optional | all | Upload date filter: any, hour, today, week, month, year |
duration | string | Optional | all | Duration filter: any, short, long |
features | string | Optional | all | Feature filter: 4k, hd, live, cc, 3d, hdr, etc. |
sort | string | Optional | r | Sort order for search results |
maxItems | number | Optional | Unlimited | Maximum videos to return |
customMapFunction | string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Define niche and subscriber range
- [ ] Step 2: Build keyword and search term list
- [ ] Step 3: Run youtube-scraper
- [ ] Step 4: Filter and calculate view-to-sub ratio
- [ ] Step 5: Deliver ranked channel listStep 1: Clarify Parameters
Ask the user for:
- Niche/topic (e.g., "personal finance for millennials", "vegan cooking", "PC gaming")
- Max subscribers (default: 100,000 — micro-influencer threshold)
- Min subscribers (default: 5,000 — filters out very new channels)
- Min videos (default: 20 — ensures established presence)
- Number of channels to return (default: 30)
Step 2: Build Search Term List
Generate 3-5 YouTube search queries for the niche. Think like a viewer, not a marketer:
- Personal finance →
"how to save money","budget for beginners","investing in your 20s" - Vegan cooking →
"easy vegan recipes","vegan meal prep","vegan on a budget" - PC gaming →
"budget PC build","PC gaming tips","indie game reviews"
Step 3: Run the Actor
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~youtube-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.json --format jsonAPIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~youtube-scraper"
Input:
{
"searchQuery": "[SEARCH_TERM]",
"maxResults": 50,
"scrapeVideoDetails": false,
"scrapeChannelDetails": true
}Run for each search query. Merge channel results, deduplicate by channel ID.
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~youtube-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"searchQuery": "[SEARCH_TERM]",
"maxResults": 50,
"scrapeChannelDetails": true
}'Wait for SUCCEEDED. Fetch dataset.
Step 4: Filter and Score
Apply subscriber range filter. Then calculate view-to-subscriber ratio as the micro-influencer quality signal:
view_ratio = (total_views / subscriber_count)
recent_momentum = avg_views_last_10_videos / subscriber_countHigh recent_momentum (>0.5) = channel punching above its weight — ideal micro-influencer.
Step 5: Format Output
Output Format
# YouTube Micro-Influencer Discovery: [NICHE]
Subscriber range: [MIN]–[MAX] | Results: [N] channels | Date: [DATE]
| # | Channel | Subscribers | Avg Views | View/Sub Ratio | Videos | Contact | URL |
|---|---------|-------------|-----------|----------------|--------|---------|-----|
| 1 | [name] | [N] | [N] | [X.Xx] | [N] | [email?]| [url] |
## Top 5 Picks for Outreach
1. **[Channel Name]** — [N] subs | [X.Xx] view ratio | Posts [X]x/month
Why: [brief reason — high engagement, relevant niche, consistent posting]
Contact: [email from About page if available]
Latest video: "[title]" — [N] views
2–5. [same structure]
## Notes
- [N] channels found total across all search queries
- [N] filtered out (outside subscriber range or too few videos)
- View/Sub Ratio > 1.0 = exceptional engagement (views exceed subscriber count per video avg)Troubleshooting
Only large channels in results: YouTube search ranks by relevance + views, surfacing big channels first. Try more niche-specific search terms or filter more aggressively on subscriber count. No contact info: Most YouTubers list business email in the About tab. If missing from scraper output, check the channel URL manually. Stale subscriber counts: YouTube data on Apify can be 24-72h old. For final outreach list, verify top picks manually.
