Skip to main content
skill CX Codex

finding-affiliate-marketers-on-social-media — Claude Code skill

Finds affiliate marketers and performance creators on Instagram and TikTok through apidojo scrapers. Useful when you are building a recruitment list for an affiliate program.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add apidojo-io/apidojo-skills --skill finding-affiliate-marketers-on-social-media -a claude-code
Open on GitHub

What finding-affiliate-marketers-on-social-media does

The skill drives the apidojo/instagram-scraper and apidojo/tiktok-scraper actors on Apify, then turns the raw output into a table of creators. Each row carries a handle, platform, affiliate signal strength, niche focus, engagement rate and promo code count. Five steps run in order: set parameters, run the scraper, filter and classify, score, deliver.

Execution goes through scripts/run_actor.js, which waits for the run to finish and writes CSV or JSON. With the Apify MCP server installed, the same actor is called as apify:run-actor. A REST fallback posts to the Apify API with curl and then pulls the dataset.

Results fall into three buckets: active affiliate (more than 3 promo posts in 30 days), occasional promoter (1–3 posts), and an audience that consumes affiliate content without producing it. The score multiplies the share of promo posts by average views on those posts. Nothing runs without APIFY_TOKEN set in the environment or a .env file. Telling real affiliates from brand staff is simple: staff push the brand with no trackable code or unique URL.

What it helps with

  • build a creator list before launching an affiliate program
  • spot who already promotes products in a niche
  • find creators running a competitor's affiliate links
  • separate active affiliates from one-off promoters
  • compare engagement and promo code counts across candidates

Example prompts for the agent

  • Find affiliate marketers in the home goods niche on Instagram
  • Build a list of TikTok creators promoting cosmetics with a promo code
  • Show me who is pushing a competitor's affiliate links

How to install finding-affiliate-marketers-on-social-media

1Skills CLI (Vercel)

npx skills add apidojo-io/apidojo-skills --skill finding-affiliate-marketers-on-social-media -a claude-code

2Manually: put the files in place

~/.claude/skills/finding-affiliate-marketers-on-social-media/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/finding-affiliate-marketers-on-social-media/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about finding-affiliate-marketers-on-social-media

How do I install finding-affiliate-marketers-on-social-media in Claude Code?

Run npx skills add apidojo-io/apidojo-skills --skill finding-affiliate-marketers-on-social-media -a claude-code. The skill file lands at ~/.claude/skills/finding-affiliate-marketers-on-social-media/SKILL.md.

What does finding-affiliate-marketers-on-social-media do?

It searches Instagram and TikTok for affiliate marketers and performance creators, classifies them by affiliate signal strength and scores each one. Output is a table with handle, platform, niche, engagement rate and promo code count.

What do I need before running the skill?

An APIFY_TOKEN in your environment or .env file. The Apify MCP server is optional — without it the skill calls the Apify REST API directly.

Source text

SKILL.md · Apache-2.0
---
name: finding-affiliate-marketers-on-social-media
description: >
  Finds affiliate marketers and performance marketing creators on Instagram and TikTok using apidojo's scrapers. Triggers when the user asks to: find affiliate marketers for a product category, discover creators running affiliate campaigns on social media, identify performance marketers promoting products in a niche, find social media affiliates for a brand program, discover who is promoting competitor affiliate links, build an affiliate creator recruitment list, or find content creators with affiliate marketing experience.
  Returns creator handle, platform, affiliate signal strength, niche focus, engagement rate, and promo code count.
  Ideal for affiliate program managers, e-commerce brands launching affiliate programs, and network managers.
license: Apache-2.0
metadata:
  author: apidojo
  version: "1.0"
  apify-actors: apidojo/instagram-scraper, apidojo/tiktok-scraper
---

# Finding Affiliate Marketers On Social Media

Executes finding affiliate marketers on social media using apidojo scrapers. Part of the apidojo intelligence skills library.

## Prerequisites

- `APIFY_TOKEN` environment variable set
- Optional: Apify MCP server installed

## Inputs

| Parameter | Type | Required | Default | Notes |
|-----------|------|----------|---------|-------|
| `startUrls` | array | ✅ | `[]` | Instagram URLs — profiles, hashtags, locations, audio pages, reels |
| `until` | string | Optional | — | Scrape posts until this date (YYYY-MM-DD) |
| `maxItems` | number | Optional | Unlimited | Maximum posts to return |
| `customMapFunction` | string | Optional | — | JavaScript function to transform each output object |

## Workflow

```
Progress:
- [ ] Step 1: Define parameters
- [ ] Step 2: Run instagram-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output
```

### Step 2: Run the Actor


**Recommended — run_actor.js (handles waiting, output, and file saving automatically):**
```bash
# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~instagram-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~instagram-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~instagram-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json
```
> `APIFY_TOKEN` must be set in environment or `.env` file.

**If Apify MCP is available:**
```
Tool: apify:run-actor
Actor: "apidojo~instagram-scraper"
Input:
{
  "searchTerms": ["#affiliate[niche]", "#[niche]code", "use code [NICHE]", "#commissioned"],
  "maxItems": 100
}
```

**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["#affiliate[niche]", "#[niche]code", "use code [NICHE]", "#commissioned"], "maxItems": 100}'
```

Wait for `SUCCEEDED`. Fetch dataset:
```bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"
```

### Step 3: Classify Results

```
classification: ACTIVE_AFFILIATE (> 3 promo posts in 30 days) | OCCASIONAL_PROMOTER (1-3 posts) | AFFILIATE_AUDIENCE (uses affiliate content but doesn't produce it)
```

### Step 4: Score Each Result

```
score = affiliate_signal = (promo_code_post_count / total_posts * 100) * (avg_views_on_affiliate_posts / 1000)
```

### Step 5: Edge Cases

- **Distinguish genuine affiliates from brand employees — employees promote brand without code; affiliates promote with a trackable code or unique URL**

Additional fallbacks:
- **< 20 results**: Broaden search terms; remove secondary filters
- **No results**: Verify the search terms are correct; try alternate phrasings
- **Data quality issues**: Remove entries with missing key fields; note count in output

## Output Format

```
# Finding Affiliate Marketers On Social Media
Results: [N] | Date: [DATE]

| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] |
|---|------------|-----------|-----------|-----------------|---------|
| 1 | [value] | [value] | [value] | [type] | [0.XX] |

## Summary
Top result: [description]
Key finding: [insight]
```

## Troubleshooting

**Too few results:** Broaden the primary search term; remove restrictive filters.
**Low quality results:** Apply minimum score threshold (≥ 0.50) to filter noise.
**Actor fails to run:** Verify API key; check actor status at apify.com/apidojo.

© apidojo · Apache-2.0 · apidojo-io/apidojo-skills

Similar skills

Everything for Marketing and content →

From the same set57

analyzing-competitor-youtube-content-strategy Audits a competitor’s YouTube strategy by topic, format, publishing cadence, views, and engagement. Use it to compare two channels or find content gaps. CX Codex +1 776installs finding-ecommerce-brands-for-outreach Builds a list of e-commerce and DTC brands on Instagram and TikTok by product-category hashtags. Useful when you need an outreach list instead of scrolling profiles by hand. CX Codex +1 776installs analyzing-competitor-tiktok-content-strategy This skill examines a competitor’s TikTok account, covering videos, posting cadence, hashtags, hooks, and engagement. Use it for content strategy research. CX Codex +1 771installs tracking-competitor-social-media-growth Pulls follower counts and engagement for competitor accounts on Twitter/X, TikTok and Instagram, then lines them up side by side. Useful when you need to compare how accounts grow. CX Codex +1 771installs discovering-tiktok-shop-sellers-by-niche Maps TikTok Shop sellers and products in a niche: who promotes what, which items move, where the gaps are. CX Codex +1 770installs tracking-startup-founders-on-twitter Finds startup founders on Twitter by industry or niche and gathers details about their companies and activity. Use it to build a list of accounts to follow. CX Codex +1 769installs tracking-brand-sentiment-across-platforms Pulls brand mentions from Twitter, Reddit and TikTok, scores sentiment per platform, and returns one brand health number from 0 to 100. CX Codex +1 767installs finding-tiktok-creators-by-location Finds TikTok creators and their videos by geographic location through apidojo's scraper on Apify. Useful for local campaigns and regional research. CX Codex +1 766installs

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor