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finding-brand-collaborations-on-tiktok — Claude Code skill

Identifies sponsored TikTok posts and maps brand-creator partnerships using Apify scrapers. Useful for tracking competitor influencer deals and post benchmarks.

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

What finding-brand-collaborations-on-tiktok does

The skill searches TikTok for sponsored content signals such as #ad, brand mentions, and promo codes. It pulls creator metadata and view metrics from post data, linking creators to brands while separating product gifting from paid promotions. It also calculates view-to-follower ratios and collaboration frequency per creator.

Data extraction relies on Apify actors apidojo/tiktok-scraper and apidojo/tiktok-profile-scraper. Runs can be triggered via node scripts/run_actor.js, an Apify MCP server, or direct REST calls. Without a valid APIFY_TOKEN in your environment, the scrapers will not run.

What it helps with

  • discover active brand sponsorships across TikTok categories
  • map creator-brand partnerships for competitor research
  • distinguish gifted collaborations from paid advertising
  • benchmark sponsored post view counts and reach ratios

Example prompts for the agent

  • Find which brands are running influencer campaigns in the skincare category on TikTok
  • Analyze competitor influencer marketing posts using #ad and #sponsored tags
  • Extract creator handles and reach metrics for recent energy drink partnerships on TikTok

How to install finding-brand-collaborations-on-tiktok

1Skills CLI (Vercel)

npx skills add apidojo-io/apidojo-skills --skill finding-brand-collaborations-on-tiktok -a claude-code

2Manually: put the files in place

~/.claude/skills/finding-brand-collaborations-on-tiktok/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/finding-brand-collaborations-on-tiktok/

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

Questions about finding-brand-collaborations-on-tiktok

How do I install finding-brand-collaborations-on-tiktok in Claude Code?

Run npx skills add apidojo-io/apidojo-skills --skill finding-brand-collaborations-on-tiktok -a claude-code.

What does finding-brand-collaborations-on-tiktok do?

It maps active brand-creator partnerships on TikTok and evaluates post performance metrics like view counts and engagement ratios.

What credentials are required to run this skill?

You need an Apify API token configured in the APIFY_TOKEN environment variable. Installing the Apify MCP server is optional.

Source text

SKILL.md · Apache-2.0
---
name: finding-brand-collaborations-on-tiktok
description: >
  Discovers brand collaboration patterns and sponsored content on TikTok using apidojo's TikTok
  scrapers on Apify. Triggers when the user asks to: find which brands are running TikTok
  influencer campaigns, discover creator-brand partnerships in a product category, identify
  which influencers are working with competitor brands on TikTok, see what sponsorship deals
  are active in a niche, find brands that sponsor TikTok creators, analyze competitor influencer
  marketing strategy on TikTok, or track paid partnership posts by category.
  Returns creator handle, brand name, post performance, estimated reach, and collaboration frequency.
  Ideal for influencer marketing teams, competitive intelligence analysts, and brand partnership managers.
license: Apache-2.0
metadata:
  author: apidojo
  version: "1.0"
  apify-actors: apidojo/tiktok-scraper, apidojo/tiktok-profile-scraper
---

# Finding Brand Collaborations on TikTok

Maps active brand-creator partnerships in a product category. Identifies which brands are investing in TikTok influencer marketing, which creators they're working with, and the performance benchmarks for sponsored content.

## Prerequisites

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

## Inputs

| Parameter | Type | Required | Default | Notes |
|-----------|------|----------|---------|-------|
| `startUrls` | array | Optional | `[]` | TikTok URLs — user profiles, hashtags, music pages, search, locations |
| `keywords` | array | Optional | `[]` | Search keywords/terms to find posts |
| `sortType` | string | Optional | `RELEVANCE` | Sort order for keyword results: `RELEVANCE`, `MOST_LIKED`, `DATE_POSTED` |
| `location` | string | Optional | — | ISO 3166-1 alpha-2 country code for regional filtering (e.g. `US`, `GB`) |
| `maxItems` | number | Optional | Unlimited | Maximum posts to return across the run |
| `includeSearchKeywords` | boolean | Optional | `false` | Add the matched search keyword field to each post |
| `customMapFunction` | string | Optional | — | JavaScript function to transform each output object |

## Workflow

```
Progress:
- [ ] Step 1: Search sponsored content hashtags for category
- [ ] Step 2: Filter for sponsored signals
- [ ] Step 3: Extract brand and creator pairs
- [ ] Step 4: Analyze collaboration patterns
- [ ] Step 5: Deliver brand-creator map
```

### Step 1: Search Posts


**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~tiktok-scraper" \
  --input '{"param": "value"}'

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

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tiktok-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~tiktok-scraper"
Input:
{
  "keywords": ["#ad", "#sponsored", "#[category]partner", "#[category]collab"],
  "keywords": ["[BRAND_NAME] sent", "use code", "thanks to [CATEGORY] brand"],
  "maxItems": 300
}
```

**REST API fallback:**
```bash
curl -X POST   "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{
    "keywords": ["#ad", "#sponsored", "#fitnesspartner"],
    "maxItems": 300
  }'
```

### Step 2: Extract Brand-Creator Pairs

From each sponsored post, extract:
- `brand_name`: From caption mention (`@[brand]`, `[Brand] sent me`, `thanks to [Brand]`)
- `creator_handle`: `authorMeta.name`
- `post_views`: `playCount`
- `post_date`: `createTime`
- `collaboration_type`: `#gifted` (product seeding) vs. `#ad`/`#sponsored` (paid)

### Step 3: Score Campaign Performance

```
sponsored_performance = playCount / 1000 (views in thousands)
creator_roi_proxy = playCount / followerCount  (view-to-follower ratio for sponsored post)
```

Brand collaboration frequency per creator:
```
collab_depth = count(posts where same brand appears) / total_posts_in_date_range
```

### Step 4: Edge Cases

- **No #ad hashtag but clearly sponsored**: Also scan for `"gifted"`, `"c/o"`, `"partnership"` in caption; TikTok disclosure is inconsistently applied
- **Brand name ambiguous** (e.g. "Nike" in sports context): Verify by checking if creator's bio mentions brand partnership or if post has dedicated product showcase format
- **< 20 sponsored posts found**: Category may be under-sponsored on TikTok; check if brands are using darker patterns (no disclosure) — widen search to product names alone

## Output Format

```
# TikTok Brand Collaboration Map: [CATEGORY]
Posts analyzed: [N] | Sponsored posts identified: [N] | Unique brands: [N] | Date: [DATE]

## Brands Running Active TikTok Campaigns
| Brand | # Creators Used | # Posts | Avg Views/Post | Collaboration Type |
|-------|----------------|---------|----------------|-------------------|
| [brand] | [N] | [N] | [N] | [Gifted/Paid/Mixed] |

## Creator-Brand Pairs
| Creator | @Handle | Brand | Posts | Avg Views | Collab Type | Est. Reach |
|---------|---------|-------|-------|-----------|-------------|-----------|
| [name] | @[handle] | [brand] | [N] | [N] | [Gifted/Paid] | [N] |

## Benchmark: Sponsored Post Performance in [CATEGORY]
- Median views for sponsored posts: [N]
- Top-performing brand campaign: [brand] — [N] avg views
- Most-used creator tier: [micro/macro/mega]
```

## Troubleshooting

**Disclosure data sparse**: TikTok doesn't always surface `#ad` in scraped captions. Check for brand mentions in text and product codes.
**Results outside the category**: Refine search by combining `#ad` with a niche keyword: `"#ad #fitness"` or `"#sponsored #skincare"`.
**Can't find competitor campaigns**: If competitor avoids disclosure, search for their brand @mention directly in TikTok search.

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

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