finding-brand-collaborations-on-tiktok
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.
- Installs
- 780
- Last 24h
- +8
- Trending rank
- #9722
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-brand-collaborations-on-tiktok- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads finding-brand-collaborations-on-tiktok automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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_TOKENenvironment 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):
# 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_TOKENmust be set in environment or.envfile.
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:
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.namepost_views:playCountpost_date:createTimecollaboration_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.
FAQ
What does the finding-brand-collaborations-on-tiktok skill do?
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.
How do I install finding-brand-collaborations-on-tiktok?
Run npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-brand-collaborations-on-tiktok in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/finding-brand-collaborations-on-tiktok/ (personal) or .claude/skills/finding-brand-collaborations-on-tiktok/ (project).
Which AI agents can use finding-brand-collaborations-on-tiktok?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is finding-brand-collaborations-on-tiktok safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains finding-brand-collaborations-on-tiktok?
It is published by apidojo-io in apidojo-io/apidojo-skills. It has 780 recorded installs.
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