Finding TikTok UGC Creators for Brands

Discovers TikTok micro-creators who produce authentic product content. UGC creators (1K–100K followers) deliver the highest ROI for paid campaigns — authentic feel, affordable rates, and high engagement relative to follower count.

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 hashtags for niche UGC content
- [ ] Step 2: Collect creator handles from search
- [ ] Step 3: Enrich profiles
- [ ] Step 4: Score UGC fit
- [ ] Step 5: Deliver creator roster

Step 1: Build Hashtag Searches

Hashtags for niche: #[niche]review, #[niche]haul, #[niche]unboxing, #[niche]honest review,
                    #[niche]foryou, #ugc[niche], #[niche]tiktokmademebuyit

Example for skincare:

["#skincarereviews", "#skincarehaul", "#skincaretiktok", "#ugcskincare", "#honestskincarereview"]

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": ["#[niche]review", "#[niche]haul", "#ugc[niche]"],
  "maxItems": 200
}

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": ["#skincarereviews", "#skincarehaul"],
    "maxItems": 200
  }'

Collect unique

authorMeta.name

(handles) with > 2 posts in niche.

Step 2: Enrich Creator Profiles

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~tiktok-profile-scraper"
Input:
{
  "profiles": ["https://www.tiktok.com/@[handle1]", "https://www.tiktok.com/@[handle2]"]
}

REST API fallback:

bash

curl -X POST   "https://api.apify.com/v2/acts/apidojo~tiktok-profile-scraper/runs?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"profiles": ["https://www.tiktok.com/@handle1"]}'

Step 3: Score UGC Fit

engagement_rate = (avg_likes + avg_comments) / follower_count * 100

view_to_follower_ratio = avg_views / follower_count

ugc_score = (engagement_rate > 5 ? 1 : engagement_rate / 5) * 0.35
          + (view_to_follower_ratio > 1 ? 1 : view_to_follower_ratio) * 0.30
          + (follower_count in 5000..50000 ? 1 : 0.6) * 0.20
          + (posts_in_niche >= 3 ? 1 : posts_in_niche / 3) * 0.15

UGC tier classification:

TIER 1 (score ≥ 0.75): High engagement, consistent niche content — ideal for paid UGC
TIER 2 (score 0.50–0.74): Good engagement, some niche overlap — worth testing
TIER 3 (score < 0.50): Low engagement or single niche post — aspirational / monitoring list

Step 4: Edge Cases

Brand accounts appear in hashtag results: Drop entries where bio contains "Official", "brand", "@company" — keep only individual creators
Views from single viral video inflating avg: Calculate avg from last 10 posts; flag if std_dev > 3× avg (viral outlier)
Creator posts in multiple niches: Track
```
niche_concentration = niche_posts / total_posts
```
; flag if < 30%
Inactive creators: Skip if
```
lastPostDate > 60 days ago
```

Output Format

# TikTok UGC Creator Roster: [NICHE]
Creators evaluated: [N] | TIER 1: [N] | TIER 2: [N] | Date: [DATE]

## TIER 1 — Prime UGC Creators
| Creator | Handle | Followers | Avg Views | Eng Rate | View/Follower | Niche % | Score |
|---------|--------|-----------|-----------|----------|---------------|---------|-------|
| [name] | @[handle] | [N] | [N] | [X%] | [X.X×] | [X%] | [0.XX] |

## TIER 2 — Worth Testing
| Creator | Followers | Avg Views | Eng Rate | Last Active |
|---------|-----------|-----------|----------|------------|

## Niche Hashtag Performance
| Hashtag | Posts Scraped | Avg Views per Post | Top Creator Found |
|---------|--------------|-------------------|-------------------|

Troubleshooting

Too many brand accounts: Tighten filter — drop accounts with

follower_count > 500K

and accounts with verification badge. Hashtag returns mainly brand posts: Switch to user-driven hashtags:

#tiktokmademebuyit[niche]

#[niche]recommendation

. Creators found aren't making product content: Use hashtags that explicitly signal product review intent rather than broad niche tags.

finding-tiktok-ugc-creators-for-brands

NPX Install

Tags

SKILL.md Content

Finding TikTok UGC Creators for Brands

Prerequisites

Inputs

Workflow

Step 1: Build Hashtag Searches

Step 2: Enrich Creator Profiles

Step 3: Score UGC Fit

Step 4: Edge Cases

Output Format

Troubleshooting