F
finding-fitness-brands-on-tiktok
About finding-fitness-brands-on-tiktok
A skill for discovering fitness brands through TikTok posts and evaluating channels with follower, engagement, and verification signals. It uses the apidojo TikTok scraper and provides ranking guidance for prospecting.
Key features
- 01TikTok のキーワード・URL検索
- 02地域と投稿順の指定
- 03投稿数の上限設定
- 04フォロワー数や反応率で評価
- 05見込み先のランク分類
Use cases
- 01営業候補となるフィットネスブランドの発見
- 02国別にフィットネス投稿を調査
- 03反応や認証状況を基に候補を優先付け
MCP support
Apify MCP の call_actor ツールで apidojo~tiktok-scraper を呼び出せます。
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ apidojo-io/ apidojo-skills --skill finding-fitness-brands-on-tiktokAfter installing, type/finding-fitness-brands-on-tiktokin Claude Code to confirm it loaded.
Details
From the project READMEFinding Fitness Brands On Tiktok
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 |
How to Run
Using run_actor.js (recommended)
# Quick answer (table)
node scripts/run_actor.js --actor "apidojo~tiktok-scraper" --input '{"keywords": ["fitness studio", "gym owner"], "sortType": "MOST_LIKED", "maxItems": 100}'
# Save as CSV
node scripts/run_actor.js --actor "apidojo~tiktok-scraper" --input '{"keywords": ["fitness studio", "gym owner"], "sortType": "MOST_LIKED", "maxItems": 100}' --output results.csv --format csv
# Save as JSON
node scripts/run_actor.js --actor "apidojo~tiktok-scraper" --input '{"keywords": ["fitness studio", "gym owner"], "sortType": "MOST_LIKED", "maxItems": 100}' --output results.json --format json
REST API fallback
curl -X POST "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"keywords": ["fitness studio", "gym owner"], "sortType": "MOST_LIKED", "maxItems": 100}'
If Apify MCP is available:
Use the Apify MCP call_actor tool with actor apidojo~tiktok-scraper and the input above.
Scoring & Ranking
Score each channel by:
followers→ normalized 0-1 (cap at 500K), weight 0.35avg_engagement = (likes + comments + shares) / views→ weight 0.35verified→ 0 or 1, weight 0.30
score = 0.35 * min(followers / 500000, 1.0) + 0.35 * min(avg_engagement / 0.10, 1.0) + 0.30 * int(verified)
Classification
| Score | Tier | Label |
|---|---|---|
| ≥ 0.70 | A | PRIME_PROSPECT |
| 0.40–0.69 | B | WARM_LEAD |
| < 0.40 | C | LOW_PRIORITY |
Edge Cases
- Mixed results with consumers: Filter by channel.followers > 1000 to focus on established brands.
- Keyword too broad: "fitness" returns individual users. Use "fitness business", "gym owner", "fitness studio" instead.
- No contact info in TikTok: Cross-reference with Instagram or website links in bio.
- Duplicate channels: Same brand may appear multiple times — deduplicate by channel.username.
- Inflated views: TikTok can have high views but low followers for viral one-offs — balance both metrics.
Comments
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