SuperAPI AI Directory

finding-fitness-brands-on-tiktok

Marketing & growth

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Updated 10-15 16:22

About this skill

Finding 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 0.35
  • avg_engagement = (likes + comments + shares) / views → weight 0.35
  • verified → 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.