finding-fitness-brands-on-tiktok

Discovers fitness studios, wellness brands, and gym businesses on TikTok using apidojo's TikTok Scraper on Apify. Triggers when the user asks to: find fitness businesses on TikTok, discover gym brands for B2B outreach, build a list of wellness brands active on TikTok, find personal trainers or fitness studios by hashtag on TikTok, prospect health and fitness companies via TikTok content, or identify growing fitness brands for partnership or vendor sales. Returns video data, channel info (username, followers, verified), hashtags, and engagement metrics. Ideal for fitness SaaS vendors, equipment suppliers, and health brand partnership teams.

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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)

bash

# 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

bash

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.

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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

python

score = 0.35 * min(followers / 500000, 1.0) + 0.35 * min(avg_engagement / 0.10, 1.0) + 0.30 * int(verified)

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Classification

Score	Tier	Label
≥ 0.70	A	PRIME_PROSPECT
0.40–0.69	B	WARM_LEAD
< 0.40	C	LOW_PRIORITY

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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.