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 0.35avg_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.