finding-fitness-brands-on-tiktok

核心功能：依托Apify的TikTok爬虫，按关键词、URL、地域等筛选，挖掘健身类商家，返回视频数据、账号信息、互动指标，并按粉丝量、互动率等评分分级。典型场景：适合健身SaaS供应商、设备商等用于B2B拓客、合作商机挖掘。输入支持关键词、排序方式等参数，输出可导出为CSV/JSON格式，助力精准筛选高优先级合作方。

apidojo-io

热度 7.62

最近更新 2026-09-03 04:43:17

分类：营销依赖：第三方 API / MCP 服务 / 代码执行 / 读写文件应用场景：社交媒体 / 市场分析

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add finding-fitness-brands-on-tiktok

Metadata

name: finding-fitness-brands-on-tiktok
description: 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.
license: Apache-2.0
metadata: {"author":"apidojo","version":"1.0","apify-actor":"apidojo/tiktok-scraper"}

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.