Skool Followers Scraper

Skool Followers Scraper

Skool Followers Scraper is a purpose-built Apify actor that turns public Skool profile follower pages into clean, structured data for fast prospecting, analysis, and enrichment. It fetches the profile URL with the followers tab, parses the embedded NEXT_DATA JSON, and streams each follower as a dataset row—perfect for marketers, developers, data analysts, and researchers. At scale, it enables bulk audience research, outreach targeting, and automated workflows with reliable, repeatable results. 🚀

What data / output can you get?

Below are the exact fields pushed to the dataset for each follower. Values are mapped from Skool’s embedded JSON and stored as flat keys so you can export to CSV or JSON with ease.

Data type	Description	Example value
id	Unique Skool user ID	"123456"
name	Username/handle used to build the profile link	"janedoe"
linkToProfile	Direct link to the follower’s Skool profile	"https://www.skool.com/@janedoe"
pictureProfile	Profile photo URL from metadata	"https://cdn.skool.com/profile/janedoe.jpg"
lastName	Last name (if available)	"Doe"
firstName	First name (if available)	"Jane"
bio	Short bio/description from metadata	"Founder @ Acme. Building community-driven products."
online	Online status placeholder	"N/A"
lastOffline	Last seen timestamp formatted as HH:MM:SS - DD/MM/YYYY	"13:24:41 - 18/04/2026"
pictureBubble	Secondary image/avatar URL from metadata	"https://cdn.skool.com/bubble/janedoe.png"
createdAt	Account created timestamp (raw, as provided)	"2025-06-10T12:34:56.000Z"
updatedAt	Last updated timestamp (raw, as provided)	"2026-04-18T09:12:03.000Z"

Notes:

• Rows are written one at a time, so you’ll see new followers appear live in the Output tab.
• Export your results as JSON or CSV at any time from the dataset tab.

Key features

• ⚡ Boldly simple HTML parsing (no login)
  Reads the followers tab directly and parses the embedded NEXT_DATA for reliable, structured extraction without cookies or session handling.

• 📥 Live, row-by-row streaming to the dataset
  Each follower is saved immediately with Actor.push_data, so your Output table updates in real time as the run progresses.

• 📚 Bulk input & normalization
  Paste one or many Skool profile URLs; supports plain strings or requestListSources objects with a url key. Add as many profiles as your plan allows.

• 🎯 Per-profile caps for speed or depth
  Control how many followers to keep per profile with maxItems (schema default 100; runtime falls back to 30 if unset or 0) for quick tests or full exports.

• 🛰️ Smart proxy escalation (optional)
  Starts direct, falls back to Apify datacenter when needed, and uses residential proxies with automatic retries. After a successful residential fetch, a “sticky” residential path is used for the rest of the run.

• 📊 Easy exports
  Download clean JSON or CSV from the Apify dataset at any time—ready for sheets, CRMs, or analytics tools.

• 🛠️ Developer-friendly Apify Actor
  Built on the Apify platform with Python and httpx; consume results programmatically from the Dataset API or connect to your automation stack.

• 🧱 Production-ready reliability
  Robust request headers, retry logic, and proxy handling designed for stable runs across multiple profiles.

How to use Skool Followers Scraper - step by step

1. Sign in to Apify
   Create or log in to your Apify account to run the actor.

2. Open the actor
   Find “Skool Followers Scraper” in your workspace and click Try it.

3. Add input URLs
   In the urls field, paste one or many Skool profile links (one per line works). You can provide:

• Plain strings like "https://www.skool.com/@yourcreator"
• Objects with a url property (requestListSources format)

4. Set limits
   Adjust maxItems to cap how many followers to keep per profile. The schema default is 100; if left unset or set to 0, the runtime uses 30 for quick tests.

5. (Optional) Configure proxy
   Expand proxyConfiguration only if your workspace uses Apify Proxy. The run starts direct, may fall back to datacenter, then residential if needed.

6. Start the run
   Click Start. Watch the Log for step-by-step progress and see the Output tab fill with follower rows in real time.

7. Export your data
   Open the dataset and export your results as JSON or CSV for immediate use in spreadsheets, CRMs, or pipelines.

Pro Tip: Automate downstream workflows by consuming the dataset via the Apify API, or trigger exports to your data tools for enrichment and reporting.

Use cases

Use case name	Description
Sales prospecting & outreach	Build targeted lead lists from Skool follower communities and export to CSV/JSON for personalized outreach.
Competitor community analysis	Benchmark community size and activity by pulling recent followers from competitor profiles.
Audience research & segmentation	Discover audience interests via follower bios and segment by creator or niche.
CRM enrichment (CSV/JSON export)	Enrich records with profile links and photos by importing the dataset into your CRM or data warehouse.
Data pipeline ingestion (API)	Consume the dataset programmatically from the Apify API to feed internal dashboards or workflows.
Academic & community research	Study community growth and patterns using structured follower data captured at intervals.

Why choose Skool Followers Scraper?

Skool Followers Scraper focuses on accurate, fast follower extraction from public Skool profile pages with automation-ready output.

• 🎯 Precision from embedded JSON: Parses NEXT_DATA for clean, structured fields without brittle HTML scraping.
• 🚀 Scales with bulk inputs: Paste many profile URLs and control row caps per profile for fast iteration or full exports.
• 💻 Developer access: Use the Apify Dataset to download JSON/CSV or consume programmatically in your pipelines.
• 🛡️ Safe & public-only: Designed for publicly available pages—no login or cookies required.
• 🔁 Robust connectivity: Direct first, then datacenter, then residential with sticky mode for stable runs.
• 💸 Efficient operations: Streamed writes let you validate results early and export anytime.
• 🧩 Workflow-friendly: Results slot neatly into spreadsheets, CRMs, and analytics without extra transformation.

Compared to browser extensions and unstable scripts, this Apify-based actor provides consistent output, proxy-aware routing, and production-grade reliability.

Is it legal / ethical to use Skool Followers Scraper?

Yes—when done responsibly. This actor reads public Skool profile pages and extracts follower data that’s embedded client-side.

Guidelines for compliant use:

• Scrape only publicly accessible pages you’re allowed to access.
• Review and respect Skool’s terms of service.
• Use exported data responsibly and in line with applicable regulations (e.g., GDPR, CCPA).
• Do not attempt to access private or authenticated content.
• Consult your legal team for edge cases or regulated use.

Input parameters & output format

Example JSON input

{
  "urls": [
    { "url": "https://www.skool.com/@liamottley" },
    "https://www.skool.com/@yourcreator"
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Field	Type	Required	Default	Description
urls	array	Yes	—	Paste Skool profile links (supports plain strings or requestListSources objects with a url key). Bulk is supported.
maxItems	integer	No	100	Cap how many follower rows to keep for each profile (newest first). Tip: Leave unset or 0 for a 30-row quick test at runtime.
proxyConfiguration	object	No	useApifyProxy: false (prefill)	Optional Apify Proxy configuration block. Leave off for typical runs; the actor still runs end-to-end.

Example JSON output

[
  {
    "id": "123456",
    "name": "janedoe",
    "linkToProfile": "https://www.skool.com/@janedoe",
    "pictureProfile": "https://cdn.skool.com/profile/janedoe.jpg",
    "lastName": "Doe",
    "firstName": "Jane",
    "bio": "Founder @ Acme. Building community-driven products.",
    "online": "N/A",
    "lastOffline": "13:24:41 - 18/04/2026",
    "pictureBubble": "https://cdn.skool.com/bubble/janedoe.png",
    "createdAt": "2025-06-10T12:34:56.000Z",
    "updatedAt": "2026-04-18T09:12:03.000Z"
  }
]

Field notes:

• online is set to "N/A" as a placeholder.
• lastOffline is formatted for readability; if missing, it appears as "N/A".
• createdAt and updatedAt are passed through as provided by the page and may be empty strings when unavailable.

FAQ

Do I need to log in to scrape followers?

No. The actor reads public Skool profile pages and parses the embedded JSON—no login, cookies, or session handling required.

What fields does the scraper return?

It outputs a structured follower record with id, name, linkToProfile, pictureProfile, lastName, firstName, bio, online, lastOffline, pictureBubble, createdAt, and updatedAt. These appear in the Output tab as rows you can export.

How many profiles or followers can I process at once?

You can paste multiple profile URLs into urls—bulk is supported. Use maxItems to control how many followers are kept per profile (default 100 in the schema; the runtime uses 30 if unset or 0 for quick tests).

What export formats are supported?

You can export your dataset as JSON or CSV directly from the Apify platform at any time during or after the run.

How does proxy handling work?

The run starts direct. If the page doesn’t load cleanly, it falls back to an Apify datacenter connection, then residential with retries. After a successful residential fetch, a sticky residential path is used for the remainder of the run.

What types of input URLs are accepted?

Provide Skool profile links either as plain strings or as objects with a url property (requestListSources format). The actor normalizes both.

How quickly will I see results?

Rows are pushed one at a time as followers are parsed. You’ll see the Output table populate live, with progress visible in the Log.

Is this compliant with Skool’s terms?

It extracts data from public pages only. You are responsible for ensuring your use complies with Skool’s terms and applicable laws.

Closing CTA / Final thoughts

Skool Followers Scraper is built for fast, reliable extraction of public follower lists from Skool profile pages. It delivers structured fields, streams results live to your dataset, and supports bulk inputs with smart connectivity handling. Whether you’re a marketer, developer, analyst, or researcher, you can export JSON/CSV for sheets and CRMs or consume results programmatically. Start extracting cleaner follower data today and turn Skool communities into actionable insights.