Boost your business leads with our Skool.com Groups' Members/Users Scraper. Gather user details like names, emails, and social media links (Facebook, Instagram, LinkedIn, Twitter, etc.). It is ideal for market research, competitor analysis, and lead generation. Save time with our advanced scraper.
This is a pay per result version of the Skool.com Member Scraper, you can check the also the renting version: Here
With this scraper you just pay $5 per 1000 leads scraped.
Unleash the full potential of Skool.com data with our Skool.com Groups' Members/Users Scraper. Gather extensive users details such as first and last name, email, user's links to: facebook, instagram, linkedin, twitter, website, youtube and etc. This tool is designed to automate the data extraction process, ensuring you receive accurate and up-to-date information for market research, competitor analysis, and lead generation. Save time and resources by leveraging our advanced scraper to explore Skool.com's vast database of user/member profiles.
Multiple Page Scraping: Capable of scraping data from a variety of page URLs. Input can either be formatted as https://www.skool.com/{group-name}/-/members
or you can directly copy and paste the Skool members' URL like: https://www.skool.com/@bjk
Authentication Requirement: To enable more extensive scraping capabilities, users are required to log in using cookie-based authentication, and you need to be a member or part of the group that you want to scrape.
Customizable Configuration: Offers adjustable settings to cater to a wide range of data extraction requirements.
Member Details: Option to include detailed profile information for each member, including their contributions, group memberships, and daily activities.
New Feature: Include Contacts from Member Websites
You can now scrape the following additional contact information directly from members' websites, if the websites are linked on their Skool profiles:
This new feature can be enabled by setting the includeContactsFromWebsite
option in the configuration:
1"includeContactsFromWebsite": { 2 "title": "Include Contacts from Website (if website is present on the user account)", 3 "type": "boolean", 4 "description": "Set to true if you want to include contacts from website (if website is present on the user account) like emails, phones, LinkedIns, Twitters, Instagrams, Facebooks, YouTubes, TikToks, Pinterests, Discords in the scraping.", 5 "default": false 6}
Setting "includeContactsFromWebsite": true
allows you to gather a richer set of data, making your scraping process more comprehensive.
https://www.skool.com/{group-name}/-/members
. You can add multiple URLs for a broader scraping scopeincludeProfileDetails
option.To initiate a search, you can provide input data in JSON format. Below is an example configuration for scraping agents with proxies and max items set to 100 and etc:
1{ 2 "startUrls": [ 3 { 4 "url": "https://www.skool.com/ai-automation-mastery/-/members" 5 } 6 ], 7 "includeAdminUsers": true, 8 "includeProfileDetails": true, 9 "includeContactsFromWebsite": true, 10 "maxConcurrency": 10, 11 "minConcurrency": 1, 12 "maxRequestRetries": 10, 13 "maxItems": 100, 14 "proxy": { 15 "useApifyProxy": true 16 } 17}
With the new feature enabled, the output data format will now also include any of the additional contact details found on members' websites. This means the output will contain both the standard Skool profile data as well as any relevant information found on their linked website. The scraper outputs data in the following structure:
1{ 2 "id": "f49074d0a8a441e994f900857616e722", 3 "name": "nate-l-6118", 4 "metadata": { 5 "bio": "Electronic & Computer Engineer | Software Developer | Ecom Coach", 6 "chatRequest": 1, 7 "lastOffline": 1730334152541737500, 8 "linkFacebook": "", 9 "linkInstagram": "", 10 "linkLinkedin": "", 11 "linkTwitter": "", 12 "linkWebsite": "", 13 "linkYoutube": "", 14 "location": "", 15 "myersBriggs": "", 16 "pictureBubble": "https://assets.skool.com/f/f49074d0a8a441e994f900857616e722/f6ec32371b9d406ca46f6759fb39c02a031bd41e483e41d6b34ecbe0150cd77b-sm.jpg", 17 "pictureProfile": "https://assets.skool.com/f/f49074d0a8a441e994f900857616e722/f6ec32371b9d406ca46f6759fb39c02a031bd41e483e41d6b34ecbe0150cd77b", 18 "spData": "{"pts":0,"lv":1,"pcl":0,"pnl":5,"role":4}" 19 }, 20 "createdAt": "2024-05-09T00:59:08.378173Z", 21 "updatedAt": "2024-10-31T12:02:09.061911Z", 22 "email": "", 23 "firstName": "Nate", 24 "lastName": "L", 25 "member": { 26 "id": "0b2e8521ab7a4be0b15b387f985a684c", 27 "metadata": { 28 "requestedAt": 1727605967758303000 29 }, 30 "createdAt": "2024-09-29T10:32:47.757314Z", 31 "updatedAt": "2024-10-31T00:22:32.543574Z", 32 "userId": "f49074d0a8a441e994f900857616e722", 33 "groupId": "54756f6f5e1843a49f13ea4df3d060ac", 34 "role": "member", 35 "approvedAt": "2024-09-29T11:00:25.054595Z", 36 "lastOffline": "2024-10-31T00:22:32.543574Z" 37 }, 38 "url": "https://www.skool.com/@nate-l-6118", 39 "userDetails": { 40 "id": "f49074d0a8a441e994f900857616e722", 41 "name": "nate-l-6118", 42 "metadata": { 43 "bio": "Electronic & Computer Engineer | Software Developer | Ecom Coach", 44 "lastOffline": 1730334152541737500, 45 "linkFacebook": "", 46 "linkInstagram": "", 47 "linkLinkedin": "", 48 "linkTwitter": "", 49 "linkWebsite": "", 50 "linkYoutube": "", 51 "location": "", 52 "myersBriggs": "", 53 "pictureBubble": "https://assets.skool.com/f/f49074d0a8a441e994f900857616e722/f6ec32371b9d406ca46f6759fb39c02a031bd41e483e41d6b34ecbe0150cd77b-sm.jpg", 54 "pictureProfile": "https://assets.skool.com/f/f49074d0a8a441e994f900857616e722/f6ec32371b9d406ca46f6759fb39c02a031bd41e483e41d6b34ecbe0150cd77b" 55 }, 56 "createdAt": "2024-05-09T00:59:08.378173Z", 57 "updatedAt": "2024-10-31T12:02:09.061911Z", 58 "email": "", 59 "firstName": "Nate", 60 "lastName": "L", 61 "profileData": { 62 "page": 1, 63 "filter": "", 64 "tabName": "posts", 65 "itemsPerPage": 30, 66 "following": false, 67 "followed": false, 68 "totalPosts": 103, 69 "totalFollowers": 3, 70 "totalFollowing": 12, 71 "totalSharedGroups": 0, 72 "groupsMemberOf": [ 73 { 74 "id": "bfe19873018549ed8774addfff3cce3e", 75 "name": "automate", 76 "metadata": { 77 "color": "#F46E6E", 78 "coverSmallUrl": "https://assets.skool.com/f/bfe19873018549ed8774addfff3cce3e/aa83713378ca41de9edbd4327f6338444a11019c0d0244baa391c6891152bf04-md.jpg", 79 "createdBy": "7d5dbcc44e3b4ffd907254d5283b593f", 80 "description": "The only resource you will ever need to learn and sell automations to businesses! See you inside.", 81 "displayName": "Automation Incubator™", 82 "faviconUrl": "https://assets.skool.com/f/bfe19873018549ed8774addfff3cce3e/7a391dec5a8a4ac7869f7bcabe9b636d53206f7fde42437f9e676f53a3d5806d", 83 "initials": "A2", 84 "totalAdmins": 5, 85 "totalMembers": 15512, 86 "totalOnlineMembers": 62, 87 "totalPosts": 1079, 88 "totalRules": 3 89 }, 90 "createdAt": "2023-12-28T22:57:52.957417Z", 91 "updatedAt": "2024-10-31T12:46:08.701643Z" 92 } 93 ], 94 "totalContributions": 103, 95 "chatRequest": false, 96 "dailyActivities": { 97 "startDate": "2023-11-06T00:00:00Z", 98 "endDate": "2024-10-31T00:00:00Z" 99 }, 100 "totalGroups": 13 101 } 102 }, 103 "contacts": { 104 "emails": [], 105 "phones": [], 106 "phonesUncertain": [], 107 "linkedIns": [ 108 "https://www.linkedin.com/company/calendly/" 109 ], 110 "twitters": [ 111 "https://twitter.com/calendly" 112 ], 113 "instagrams": [ 114 "https://www.instagram.com/calendly/" 115 ], 116 "facebooks": [ 117 "https://www.facebook.com/calendly" 118 ], 119 "youtubes": [ 120 "https://www.youtube.com/c/Calendly" 121 ], 122 "tiktoks": [], 123 "pinterests": [], 124 "discords": [] 125 } 126}
Skool Posts(Content) with Comments Scraper - unlock valuable insights from Skool.com discussions. Extract comprehensive post data and nested comments with ease, empowering your community analysis and content strategy.
Yes, if you're scraping publicly available data for personal or internal use. Always review Websute's Terms of Service before large-scale use or redistribution.
No. This is a no-code tool — just enter a job title, location, and run the scraper directly from your dashboard or Apify actor page.
It extracts job titles, companies, salaries (if available), descriptions, locations, and post dates. You can export all of it to Excel or JSON.
Yes, you can scrape multiple pages and refine by job title, location, keyword, or more depending on the input settings you use.
You can use the Try Now button on this page to go to the scraper. You’ll be guided to input a search term and get structured results. No setup needed!