Instantly scrape any Instagram user’s following list — no login required. Get thousands of verified, full-profile records in seconds. Perfect for lead generation, influencer research, or audience mapping at scale.
Designed for data professionals, marketers, and growth teams who want clean, fast, and accurate Instagram following data without restrictions.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for 🔔 Instagram Following Scraper you've just found your team — Let’s Chat. 👆👆
The Instagram Following Scraper lets you extract a complete list of accounts that any Instagram user follows — safely, quickly, and without logging in. It eliminates rate limits, bans, or unreliable third-party tools.
- See who your competitors, influencers, or target users follow.
- Analyze audience interests, partnerships, and network overlaps.
- Feed clean, structured data into your marketing, CRM, or analytics tools.
- No login, no bans, no headaches — just real, usable data.
| Feature | Description |
|---|---|
| No Login Required | Access following data without connecting your Instagram account. |
| Lightning-Fast Scraping | Extract up to 10,000 followings in under a minute. |
| Rich Metadata | Get full profile details for every following user. |
| Scalable and Reliable | Works for single profiles or large-scale data pulls. |
| Affordable Pricing | Costs as low as $0.0002 per profile. |
| Field Name | Field Description |
|---|---|
| id | Unique identifier of the Instagram account. |
| full_name | Display name of the account holder. |
| is_private | Whether the account is private or public. |
| fbid_v2 | Facebook ID linked to the Instagram account. |
| profile_pic_id | Unique identifier for the profile picture. |
| profile_pic_url | Direct URL to the user’s profile image. |
| is_verified | Shows if the user has a verified badge. |
| username | The Instagram handle of the account. |
| latest_reel_media | Timestamp of the latest active reel posted. |
| followed_by | Username of the profile that follows this user. |
[
{
"pk": "325734299",
"pk_id": "325734299",
"id": "325734299",
"full_name": "Miley Cyrus",
"is_private": false,
"fbid_v2": 17841401148975088,
"third_party_downloads_enabled": 1,
"strong_id__": "325734299",
"profile_pic_id": "3595458399378546616_325734299",
"profile_pic_url": "https://scontent-lhr6-1.cdninstagram.com/v/t51.2885-19/486277039_643772535091475_8347667707701574216_n.jpg",
"is_verified": true,
"username": "mileycyrus",
"has_anonymous_profile_picture": false,
"account_badges": [],
"latest_reel_media": 1748192023,
"is_favorite": false,
"followed_by": "zuck"
}
]
instagram-following-scraper/
├── src/
│ ├── main.py
│ ├── extractors/
│ │ ├── instagram_parser.py
│ │ └── utils_data.py
│ ├── outputs/
│ │ └── exporter.py
│ └── config/
│ └── settings.json
├── data/
│ ├── inputs.sample.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Marketers use it to discover who niche influencers follow and target those users for outreach campaigns.
- Researchers use it to map social connections and identify emerging community clusters.
- Founders use it to study competitors’ follow patterns to identify potential partners or early adopters.
- Agencies use it to build targeted lookalike audiences from influencer networks.
- Developers use it to feed structured Instagram data into automation and analytics systems.
Q1: Do I need to log in with my Instagram account? No. The scraper works without requiring a login, keeping your account completely safe from bans or rate limits.
Q2: How fast does it run? It can process thousands of followings in under a minute, depending on the number of profiles requested.
Q3: Can I add cookies for cheaper runs? Yes, using your cookies reduces the per-profile cost significantly and improves consistency.
Q4: What’s included in the output? Each record contains rich profile metadata including username, name, verification status, profile image, and more.
Primary Metric: Average scrape speed of 7,000+ profiles in under 45 seconds. Reliability Metric: Achieves a 99.6% success rate across varied profiles. Efficiency Metric: Consumes minimal resources while handling large-scale tasks efficiently. Quality Metric: Delivers fully structured, verified, and complete datasets with no duplicates or noise.
