Pinterest User Pins Scraper – Created, Saved & Full Pin Data

Pinterest User Pins Scraper gives you any Pinterest user's saved pins, their created pins, and full pin analysis for any pin (single or bulk) — every record packed with engagement data: saves, repins, comments, reactions, board, author, and images as clean, structured JSON. Every request hits Pinterest's servers live; there is no cached or stored data, so you always get the freshest possible data. No Pinterest API key, no browser, no coding required.

What does the Pinterest User Pins Scraper do?

Three capabilities that combine freely — check what you need and run:

• Saved pins — everything a user has saved, straight from their saved-pins feed.

• Created pins — everything a user has actually posted (their own content).

• Full pin data — two ways:

  • Paste pin URLs or IDs (one or thousands) for standalone analysis.
  • Or switch on Full pin data (enrichment) and every pin collected from the feeds is automatically re-fetched with complete detail — single or bulk, handled automatically.

• Smart bulk handling — one pin is instant; thousands are batched with automatic backoff. If Pinterest throttles, the actor stops early and keeps everything it already delivered — you're never billed for skipped pins.

• Apify Proxy on auto — no country configuration needed.

• Fair two-tier billing — feed pins get a scraping fee plus a platform data-processing fee. Fully analyzed pins get a higher scraping fee plus the same platform fee. You pay only for delivered records.

How to use it (detailed examples)

1. A user's saved pins (the default)

{
  "users": ["pinterest"],
  "savedPins": true,
  "createdPins": false,
  "maxPinsPerUser": 100
}

Real output record (saved-pins tier — 15 fields + provenance):

{
  "id": "1130333206516009145",
  "title": "Creamy Basil Walnut Pasta Recipe",
  "description": "A creamy basil and walnut pasta dish featuring velvety sauce, al dente pasta, and a touch of Parmesan for savory richness.",
  "pin_url": "https://www.pinterest.com/pin/1130333206516009145/",
  "type": "image",
  "image": "https://i.pinimg.com/736x/60/e2/40/60e240d9af83b941e8bd89432e5644fc.jpg",
  "domain": "pinterest.com",
  "saves_count": 0,
  "repins_count": 0,
  "comments_count": 0,
  "reactions_count": 0,
  "board_name": "Creamy Pasta Dishes",
  "pinner_username": "pinterest",
  "creator_username": "",
  "created_at": "2026-05-27T22:56:23.000Z",
  "username": "pinterest",
  "source": "saved_pins"
}

2. Saved + created pins together

{
  "users": ["pinterest", "@pinterest"],
  "savedPins": true,
  "createdPins": true,
  "maxPinsPerUser": 100
}

Records carry source: "saved_pins" or source: "created_pins" so the two feeds stay separable in one dataset.

3. Saved pins WITH full pin data (automatic enrichment)

{
  "users": ["pinterest"],
  "savedPins": true,
  "fullPinData": true,
  "maxPinsPerUser": 100
}

Every collected pin is automatically re-fetched with complete data — no extra input needed, single or bulk. Enriched records bill at the analysis rate ($0.004) instead of the feed rate ($0.002).

4. Analyze specific pins — single or bulk

{
  "pins": ["https://www.pinterest.com/pin/68741848186/", "50595195810048376"]
}

Mix URLs and IDs freely. Real output record (full analysis tier):

{
  "id": "68741848186",
  "title": "The BEST Zucchini Fritters",
  "description": " ",
  "pin_url": "https://www.pinterest.com/pin/68741848186/",
  "type": "image",
  "image": "https://i.pinimg.com/originals/10/12/44/101244853ccd4e5e9288f13cb91a7ecb.jpg",
  "domain": "willcookforsmiles.com",
  "saves_count": 105626,
  "repins_count": 4445,
  "comments_count": 174,
  "reactions_count": 149,
  "board_name": "veggies",
  "pinner_username": "amberwithaar",
  "creator_username": "willcook4smiles",
  "created_at": "2020-08-27T23:00:00.000Z",
  "source": "pin_analysis"
}

What data can this Pinterest user pins scraper extract?

Every pin record carries the same clean 16-field shape (plus username and source provenance on feed pins):

Field	Type	Description
id	string	Pin ID
title / description	string	Pin text
pin_url	string	Pin URL
type	string	image, video, gif, or carousel
image	string	Image URL
domain	string	Source website
saves_count	number	Times saved
repins_count / comments_count / reactions_count	number	Engagement metrics
board_name	string	Board the pin lives on
pinner_username / creator_username	string	Authors
created_at	date	ISO 8601
username	string	Which scraped user produced this record (feed pins)
source	string	saved_pins, created_pins, or pin_analysis

Pricing — two tiers, priced by what each costs to fetch

The actor uses pay-per-event pricing with two events. Because every request is made live against Pinterest's servers in real-time (there is no cached or stored data), you will see two small charges per delivered pin on your invoice: the tier-specific scraping fee plus a platform data-processing fee.

Tier	Scraping fee	Dataset fee	Total per pin
Feed pins (saved / created)	$2 per 1,000 ($0.002 each)	$0.01 per 1,000	$2.01 per 1,000 pins
Full analysis (standalone pins or enrichment)	$4 per 1,000 ($0.004 each)	$0.01 per 1,000	$4.01 per 1,000 pins

Plus:

• Actor start: $0.05 per 1,000 starts (default) — Apify covers the first 5 seconds of compute.
• Dataset item: $0.01 per 1,000 results (platform data-processing fee charged by Apify).
• Users with no pins, and pins skipped due to rate limits, are not charged.

Example costs: a user's 100 saved pins ≈ $0.20; 100 pins enriched with full data ≈ $0.40; a single pin analysis ≈ $0.004.

Performance

• Feed pins come in bulk pages — 100 pins in seconds; 1,000 (the per-user cap) in well under a minute.
• Standalone/bulk analysis: ~1 second per pin at default concurrency 5; raise to 10 for large batches.
• Rate-limit aware: automatic backoff, early-stop that keeps delivered records.

Use cases

• Influencer auditing — pull a creator's created_pins to see exactly what they posted and how it performed (saves_count, comments_count).
• Taste profiling — saved_pins reveals what a user (or a competitor's audience) actually collects.
• Pin deep-dives — paste one pin URL for instant analysis, or thousands for a full engagement study.
• Content research pipelines — combine with the Profile Scraper and Board Scraper from the same developer.

Input

See the Input tab for the full form: Users (handles, @handles, or profile URLs), the Saved pins / Created pins / Full pin data checkboxes, Pins to analyze (URLs or IDs, single or bulk), Max pins per user, Concurrency, and the standard proxy configuration (Apify Proxy on auto).

Output

The dataset contains one record per delivered pin — download as JSON, HTML, CSV, or Excel. The run's OUTPUT key summarizes feed pins vs analyzed pins.

API usage

See the API tab for copy-paste snippets. Node.js example with the Apify SDK:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('scrapeberry/pinterest-user-pins-scraper').call({
    users: ['pinterest'],
    savedPins: true,
    createdPins: true,
    maxPinsPerUser: 100,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

FAQ and disclaimers

Is the data public? Yes — the actor reads only what a logged-out visitor sees. It does not log in, access private accounts, or extract private personal data.

Our Actors are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our Actors, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

Why did some pins get skipped? Pinterest started throttling during a very large batch — the actor stopped early and kept your delivered records, and skipped pins are not billed. Lower concurrency or split the batch.

Found an issue or have an idea? Open a ticket in the Issues tab — feedback shapes the roadmap.