How to Batch-Scrape 10 Vinted Search URLs in One Run: A Reseller's Workflow

Two weeks ago, a reseller I work with asked me a surprisingly common question:

"I track 12 different brands across Vinted. That means 12 different search URLs, 12 different filter combinations, 12 different countries depending on where inventory is cheapest. Right now I run them one by one. How do I automate all of this without writing orchestration code?"

The short answer: paste all 12 URLs at once.

The tool: Vinted Turbo Scraper.

This article breaks down the exact batch workflow I set up for him — and why it's the most underused feature of the Actor.

📺 Watch the Tutorial

Why Batch URLs Matter (More Than Speed)

Speed is great. But for serious resellers and market researchers, throughput is what actually moves the needle.

Here's the reality of single-URL scraping:

Most people never think about batching because:

1. Vinted's own site doesn't suggest it
2. Most Python scrapers on GitHub are built for single requests
3. Apify Actors often look like they only accept one input

Vinted Turbo Scraper accepts an array of URLs. Not one. An array. Paste 10, get 10 datasets merged into a single export.

Real-World Use Cases

Before diving into the how-to, here's who actually uses this feature:

Multi-brand resellers — tracking Nike, Adidas, Jordan, New Balance, and vintage Patagonia simultaneously across the same country domain.

Cross-country arbitrageurs — monitoring the same keyword across Vinted.fr, Vinted.de, Vinted.nl, and Vinted.pl to spot price gaps.

Category monitors — running separate searches for Men's Sneakers, Women's Sneakers, and Kids' Sneakers with different size filters.

Deal hunters — setting up 15–20 hyper-specific filter combos (brand + price + size + condition + color) and running them all nightly via Apify's scheduler.

How to Batch-Scrape Vinted URLs: Step-by-Step

Step 1: Prepare your search URLs

This is identical to single-URL mode. For each segment you want to track:

1. Go to Vinted (any country domain)
2. Apply filters: brand, size, price range, condition, color, category
3. Copy the URL from your browser bar
4. Repeat for every segment you want

Example URL set for a sneaker reseller:

https://www.vinted.fr/catalog?search_text=jordan&price_from=50&price_to=100&size_from=42&size_to=44&status_id=6
https://www.vinted.fr/catalog?search_text=nike&price_from=30&price_to=80&size_from=40&size_to=45&status_id=6
https://www.vinted.de/catalog?search_text=jordan&price_from=40&price_to=90&status_id=6
https://www.vinted.nl/catalog?search_text=nike&price_from=35&price_to=85&status_id=6

Each URL already contains the exact filters you need. No rebuilding required.

Step 2: Configure the Actor for batch mode

1. Open Vinted Turbo Scraper on the Apify Store
2. Click Try for free
3. In the Input tab, locate the searchURLs field
4. Paste your URLs — one per line, or as a JSON array:

Plain text input:

https://www.vinted.fr/catalog?search_text=jordan...
https://www.vinted.fr/catalog?search_text=nike...
https://www.vinted.de/catalog?search_text=jordan...
https://www.vinted.nl/catalog?search_text=nike...

JSON input (for API/programmatic runs):

{
  "searchURLs": [
    "https://www.vinted.fr/catalog?search_text=jordan&price_from=50&price_to=100",
    "https://www.vinted.de/catalog?search_text=jordan&price_from=40&price_to=90",
    "https://www.vinted.nl/catalog?search_text=nike&price_from=35&price_to=85"
  ]
}

Step 3: Run and export

Click Start. The Actor processes each URL sequentially but without the overhead of browser restart between URLs. Results from all URLs are merged into a single output dataset.

Export options:

• CSV — flat table, one listing per row, with an added source_url column showing which search URL each listing came from
• JSON — structured object with all fields + source attribution
• Excel — same as CSV, formatted for Excel
• Google Sheets — live push to a shared spreadsheet
• API — consume via the Apify API, perfect for custom pipelines

Step 4: Automate with scheduling (optional but recommended)

Apify has a built-in scheduler. I set mine to run every day at 6 AM CET:

1. Go to the Actor's Schedules tab in Apify Console
2. Create a new schedule: Daily at 06:00
3. Paste your URL array into the schedule input
4. Set the destination: Google Sheets, webhook, or just store in Apify's key-value store

Every morning, I wake up to a fresh dataset in my Google Sheet. Zero manual work.

What the Output Actually Looks Like

When you batch URLs, the Actor adds one critical field to every record:

{
  "url": "https://www.vinted.fr/items/987654321-nike-air-max-90",
  "title": "Nike Air Max 90",
  "price": 55.00,
  "currency": "EUR",
  "brand": "Nike",
  "size": "43",
  "condition": "Good",
  "seller_username": "paris_sneakers",
  "location": "Paris, France",
  "thumbnail": "https://images1.vinted.net/...",
  "source_url": "https://www.vinted.fr/catalog?search_text=nike&price_from=30&price_to=80",
  "scraped_at": "2026-04-24T06:03:15.000Z"
}

Key field: source_url tells you exactly which search query produced each listing. This is essential when you're running 10+ URLs simultaneously and need to segment results later.

Cost Breakdown for Batch Workflows

With Apify's $5 monthly free credits, a small batch workflow costs you nothing.

For active resellers running daily large batches: $6.75 × 30 days = ~$200/month. The time saved is roughly 2–3 hours per day of manual scraping, monitoring, and data cleaning. At any consulting rate, the ROI is immediate.

Common Batch Pitfalls (and How to Avoid Them)

Pitfall 1: Mixing country domains in one run

The Actor handles .fr, .de, .nl, .pl, .es, .it, .be, etc. natively. No issue. But be aware that pricing will be in local currencies — EUR for Eurozone, GBP for UK, PLN for Poland. Normalize in your export pipeline or spreadsheet.

Pitfall 2: URLs with too few filters

An overly broad URL (e.g., just search_text=vintage with no price/size filters) can return 10,000+ results per URL. The Actor caps per-URL extraction to prevent runaway costs, but it's better to filter aggressively on Vinted first.

Pitfall 3: Identical URLs

Deduplication happens at the dataset level, but identical URLs waste compute. Check your URL list before running.

Pitfall 4: Expecting real-time inventory

Vinted listings appear and disappear fast — especially underpriced items. A scheduled run every 6 hours catches most opportunities without hitting rate limits.

Integrating Batch Results Into Your Workflow

Here's the exact stack I use with a reseller partner:

The entire pipeline from "run Actor" to "receive Telegram alert for a €45 Jordan 1" is under 5 minutes.

FAQ

Q: What's the maximum number of URLs per run?

Tested comfortably up to 50 URLs per run. Beyond that, splitting into multiple runs is safer for stability. Each URL is processed sequentially, so it's more about total runtime than URL count.

Q: Does batch mode cost more?

No. Pricing is $0.0015 per result, regardless of how many URLs produced that result. 1,000 listings from 1 URL = $1.50. 1,000 listings from 10 URLs = $1.50.

Q: Can I batch across different Vinted country domains?

Yes. Mix .fr, .de, .nl, .pl, .es, .it, .be, etc. in the same input array. The Actor handles domain detection automatically.

Q: What if one URL fails?

Failed URLs are logged in the Actor's run log. Successful URLs still produce their dataset. No total-run failure from a single bad URL.

TL;DR

• Vinted Turbo Scraper accepts multiple search URLs in one run
• Results merge into a single export with source_url attribution
• Schedule daily runs, push to Google Sheets, build alert pipelines
• Pricing is per-result, not per-URL — batching is free in terms of cost structure
• Supports all 26 Vinted country domains in a single batch

👉 Launch Vinted Turbo Scraper

Related tools:

• Vinted Smart Scraper — Deep seller analytics + cross-country price comparison
• Vinted MCP Server — Natural language Vinted queries via AI
• How I Scrape 1,000 Vinted Listings in Under 2 Minutes — Speed-focused guide with video tutorial