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I Scraped 22,000+ Prices from 5 E-Commerce Markets — Here's What I Found and How You Can Use the Data

#webscraping #datascience #ecommerce #python

I Scraped 22,000+ Prices from 5 E-Commerce Markets — Here's What I Found

A few months ago, I started building PricePulse — a real-time pricing API that monitors product prices across multiple e-commerce marketplaces. What started as a small tool for personal arbitrage tracking quickly grew into a dataset of 22,000+ product records spanning 5 different markets.

Here's what I learned, and how you can use this data.

The Markets I'm Tracking

Marketplace Region Focus
Carousell Singapore Second-hand electronics, fashion, luxury
Vinted Europe Vintage clothing, accessories
Amazon SG Singapore Electronics, books, home goods
Lazada SE Asia General e-commerce
eBay Global Everything

What the Data Shows

Cross-Border Arbitrage Is Real

The most interesting patterns appear when you compare Singapore Carousell prices to European Vinted prices. Here's a concrete example:

Apple MacBook Pro 13" 2020: S$499 on Carousell SG ≈ ¥499 CNY

Same model on Chinese market: ~¥5,000 CNY

Potential profit margin: ~80% after shipping

This pattern repeats across iPhone, gaming hardware, and luxury goods. The price differences aren't small — they're often 2-5x.

Regional Price Differences

Some products show massive regional variations:

  • Apple products: 30-50% cheaper in Singapore than Europe
  • Nike/Adidas: Vintage models 40-60% cheaper on Vinted than Asian markets
  • Camera gear: Professional lenses 25-40% cheaper in EU second-hand markets
  • Gaming hardware: PS5, Nintendo Switch 15-20% cheaper in Singapore

How the API Works

The stack is straightforward:

# Simple API call — one endpoint, real data
GET https://pricepulseapi.site/v1/search?q=iPhone+15&source=carousell

# Response
{
  "results": [
    {
      "title": "iPhone 15 Black 128GB Unlocked",
      "price": 163.0,
      "currency": "SGD",
      "url": "https://carousell.sg/...",
      "source": "carousell"
    }
  ]
}
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No complex setup. No authentication headaches. One API key, real data.

The Dataset

After weeks of continuous scraping, I've packaged the raw data into a downloadable dataset:

What's included:

  • 22,000+ product records
  • CSV + JSON formats
  • Product title, price, currency, URL, seller info
  • Multiple categories (electronics, fashion, gaming, cameras, luxury)
  • Weekly updates with free re-downloads

Use cases:

  • Market research & competitor analysis
  • ML/AI training data for pricing models
  • Cross-border arbitrage opportunity scanning
  • Academic research on e-commerce pricing

You can grab the dataset here: PricePulse Dataset — $9.99 one-time

Free Tier Available

The API itself is free for up to 100 calls/day — no credit card required. Just sign up here and get an API key instantly.

For heavier usage, paid plans start at $10/month (1,000 calls/day).

What I'm Building Next

I'm currently working on:

  • Camera-based product recognition — point your phone at a product, get its price across all markets
  • Real-time alerting — get notified when a product drops below your target price
  • More data sources — adding Mercari, Poshmark, and Depop

If you're interested in the data or the API, check out PricePulse or grab the dataset directly.

Built with Python, FastAPI, and a lot of coffee. Solo dev, one server, real data.

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