How We Monitor500K+ Product Prices Across Latin America Every Hour
Price monitoring in Latin America sounds simple. Until you try it.
Between Falabella, MercadoLibre, Amazon Mexico, and dozens of regional retailers — each with different page structures, anti-bot measures, and currency systems — getting reliable price data is a nightmare.
Here's how we solved it.
The Challenge
We needed to track prices across:
- Chile: Falabella, Ripley, Paris
- Peru: Falabella Peru, Oechsle
- Colombia: Falabella Colombia, Exito
- Argentina: MercadoLibre, Garbarino
Each country has different:
- Currencies (CLP, PEN, COP, ARS)
- Tax structures
- Shipping rules
- Product naming conventions
Our Architecture
# Simplified pipeline
class PriceMonitor:
def __init__(self):
self.crawlers = {
'falabella_cl': FalabellaCLCrawler(),
'mercadolibre_ar': MercadoLibreCrawler(),
# ...30+ more
}
self.normalizer = PriceNormalizer()
self.alerts = AlertEngine()
def crawl_all(self):
for store, crawler in self.crawlers.items():
products = crawler.get_products()
normalized = self.normalizer.normalize(products)
self.alerts.check(normalized)
Key Innovations
1. Smart Price Normalization
Converting "CLP $19.990" to USD requires:
- Real-time exchange rates
- Tax inclusion handling
- Shipping cost estimation
2. Anti-Detection
We rotate through residential proxies, use Playwright with stealth plugins, and implement human-like browsing patterns.
3. Telegram Alerts
When a price drops below threshold, subscribers get instant alerts via Telegram bot:
🔥 PRICE DROP ALERT
Product: Samsung Galaxy S24
Store: Falabella Chile
Old: CLP $899,990
New: CLP $649,990 (-28%)
Link: [Shop Now]
Results
- 500K+ products tracked daily
- 15 retail platforms
- 4 countries
- 99.2% uptime
- <15min price change detection
Try It
Free Telegram bot: @PreciosML2_bot
GitHub: [Coming Soon]
What e-commerce platforms in your region would you want price monitoring for?
