Why generic scrapers fail at scale
Retailers run sophisticated anti-bot systems that watch for behavior typical of price monitoring: hitting the same high-margin product pages over and over, never adding to cart, never checking out. A basic scraper falls into this pattern and gets blocked within hours. A good price-monitoring API avoids it by rotating residential IPs by country, varying how requests look, and capping how many requests hit a single site at once — so no single identity stands out.
Geo-targeting matters more than you think
Prices are not the same everywhere. A major marketplace's prices, stock, and shipping eligibility change by country and even by ZIP code; big-box retailers show different inventory per store. If you scrape from the wrong location, you collect the wrong numbers and your pricing decisions are off from the start. Geo-targeting means choosing where your request appears to come from. A good API lets you pick the proxy's country and city per request, so you track the exact markets you sell in.
Structured output vs raw HTML
Some scraping APIs hand back raw HTML and leave the parsing (pulling the price and other fields out of the page) to you. For price monitoring, prefer APIs that ship ready-made extractors for the big retailers — they absorb layout changes for you, so a retailer redesign does not break your pipeline at 3am. For smaller, long-tail hosted-platform stores, plain HTML plus a small extraction layer (CSS selectors, which point at elements on the page, or LLM-based extraction) is usually the simpler choice.