Stock tracking is a harder problem than price tracking: the price is written plainly on the page, while stock is often only visible indirectly, as "out of stock" or "only X left". For this reason, stock monitoring is built on frequent sampling and change detection .
The Logic of Change Detection
Instead of storing all the data on every round, recording only the hash difference reduces the storage cost to a tenth.
Sampling Frequency and Cost
As frequency increases, both the number of requests and GB consumption rise linearly. A product page averages between 600 KB and 1.5 MB (including images). Turning off image downloads alone reduces traffic by 80%.
Turning off image downloads (theAccept header and resource filtering) is the biggest saving item in GB-based packages.
The Right IP Profile
When monitoring the Turkish market you need residential IPs exiting from TR; foreign addresses bring different content and more frequent verification. Pool size is determined by your concurrency:
This volume is comfortably covered by a mid-sized residential package. Measure your success rate before increasing concurrency.
Alert Design
- Back in stock: the transition from "out of stock" to "add to cart" — the most valuable signal.
- Price dropped: falling below the threshold you set.
- New seller: a new competitor added to the product.
- Page structure changed: a parse error — the monitor's maintenance signal.
The last item is the point most teams miss: when the target site changes its design, you silently start collecting empty data. Set up parse failure as an alert as well.
Monitoring publicly available product information for commercial analysis is common; even so, you have to comply with the target site's terms of use and its robots.txt rules. If you have official integrations as a seller, use those first.
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