How Much Does It Cost to Monitor 10,000 Products Monthly: Traffic Calculation and Proxy Selection

Sellers on Wildberries and Ozon often estimate their proxy budget "by eye" — either overpaying by 3-4 times, or purchasing a package that is too cheap, which runs out in a week. Let’s analyze how to correctly calculate the volume of traffic needed to monitor 10,000 products per month, what type of proxy to choose for such a load, and where to save without losing data quality.

Why monitor 10,000 products instead of 100

If you have 100-200 products, you can check competitor prices manually once a day. But when the catalog grows to thousands of SKUs, and competitors change prices 5-10 times a day (especially during promotions on Wildberries and Ozon), manual monitoring becomes a fiction — data becomes outdated faster than you can collect it.

10,000 products is a typical volume for an average seller with several categories or an agency that monitors for 5-10 clients simultaneously. For such scale, automation is needed: a script or a ready-made parsing service that hits product cards, category pages, and marketplace APIs tens of thousands of times a day. And here arises the main question — through what to send these requests to avoid IP blocking within the first two hours of operation.

Wildberries, Ozon, and Avito actively protect against scraping: they implement CAPTCHAs, throttle response speed, and ban datacenter IPs in bulk. Therefore, the budget for monitoring is not only the payment for servers and development, but also a separate expense item for proxies, which is often the most unpredictable if calculated "by eye."

How many requests are actually needed per month

The first step in budgeting is to understand how many HTTP requests you physically need to make. This depends on the frequency of price updates that you incorporate into your monitoring strategy.

Update Frequency	Requests per Product per Month	Requests for 10,000 Products
Once a day	30	300,000
Four times a day	120	1,200,000
Once an hour (24 times a day)	720	7,200,000

For most sellers on Wildberries and Ozon, 4-6 updates per day are sufficient — this covers morning and evening price wars without excessive load on the proxy pool. Hourly monitoring is only needed in highly competitive niches (electronics, cosmetics) during major promotions like "Black Friday."

Traffic calculation formula

The traffic that "weighs" on proxies depends not only on the number of requests but also on what you are parsing: the entire product card (HTML page with images and scripts) or just the JSON response from the marketplace API.

The average response size varies significantly depending on the method:

• API request for product card (JSON) — 15-60 KB per response
• Full HTML page of product card — 300-900 KB per response
• Category/search page with pagination — 500-1500 KB per response

If you are scraping directly through the internal APIs of marketplaces (which is preferable — less weight, higher speed, lower CAPTCHA risk), for 10,000 products with 4 updates per day, we get 1,200,000 requests × 40 KB ≈ 45.8 GB of traffic per month. If scraping full HTML pages, the same number of requests "weighs" already 600-900 GB — a difference of 15-20 times just due to the data collection method.

Datacenter, residential, and mobile proxies: what to choose

The type of proxy directly affects both the cost and the success rate of requests. For monitoring marketplaces, this is critical: the more often a proxy gets banned, the more retries are needed, and the higher the actual traffic consumption beyond the calculated formula.

Proxy Type	Success Rate on WB/Ozon	When to Use
Datacenter Proxies	40-60% (easily banned in bulk)	Low-frequency monitoring, test runs, small catalogs
Residential Proxies	85-95%	Main option for 10,000+ products, daily monitoring
Mobile Proxies	90-98%	High-frequency monitoring in tough niches, bypassing enhanced protection

Datacenter proxies may seem cost-effective per GB, but in practice, for Wildberries and Ozon, their success rate drops after just a few hours of active scraping — marketplaces identify the IP address ranges of hosting providers and cut access in bulk. As a result, you pay for traffic that is spent on retries, not on actual successful requests.

Residential proxies use real IPs of home users, so they are perceived by the marketplace as regular website visitors. For stable monitoring of 10,000 products, this is the optimal balance of price and reliability. Mobile proxies provide an even higher success rate but are usually more expensive — they should be connected selectively, for the most problematic categories or during peak promotional periods.

Three budget calculation scenarios

Let’s analyze three typical scenarios for monitoring 10,000 products to show how the data collection method and update frequency affect the total traffic volume.

Scenario 1: Frugal monitoring via API

4 updates per day, scraping through the internal marketplace APIs (JSON, ~40 KB per response), residential proxies with a 90% success rate.

• Base requests: 1,200,000 per month
• Considering 10% retries: 1,320,000 requests
• Traffic: 1,320,000 × 40 KB ≈ 50.4 GB per month

Scenario 2: Medium load with HTML page scraping

6 updates per day, scraping full product cards (HTML, ~500 KB per response) to obtain not only prices but also stock levels, reviews, and search rankings.

• Base requests: 1,800,000 per month
• Considering retries (15%): 2,070,000 requests
• Traffic: 2,070,000 × 500 KB ≈ 987 GB per month

Scenario 3: High-frequency monitoring during peak season

Hourly updates (24 times a day) via API, additionally scraping category pages to track rankings in search results, mobile proxies for problematic categories.

• Requests for products: 7,200,000 per month (at 40 KB)
• Requests for category pages: 300,000 per month (at 800 KB)
• Traffic: (7,200,000 × 40 KB) + (300,000 × 800 KB) ≈ 274.7 + 228.9 ≈ 503.6 GB per month

The difference between the scenarios clearly shows: the data collection method affects the budget more than the update frequency. Switching from HTML scraping to API usage can reduce traffic consumption by 10-20 times while maintaining the same number of products and the same frequency of checks.

How to reduce traffic consumption without losing data

There are several practical techniques that allow you to keep the monitoring budget under control without losing data relevance.

1. Scrape APIs, not HTML. If the marketplace provides data through an internal API (this can be determined by analyzing network requests in the browser when opening a product card), use it — the response weight drops by 10-20 times.
2. Prioritize products. Not all 10,000 SKUs are equally important. Monitor high-competition leading products every hour, while others — 1-2 times a day. This reduces the overall volume of requests by 40-60%.
3. Cache static data. Product name, description, and characteristics change rarely — they only need to be collected once a week. Only price and stock levels need to be updated hourly.
4. Set up proxy rotation wisely. Changing IP too frequently for each request increases the number of CAPTCHAs and retries. Rotating once every 5-10 requests from one IP usually provides a better balance between anonymity and success rate.
5. Compress traffic using gzip. Ensure that your script or parsing service sends the header Accept-Encoding: gzip — this reduces the weight of JSON responses by 60-70%.

Common mistakes in budget calculation

When planning the budget for monitoring 10,000 products, sellers regularly make the same mistakes, which lead to overspending or, conversely, a lack of traffic during the month.

• Not accounting for retries. When working with datacenter proxies, up to 40-50% of requests may end in CAPTCHA or blocking — the actual traffic consumption turns out to be 1.5-2 times higher than calculated.
• Monitoring everything with the same frequency. If 10,000 products are updated hourly "just in case", the budget skyrockets without real benefits for the business.
• Forgetting about seasonality. During sales periods (11.11, "Black Friday", New Year), competitors change prices more often, and along with this, the number of your retry requests increases due to stricter marketplace protections against scraping.
• Calculating traffic only by the formula, without a buffer. It is wise to allocate a 20-30% buffer of traffic beyond the calculated volume in case of changes in the structure of marketplace pages or temporary increases in CAPTCHAs.

Checklist before launching monitoring

Conclusion

The budget for monitoring 10,000 products per month is not a fixed number, but the result of specific decisions: how often to update prices, through what to scrape data, and what type of proxy to use. A correct calculation of traffic using the formula "number of requests × response weight" with a buffer for retries allows you to understand the actual cost of monitoring in advance and avoid unpleasant surprises in the middle of the month.

For stable monitoring of Wildberries, Ozon, and Avito at an average and large scale, we recommend starting with residential proxies — they provide a high success rate at an acceptable traffic cost. If specific product categories fall under enhanced marketplace protection, selectively connect mobile proxies specifically for them, rather than for the entire catalog at once — this will help control the budget without losing data quality.