Monitoring competitors' prices, website positions, or product availability is a routine task that, if proxies are not set up correctly, can lead to constant blocks and wasted traffic budget. We analyze 12 real monitoring scenarios, select the optimal type of proxy for each, and calculate how much traffic this will consume over a month.
Why Proxies are Needed for Monitoring
Any website with high traffic — Wildberries, Ozon, Yandex, Google, Facebook — tracks the frequency of requests from a single IP. If you check a competitor's prices once an hour from one address, the system quickly presents a CAPTCHA and then completely blocks the IP. For a one-time visit, this is not a problem, but for monitoring that needs to operate 24/7 and query hundreds of pages a day, a single IP guarantees a ban within a day or two.
Proxies solve the load distribution problem: instead of one IP, requests come from dozens or hundreds of different addresses, and for the platform, it looks like ordinary visitors from different cities, not a bot. The second point is geolocation. Prices on Wildberries, Google search results, and even currency rates can vary depending on the region, so proxies of the right type and geolocation are also a way to obtain accurate data, not distorted ones.
However, not all proxies are equally suitable for different tasks. For monitoring prices on a marketplace, residential proxies work best, while for checking website positions in search, sometimes cheaper data center proxies are sufficient. We will examine each of the 12 typical tasks separately.
Table: 12 Monitoring Tasks and Proxy Type for Each
Below is a summary table of all scenarios that we will discuss in more detail in the article. It will help you quickly orient yourself if you already know your task and are simply looking for the appropriate type of proxy.
| Monitoring Task | Proxy Type | IP Rotation | Traffic/Month (Approx.) |
|---|---|---|---|
| Prices on Wildberries | Residential | Every request | 5–15 GB |
| Prices on Ozon | Residential | Every request | 5–15 GB |
| Ads on Avito | Residential / Mobile | Every 3–5 requests | 3–10 GB |
| Positions in Yandex | Data Center / Residential | Once per session | 1–5 GB |
| Positions in Google | Residential | Once per session | 1–5 GB |
| Competitors' Ads (Facebook Ads Library) | Mobile | Once per session | 2–8 GB |
| Ads on TikTok | Mobile | Once per session | 3–10 GB |
| Product Reviews and Ratings | Residential | Every 5–10 requests | 2–7 GB |
| Product Availability in Stock | Residential | Every request | 5–12 GB |
| Brand Mentions on Social Media | Residential / Mobile | Once per session | 2–6 GB |
| Website Uptime Monitoring | Data Center | Not required | less than 1 GB |
| Currency/Cryptocurrency Rates | Data Center | Not required | less than 1 GB |
| SERP for Contextual Advertising | Residential | Once per session | 2–8 GB |
Monitoring Marketplaces: Wildberries, Ozon, Avito
Marketplaces are the most demanding category for monitoring. Wildberries and Ozon actively counteract automated data collection: they show different prices depending on the city, use dynamic layouts, and quickly ban IPs that exhibit atypical request patterns — for example, 500 requests to product cards in 10 minutes.
For a seller monitoring 200-300 competitor positions several times a day, the optimal option is residential proxies with rotation on every request. This provides two advantages: first, the system sees ordinary users from different regions, not a bot; second, you get real prices for different cities, which is critical since Wildberries shows different delivery costs and even discounts depending on the buyer's region.
For Avito, the situation is slightly different: the platform is less aggressive towards scraping ads but strictly blocks attempts to view phone numbers and seller contacts en masse. Here, a combination of residential proxies with a limit of 3-5 requests from one IP before changing works well — this reduces the load on a specific address and does not raise suspicions.
Practical Advice: If you are monitoring prices on Wildberries from several regions simultaneously (for example, Moscow, Novosibirsk, Krasnodar), create separate proxy sessions with geolocation tied to each city. This way, you get accurate local prices, not averaged data.
Monitoring Website Positions and SERP
Checking positions in Yandex and Google is a task that at first glance seems similar to scraping marketplaces, but in fact requires less traffic and does not always need the most expensive proxies. Google is quite tolerant of single requests from data center IPs, as long as the frequency does not exceed a reasonable limit — say, no more than one request from an IP every 2-3 minutes.
However, if you are checking positions for 500+ keywords daily and want to get accurate results considering personalization and geolocation of a specific region, data center proxies start to introduce inaccuracies — Google mixes in atypical results for IPs from hosting providers. In this case, switch to residential proxies tied to the desired city: this provides results that are as close as possible to what a real user of the search engine sees.
For Yandex, the situation is the opposite — it is less sensitive to the type of IP but reacts harshly to frequency. Rank-tracking services usually make one request per keyword once a day, so even data center proxies with rotation once per session work without problems and are cheaper.
Monitoring Competitors' Ads
Arbitrageurs and marketers often monitor competitors' ad creatives through Facebook Ads Library, TikTok Creative Center, and similar tools. Here, the volume of traffic is not as important as the plausibility of the session: these platforms track behavioral patterns of the device, not just the IP.
For such tasks, mobile proxies are more suitable — they use IPs from real mobile operators, and platforms perceive such connections as ordinary smartphone users who are browsing ads in their feeds. If you open Ads Library through an anti-detect browser (Dolphin Anty, AdsPower) with a mobile proxy and a realistic device fingerprint, the risk of access restrictions to the ad library is minimal even with frequent use.
The same logic applies to TikTok Creative Center: the platform aggressively bans data center IPs and often shows empty results or CAPTCHA to bots. Mobile proxies with rotation once per session (rather than on each request) provide the most stable results — the session looks like an ordinary person browsing ads, not an automated script.
Traffic Consumption Calculation by Tasks
Traffic consumption directly depends on how many pages you are querying and how "heavy" those pages are. A product card on Wildberries with images and scripts weighs 1.5-3 MB, a Google search results page — 0.5-1.5 MB, and a simple API request to check a price via JSON — only 5-20 KB.
If you are monitoring 300 product cards 4 times a day (every 6 hours) with an average page weight of 2 MB, the calculation would be: 300 × 4 × 2 MB = 2400 MB or 2.4 GB per day, which gives about 72 GB per month. This is a significant figure, and for such a volume, residential proxies with unlimited traffic or a large package will be more cost-effective than paying per traffic with each request counted.
In comparison, monitoring positions in search for 500 keywords once a day with light requests (without loading images, just HTML output) usually fits within 1-3 GB per month — here, overpaying for an expensive type of proxy makes no sense, and data center solutions perform effectively.
| Parameter | Light Monitoring (API/JSON) | Heavy Monitoring (Full Pages) |
|---|---|---|
| Weight of One Page | 5–50 KB | 0.5–3 MB |
| 300 Positions × 4 Times/Day | ~0.06 GB/Day | ~2.4 GB/Day |
| Monthly Consumption | ~1.8 GB | ~72 GB |
How to Set Up Proxies in Parsers and Anti-Detect Browsers
Most ready-made monitoring tools — from no-code parsers to anti-detect browsers — support proxy connections in a few clicks, without writing code. Let's go through a typical setup using Dolphin Anty, which is often used for monitoring ads and social media.
In Dolphin Anty, create a new profile → open the "Proxies" section → choose the connection type HTTP or SOCKS5 → insert the username, password, IP address, and port provided by the proxy provider → click "Check" to test the connection → save the profile. After this, all browser traffic within this profile will go through the specified proxy, and the device fingerprint (user-agent, screen resolution, time zone) will remain tied to the profile.
For no-code price parsers (for example, marketplace monitoring services), the setup usually looks like this: in the task settings, specify the list of proxies in the format IP:port:username:password → choose the rotation mode — "on each request" or "every N minutes" → set the interval between requests to avoid exceeding the platform limits. For Wildberries and Ozon, the recommended interval is at least 2-3 seconds between requests from one IP, even with rotation.
If monitoring is done through AdsPower or GoLogin, the logic is the same: the proxy is tied to the browser profile, not to the task as a whole, allowing you to maintain dozens of parallel monitoring sessions with different IPs simultaneously — convenient when you need to check prices from several regions at once.
Common Mistakes When Choosing Proxies for Monitoring
The first and most common mistake is using cheap data center proxies for monitoring marketplaces. Wildberries and Ozon have long blacklisted IP ranges of major hosting providers, so requests from such addresses receive CAPTCHA almost immediately, even at low frequency.
The second mistake is too aggressive rotation where it is not needed. For website uptime monitoring or checking currency rates, changing IP on every request is just unnecessary expenses without additional benefit, as such services rarely ban by IP at low request frequencies.
The third mistake is ignoring geolocation. If you are monitoring prices for the "Moscow" region, but the proxy is physically located in another country, the platform may show default data or even block access as suspicious traffic from an atypical location.
The fourth mistake is underestimating traffic volume at the start. Many take a small package, and after a week hit the limit because they did not calculate the page weight and request frequency in advance. The calculation from the previous section of the article will help avoid this situation.
Conclusion
The correct choice of proxies for monitoring depends on the specific task: marketplaces and social media require residential or mobile IPs with frequent rotation, while for checking positions in Yandex, uptime monitoring, or currency rates, cheaper data center solutions are sufficient. The main thing is to estimate the traffic volume and request frequency in advance to avoid overpaying for excessive rotation where the platform is not aggressive towards scraping.
If you plan to monitor prices on marketplaces or track competitors' ads on social media, start with residential proxies — they offer the lowest risk of blocks and accurate geolocation data. For lighter tasks like checking search positions or monitoring website availability, data center proxies will perform just as well and be cheaper when calculated per traffic volume.