Most beginners buy proxies "by eye" — they take the first available plan, and after a week realize that they either overpaid by twice, or the traffic was insufficient, and the accounts got banned due to constant IP changes. To avoid wasting the budget, it's enough to calculate four variables before payment. Below is a working formula and three ready-made calculations for arbitrage, SMM agencies, and marketplace monitoring.
Why You Need to Calculate the Budget Before Purchase, Not After
Proxies are not a one-time purchase, but a constant expense that scales with the business. If you manage 5 Instagram accounts, a plan with 1 GB of traffic per month may be sufficient. But as soon as the number of accounts grows to 30-50, the same plan will run out in three days, and you will either be left without proxies in the midst of warming up, or you will have to buy traffic at an unfavorable price in small batches.
An error in budget calculation leads to two scenarios. The first is overpayment: you take an unlimited plan for residential proxies, although cheap data center proxies would suffice for price scraping on Ozon. The second is underestimation: you take the minimum package of mobile proxies for TikTok farming, and a week later the accounts get banned because there weren't enough IPs, and you had to use one address for several profiles at once.
Calculating the budget in advance solves both problems. You know exactly how much traffic or how many IP addresses you need for a month, what type of proxy to choose for a specific task, and how long the purchased volume will last at the current pace of work. This is especially critical for arbitrage specialists, where every day of downtime in the ad account means lost profit, and for SMM agencies, where the client pays for the stable operation of accounts, not for experiments with proxies.
Formula of 4 Variables
The proxy budget depends not on one parameter, but on a combination of four variables. If at least one of them is not taken into account, the calculation will be inaccurate. The formula looks like this:
Budget = N × T × V × K
where N is the number of accounts/tasks, T is the type of proxy (residential, mobile, data center), V is the volume of traffic or number of IPs per task, K is the reserve coefficient for peak loads (usually 1.2–1.5).
Let's break down each variable in detail.
N — number of accounts or parallel tasks. This is the starting point for the calculation. For SMM — the number of client profiles in Dolphin Anty or AdsPower. For arbitrage — the number of Facebook Ads or TikTok Ads accounts. For e-commerce — the number of product items or competitor stores that need to be monitored simultaneously.
T — type of proxy. This affects the price per unit of traffic or per IP. Residential proxies are more expensive than data center proxies, but are needed where maximum similarity to a regular user is important — for example, for social networks and marketplaces with strict anti-fraud protection. Data center proxies are cheaper and faster, suitable for tasks without strict behavior checks, such as basic scraping.
V — volume of traffic or IPs per task. Here, it's important not to guess, but to measure. One warming up of an Instagram account with viewing the feed and stories typically consumes 150-300 MB per day. One cycle of scraping 1000 product cards on Wildberries takes 50-100 MB, depending on whether you are scraping just prices or also images with descriptions.
K — reserve coefficient. Any budget without a reserve risks running out at the wrong moment — during the launch of an advertising campaign or overnight scraping. The standard reserve is 20-50% above the calculated volume, depending on the stability of the task.
Calculation #1: SMM Agency, 30 Instagram Accounts
The agency manages 30 client accounts on Instagram through Dolphin Anty. Each account needs a separate stable IP to avoid linking profiles to one address. The task involves posting, responding in direct messages, and working with stories every day.
- N = 30 accounts
- T — residential proxies, as Instagram actively checks behavior and IP type
- V — on average 250 MB per account per day, which means 7.5 GB per day for all 30 profiles, about 225 GB per month
- K = 1.3 — reserve for active days with live broadcasts and uploading Reels
The total traffic volume: 225 GB × 1.3 ≈ 293 GB per month. For this volume, it makes sense to choose a package plan for residential proxies with IP rotation for each account — this reduces the risk of linking and allows maintaining the same IP for a specific profile throughout the work, which is important for Instagram's algorithm trust.
Additionally, the agency should consider seasonality: during the launch of client advertising campaigns, activity in accounts increases by 30-40%, so the reserve coefficient can be raised to 1.5 during such periods.
Calculation #2: Arbitrage, Facebook Ads, 20 Accounts
The arbitrage specialist launches traffic through 20 Facebook Ads accounts, each linked to a separate profile in AdsPower. The task involves farming accounts before launching campaigns plus constant monitoring of statistics.
- N = 20 accounts
- T — mobile proxies, as Facebook trusts mobile IPs significantly more than regular residential ones when working with ad accounts
- V — 400 MB per account per day (farming + checking statistics + launching ads), totaling 8 GB per day for all accounts, about 240 GB per month
- K = 1.4 — increased reserve, as traffic consumption sharply rises on days of launching new campaigns
The total volume: 240 GB × 1.4 ≈ 336 GB per month. For such a load, arbitrage specialists usually take mobile proxies with the ability to bind a static IP to an account — this is critical to avoid chain bans, where blocking one account leads to the others being blocked that are linked to the same IP or device.
An important point: if some accounts are new and in the warming phase, while others are already launched with active campaigns, it makes sense to divide the budget into two pools of traffic with different reserve coefficients to avoid mixing risks.
Calculation #3: Seller, Price Monitoring on Wildberries
The seller monitors prices of 15 competitors on Wildberries and Ozon, with 2000 product items each, once a day. The task does not require emulating live user behavior, but it is necessary to bypass blocks due to request frequency.
- N = 15 competitor stores
- T — data center proxies, as the task is mass and does not require high similarity to a real user; speed and low price per IP are important
- V — scraping 2000 product cards takes about 80 MB, totaling 1.2 GB per day for all 15 stores, about 36 GB per month
- K = 1.2 — a small reserve in case of repeated requests due to errors
The total volume: 36 GB × 1.2 ≈ 43 GB per month. Here, data center proxies are optimal — they are faster than residential ones and are cheaper for a large number of requests, which is critical for daily scraping of thousands of product cards.
If Wildberries starts banning IPs due to request frequency, it is advisable to increase the number of parallel addresses rather than the volume of traffic — this changes variable N in the formula, not V, so the budget needs to be recalculated for the new number of IPs.
Comparison of Proxy Types by Cost and Tasks
Below is a summary table that helps quickly orient which type of proxy to budget for a specific task.
| Type of Proxy | When to Choose | Relative Cost |
|---|---|---|
| Residential Proxies | Instagram, TikTok, social networks with anti-fraud checks | Medium-High |
| Mobile Proxies | Facebook Ads, TikTok Ads, accounts with a high risk of banning | High |
| Data Center Proxies | Scraping Wildberries, Ozon, Avito, mass requests | Low |
General rule: the stricter the platform checks user behavior, the closer the type of proxy should be to a "live" IP of a real person. Social networks and advertising platforms require residential or mobile addresses, while mass data scraping without emulating behavior can be covered by cheaper data center proxies.
Common Mistakes in Budget Calculation
Even knowing the formula, it's easy to make mistakes in the details. Here are five typical blunders that arbitrage specialists, SMM professionals, and sellers encounter when planning proxy expenses.
1. Calculation without considering peak loads. If you calculate the budget based on an average day rather than the most active one, the plan will run out precisely at the moment of launching a campaign or during a sale on Wildberries, when price monitoring is especially important.
2. Ignoring the task type when choosing the type of proxy. Using cheap data center proxies for Instagram farming is a common cause of instant bans because the platform easily identifies data center IPs and marks the account as suspicious.
3. Estimating traffic "by eye" without measurement. The actual traffic consumption per account depends on activity: watching videos on TikTok consumes much more data than simply scrolling through the feed on Facebook. Before purchasing a large package, it's worth measuring consumption on 2-3 test profiles.
4. Lack of budget separation by work stages. Warming up a new account and working with an already promoted profile require different volumes of traffic — warming up usually consumes less than the active phase with advertising or content.
5. Forgotten reserve coefficient. Calculating too tightly without a reserve is a guaranteed downtime at the most inconvenient moment. It's better to allocate 20-30% on top than to stop work in the middle of an advertising campaign.
Conclusion
The formula "N × T × V × K" transforms the choice of proxy from guessing into a concrete calculation: how many accounts or tasks, what type of proxy is suitable for the platform, how much traffic is actually needed, and what reserve to allocate for peak loads. The three examples show that even seemingly similar tasks — account farming, advertising, and scraping — require different types of proxies and different budget volumes.
If you manage clients' social networks or warm up accounts manually, start with residential proxies — they provide the best balance between platform trust and cost. For ad accounts with a high risk of blocking, consider mobile IPs, while for mass price monitoring and data scraping, data center proxies work cheaper and faster. Accurate budget calculation before purchase saves not only money but also time spent on dealing with sudden bans and downtimes.