From Proxies to AI: Building a Media Buyer’s Toolkit in 2026

A few years ago, a media buyer needed only an advertising account, a proxy, a few creatives, and an understanding of the audience to launch an ad campaign. Today, the working toolkit has become much broader. Depending on the task, a team may use several advertising platforms, anti-detect browsers, trackers, AI tools, analytics, and payment services.

The reason is not just that advertising platforms have become more complex. The approach to traffic buying itself has changed. A media buyer no longer focuses solely on launching ads. They manage an entire system: testing hypotheses, controlling costs, analyzing data, allocating resources, and looking for opportunities to scale.

At the same time, having more tools does not automatically make a team more effective. A team can use dozens of services and still lose money because of poor tracking, budget confusion, or a lack of coordination among team members.

Let’s look at what a media buyer’s working stack consists of in 2026 and which tools help not just launch ads, but build a sustainable traffic-buying system.

The Basic Media Buying Stack: What You Need to Launch a Campaign

Regardless of the traffic source, vertical, or team size, the basics of the work remain roughly the same. The specific services may change, but the tasks they solve stay the same.

The basic stack includes several components.

Advertising accounts. Meta Ads (Facebook and Instagram), Google Ads, TikTok Ads, and other platforms through which a team reaches its audience. The choice depends on the GEO, offer, target audience, and product specifics.

Offers and affiliate networks. Sources of offers that the team plans to promote. It is important to consider not only the payout amount, but also conversion terms, available GEOs, traffic restrictions, and lead-processing quality.

Creatives. Images, videos, copy, headlines, and other advertising materials. They help attract users’ attention and test hypotheses about which messaging works best.

Tracker. A tool for tracking clicks, distributing traffic, and analyzing campaign results. When configured correctly, it helps compare advertising costs with the conversions and revenue generated.

Analytics. A system for evaluating performance. The team uses CTR, CPC, CPM, CPA, CR, ROI, and other metrics to understand what is happening with a campaign.

Additional tools are gradually added to this set: anti-detect browsers, proxies, AI services, task management systems, financial platforms, and automation.

The key principle is that every tool should serve a specific purpose. If a service does not save time, improve control, or help with decision-making, its necessity should be reconsidered.

Proxies and Anti-Detect Browsers: The Technical Foundation of the Workflow

Proxies and anti-detect browsers have long been part of the infrastructure used by teams working with multiple advertising accounts and profiles.

Proxies let users establish a network connection through an intermediary server. Depending on the task, residential, mobile, and datacenter solutions may be used. They differ in connection characteristics, stability, speed, and cost.

When choosing a proxy, consider:

• The IP’s geographic location and whether it matches the task.
• Connection type and stability.
• Speed and latency.
• IP address reputation.
• The provider’s replacement policy and technical support.

For a media buyer, however, the IP type is not the only consideration. The way the work session is organized also matters.

Stable Session or IP Rotation: Which Should You Choose?

If a specialist needs to return to the same work profile regularly, it is worth considering connection stability and the ability to keep the same IP for the required period.

For example, a buyer may work with a project’s advertising account every day. In this case, a predictable connection may be more convenient than automatically changing the address with every new request.

Rotating proxies serve other purposes—for example, checking how advertising materials appear in different regions or collecting data for market analysis, provided that such collection is allowed by the relevant websites’ rules.

At the same time, changing an IP does not, by itself, make an advertising account more reliable or guarantee that additional checks will not occur.

Proxy selection should start with a clear understanding of the task: do you need a persistent session, a specific GEO, high speed, or the ability to work with different IPs?

You can read more about the differences between connection types in Node Proxy’s article on residential and mobile proxies.

How to Organize Work with Multiple Profiles

Anti-detect browsers let users create and store separate browser profiles with isolated settings. Within a team, this is useful for organizing workflows, separating projects, and managing access.

When choosing an anti-detect browser, consider:

• The ability to create and manage a large number of profiles.
• Compatibility with the proxies you use.
• Team features and access permissions.
• Data synchronization and backup storage.
• Ease of everyday use.

One common beginner mistake is treating an anti-detect browser and proxies as a guarantee that an advertising account will work reliably. That is not the case. They solve technical tasks, but they do not override advertising platform requirements, payment verification, or advertising policies.

Another problem is the lack of an organizational system. When one buyer has dozens of profiles and the team works across several GEOs, confusion can quickly arise without a clear structure: which proxy belongs to which project, who is responsible for a profile, and where the necessary information is stored.

For example, a team launches ads for three clients in different GEOs. If profiles have random names and connection information is stored in employees’ private messages, handing a project over to another buyer becomes a separate technical task.

That is why it is useful to assign each work profile to a project, a responsible team member, and a clear connection identifier in advance. Sensitive data should be stored in a secure system, not in a shared spreadsheet with open access.

You can read more about organizing these work environments in Node Proxy’s article on multi-accounting and browser profile management.

Technical infrastructure should be organized in advance, not after the first problems appear.

Creatives and AI: From Finding an Idea to Rapid Testing

AI tools are increasingly used at different stages of preparing and optimizing advertising campaigns. They help not only generate copy, but also develop advertising concepts, prepare scripts, create visual materials, and analyze results.

AI helps shorten the time between developing a hypothesis and testing it.

For example, a team is planning to launch an offer in a new GEO. Instead of starting from scratch, a buyer can use neural networks for several tasks.

Idea generation. AI helps develop advertising concept options, identify possible audience needs, and suggest different ways to present a product.

Copy preparation. It can quickly produce several versions of headlines, descriptions, CTAs, and adaptations for different audience segments.

Script development. Neural networks can help prepare the structure of a short video: the opening seconds, the main idea, product demonstration, and call to action.

Visual production. Generative tools can create images, concepts, and individual creative elements. Video production tools are also available to help create and edit clips.

Localization. AI speeds up the adaptation of copy and scripts for different languages and markets. However, the finished materials still need to be checked for natural phrasing and cultural relevance.

How AI Is Changing Creative Work in 2026

AI is gradually becoming part of advertising platforms themselves, not just external tools.

For example, Google Ads can automatically combine advertising assets in Performance Max campaigns, while available AI features help create text and visual elements for ads. As a result, a buyer’s work includes not only preparing the original creatives, but also checking which variations the system generates and uses.

In practice, AI is especially useful for speeding up test preparation.

Suppose a team is launching ads for one product in two GEOs. Instead of preparing every variation from scratch, it can use AI to develop several concepts, adapt scripts for local audiences, and send the finished materials to a specialist for review.

The team then launches tests and analyzes not only CTR, but also the cost of the target action, conversion quality, and overall economics.

Another area is using AI to analyze advertising materials. For example, test results can be grouped by concept to identify recurring patterns: which messages are more likely to generate clicks and which visual approaches show a better CTR.

But there is an important point: a neural network cannot know in advance which creative will generate profit.

Even a well-generated visual may fail to interest the audience. Attractive copy does not guarantee conversions, and a persuasive script does not necessarily deliver an acceptable customer acquisition cost.

That is why the workflow looks like this:

1. The buyer develops a hypothesis.
2. AI helps prepare several ways to implement it.
3. A specialist checks the accuracy of the materials and their compliance with the advertising platform’s rules.
4. The team launches tests.
5. The tracker and analytics show the actual results.
6. The team uses the data to decide whether to scale or abandon the hypothesis.

AI speeds up production and preparation, but it does not replace advertising tests, audience understanding, or the specialist’s responsibility for the result.

Tracking and Analytics: Why You Shouldn’t Make Decisions by Guesswork

An advertising account shows only part of the picture. To understand the actual effectiveness of traffic buying, you need to compare costs with results at subsequent stages of the funnel.

Trackers, affiliate network statistics, analytics platforms, and internal spreadsheets or dashboards are used for this purpose.

What data is important to collect?

• Impressions — the number of ad impressions.
• Clicks — the number of clicks.
• CTR — the ratio of clicks to impressions.
• CPC — cost per click.
• CPM — cost per thousand impressions.
• Conversions — the number of target actions.
• CR — the conversion rate from one funnel stage to another.
• CPA — cost per target action.
• Revenue — the revenue generated.
• ROI — the ratio of profit to costs, based on the calculation method used.

Let’s look at a simple example.

A team launches two advertising campaigns with the same budget. The first has a high CTR and generates a large number of clicks, but produces almost no target actions. The second receives fewer visits but delivers higher-quality traffic and better economics.

If campaigns are evaluated by clicks alone, the first may appear more successful. But after analyzing conversions and costs, the priority may change.

For a team lead, analytics also matters at the team level. They need to see not only the results of individual campaigns, but also the overall picture:

• How much each buyer has spent.
• Which accounts generate the majority of traffic.
• Which combinations are being tested.
• Where acquisition costs are increasing.
• Which campaigns can be scaled.
• What budget is needed to maintain the current volume.

Data quality also deserves special attention. If costs from the advertising account, conversions from the affiliate network, and information from the tracker do not match, the discrepancies should be investigated before making decisions.

It is also important to account for operating expenses that may not appear in advertising statistics. Subscriptions to proxies, anti-detect browsers, trackers, AI services, and payment fees can affect the team’s overall profitability.

Good analytics does more than record past results. It helps determine where to allocate the next advertising dollar.

Automating Routine Tasks: What You Can Delegate to Systems

As a team grows, less time is available for repetitive manual tasks. That is why automation in 2026 is no longer an extra advantage; it is a way to keep processes manageable.

Start by automating operations that follow clear rules and recur regularly.

For example:

• Collecting statistics from advertising sources.
• Generating reports on campaigns and buyers.
• Sending alerts when specified metrics are reached.
• Monitoring spending and remaining budgets.
• Preparing creatives using approved templates.
• Creating new work records and assigning tasks.
• Issuing and topping up cards through an API, when configured accordingly.

AI agents are also gradually expanding automation capabilities. They can help analyze information, generate reports, work with data, and perform sequences of tasks in connected systems.

For example, a team can set up automatic collection of campaign statistics and a daily report for the team lead. If the cost per conversion exceeds a specified value or the budget approaches its limit, the system sends a notification to the responsible specialist.

This approach makes it possible to spot deviations faster without manually checking every advertising account. At the same time, reporting delays and metric calculation rules must be taken into account so that alerts do not lead to premature decisions.

But not everything should be automated.

It is better to leave the following to people:

• Choosing the advertising strategy.
• Evaluating offer quality.
• Making scaling decisions.
• Reviewing unusual situations.
• Monitoring compliance with advertising platform rules.
• Giving final approval for large expenses.

The optimal model is to automate repeatable actions while keeping human oversight of decisions that affect money and strategy.

Teamwork: From an Individual Buyer to a Shared System

When one person handles traffic buying, many processes can be kept in their head. As the team grows, that approach stops working.

Several buyers may have different advertising accounts, GEOs, offers, budgets, and work tools. If everyone keeps records in their own system, it becomes difficult for the team lead to evaluate overall performance.

That is why the team needs a clear organizational structure.

Role allocation. The buyer is responsible for launching and optimizing campaigns, while the team lead handles strategy, resource allocation, and performance monitoring. Designers, creative producers, analysts, and technical specialists may also be involved.

Project separation. Each area should have designated team members, the accounts being used, and allocated budgets.

Access management. Not every employee should be able to change settings across all advertising accounts, manage payments, or view the team’s entire financial information.

Expense tracking. The team needs to know how much money has been allocated for testing, how much has been spent, and what balance is available for further work.

Regular reporting. Team members should follow the same accounting principles so that results can be compared.

It is especially important to separate advertising spend from other operating expenses. In addition to buying traffic, the team pays for proxies, anti-detect browsers, trackers, analytics tools, subscriptions, and other services.

If only advertising account expenses are counted, the team’s actual operating costs will appear lower than they really are.

At this stage, financial infrastructure becomes part of operational management.

Payment Infrastructure: How to Manage Budgets Without Manual Chaos

At a small scale, payment issues are often simple: a buyer receives a card, tops it up, and launches ads.

But as the team scales, this model creates additional operational risks.

Imagine a situation in which five buyers are working with several advertising accounts at the same time. Each has their own cards, different budgets, and regular top-up needs.

If all operations are performed manually, the team lead has to keep checking balances, approving top-ups, tracking expenses, and controlling how funds are distributed among projects.

As a result, some working time goes toward managing payments rather than buying and optimizing traffic.

To prevent a larger advertising budget from causing a constant increase in manual work, the financial infrastructure should support fast card issuance, expense separation, budget control, and convenient access management.

Pay2.House: Managing Cards and Budgets in One System

Pay2.House allows users to issue virtual Visa and Mastercard cards for Meta Ads, Google Ads, TikTok Ads, and other online services. The team can use available BINs and manage cards through a single interface.

This is convenient when several advertising directions are running at the same time and payment tools need to be separated by project.

Several tools are available for team workflows.

My Teams. This feature allows users to create teams, invite members, allocate funds, manage access, and monitor financial operations. The team lead gets a clearer view of expenses, while buyers can work with the resources assigned to them.

Auto Top-Up. This feature lets users set up automatic card top-ups when the balance reaches a specified threshold. It helps reduce manual operations and the risk of running out of funds on a card. The team’s overall balance and spending still need to be monitored.

Card Transfer. This feature lets users transfer an already-issued virtual card to another registered Pay2.House user. For example, if responsibility for an advertising direction passes from one buyer to another, the card can be transferred to the new person in charge without issuing an additional one.

The recipient must confirm the transfer, and each card can be transferred only once. To transfer a Personal Card, both users must complete verification.

Bulk card issuance. This helps reduce manual work when a team needs to prepare several payment tools at once. Feature availability depends on the terms of the selected plan.

API. It allows users to automate card issuance and top-ups, retrieve information about balances and transactions, and integrate payment processes with the team’s internal systems. When configuring it, it is important to provide for access permissions, limits, and error handling.

For example, when launching a new advertising direction, a team lead can organize the team’s budget through My Teams, prepare the required cards, set up automatic top-ups, and track expenses within a single workflow.

At the same time, automation does not replace financial oversight. Advertising expenses should be regularly reconciled with payment transactions, while fees, limits, and remaining balances should also be taken into account.

Thus, payment infrastructure becomes not just a way to pay for ads, but part of the team’s overall management system.

How to Build a Stack That Can Handle Scaling

There is no universal set of services that will work for every team. A small project may get by with minimal infrastructure, while a large media buying department will need team tools, automation, centralized analytics, and financial management.

Regardless of team size, however, one principle is important: every increase in workload should be accompanied by the corresponding development of infrastructure.

If a team adds advertising accounts, it needs to review how profiles and proxies are managed. If the number of creatives grows, their production and testing need to be organized. If the number of buyers increases, the team will need a unified system for reporting, task allocation, and budgets.

Example of a Media Buyer’s Working Stack in 2026

This table does not mean that every media buyer necessarily needs all the tools listed. The specific stack depends on traffic sources, the number of advertising accounts, team structure, and project requirements.

The main thing is for the tools to complement one another rather than create extra processes for their own sake.

A working combination of tools creates the opportunity for profit, but it does not guarantee that a team can handle scaling. All key elements must work: accounts, creatives, tracking, proxies, payment tools, and internal processes.

If a team buys $500 worth of traffic per day today and plans to reach $5,000 tomorrow, the capacity of the entire system must grow along with the budget.

Otherwise, an increase in advertising spend will lead not only to higher potential profit, but also to more errors, delays, uncontrolled expenses, and operational workload.

In 2026, a strong media buyer is no longer just a specialist who knows how to find successful combinations. They are part of a system in which every tool, process, and budget must contribute to the overall result.

At a small scale, the question is, “Where can I get a card?” At a larger scale, it becomes, “How can we make 50 cards, 20 accounts, and 5 buyers work as one system?”

That is the question where real scaling begins.

Pay2.House — virtual cards and budget management tools for teams.