Richard Golian

1995-born. Charles University alum. Head of Performance at Mixit. 10+ years in marketing and data.

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Richard Golian

Hi, I am Richard. On this blog, I share thoughts, personal stories — and what I am working on. I hope this article brings you some value.

What Is Performance Marketing – and How Is AI Changing It?

Performance marketing, AI and ROI

By Richard Golian

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I have been working in performance marketing since 2017, and over the years, I have realised that its essence lies in having a clearly defined goal and choosing the best way to achieve it. The key is to see the available ways to achieve it. And behind every possibility, we must evaluate two fundamental aspects – its difficulty and its positive impact on reaching the goal.

It’s like picking fruit. We go for the low-hanging ones first. If we have multiple options with the same impact, we start with the one that takes seconds (for example, increasing the budget on a high-potential campaign), then move to those that take minutes, and only after that do we tackle the tasks that require hours or days (such as shooting and editing brand-new professional videos for ads). It’s about having a goal-driven mindset, common sense, and smart resource management.

Learning from Mistakes and Continuous Growth

Even though I constantly remind my colleagues of this principle, include it in company marketing guidelines, and look for it in job candidates, I am not perfect either. Everyone occasionally makes a suboptimal decision. In the past, I have underestimated the importance of small tweaks that could have brought quick results or overlooked details that, if fixed, could have had a significant impact. That’s a mistake. As I’ve written before, I consider every suboptimal decision a mistake, regardless of whether we ultimately achieved the set goal. If a mistake happened along the way, it’s essential to acknowledge it.

This is the foundation for learning. It’s a crucial skill not just for performance marketers but for anyone striving to move forward. I’ve written more about mistakes in my previous posts.

So, performance marketing isn’t just about ads, data, and analytics. It’s about identifying weak spots and recognising potential — then making the most of it. It’s a continuous process of learning, testing, and optimisation. Those who can effectively prioritise, quickly adapt, and learn from their mistakes will always stay one step ahead.

The Future of Performance Marketing in the Age of Artificial Intelligence

Asking what performance marketing is and what it will become in the era of AI actually means asking two different things. One question is about its core essence. The other is about the tools and processes we use.

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Summary

Performance marketing is having a clearly defined goal and choosing the best path to achieve it. Start with quick wins, then moderate-effort tasks, then the hard stuff. Acknowledge suboptimal decisions. The foundation for growth is honesty about what isn't working.
Richard Golian

If you have any thoughts, questions, or feedback, feel free to drop me a message at mail@richardgolian.com.

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Common questions on this article's topic

What is performance marketing?
Performance marketing is a results-driven approach to online marketing where advertisers pay only when a specific measurable action occurs — such as a click, lead, or sale. It is defined by standard metrics like CPA (Cost Per Acquisition), ROAS (Return on Ad Spend), and conversion rate, and operates across channels including paid search, paid social, affiliate marketing, and programmatic advertising. Unlike traditional advertising, where costs are paid upfront regardless of results, performance marketing ties every euro spent to a measurable outcome. In the article, this formal framework is distilled into a practical principle: have a clearly defined goal and choose the best path to achieve it — starting with quick wins, then moderate-effort tasks, then the hard stuff.
How is AI changing performance marketing?
AI is already automating campaign optimisation, performance analysis, reporting, and flagging inconsistencies in data. In the article, the expectation is that large performance marketing teams will no longer be needed — the future belongs to smaller, more focused units of people who combine skills across marketing, analytics, and technology. What changes are the tools and who executes the work. The essence — having a goal and finding the best path — remains the same.
What skills will performance marketers need in the age of AI?
In the article, the most valuable skills are those AI cannot yet replicate: strategic planning, prioritisation, creativity, brand feel, and evaluating results in context. The ability to recognise when AI makes a mistake, misses an opportunity, or takes a suboptimal route is what separates marketers who will thrive from those who will not keep up. Vision, strategy, and resource allocation will remain human responsibilities.
Why is acknowledging mistakes important in performance marketing?
In the article, every suboptimal decision is treated as a mistake — regardless of whether the overall goal was achieved. If something could have been done better along the way, it matters. This honesty about what is not working is described as the foundation for learning and continuous improvement, which is essential in a field where conditions change constantly.
What is the low-hanging fruit approach in marketing optimisation?
It means prioritising actions by their difficulty relative to their impact. In the article, the framework is: if multiple options have the same impact, start with the one that takes seconds (such as increasing budget on a high-potential campaign), then minutes, then hours. This prevents wasting time on complex projects when simpler actions could deliver results faster.
Will AI replace performance marketers entirely?
Not in the near term. In the article, AI is expected to handle most execution — optimisation, analysis, testing — but humans will still be needed for strategic oversight, creative judgement, and final quality control. The growing gap will be between marketers who embrace AI as a tool and those who do not. In the long run, what remains is responsibility: connecting all parts of the system and interpreting them in context.