Performance marketing is very often an art of knowing what you don’t know.
Especially when planning a campaign for a new product, service or brand, all you can really do is make informed assumptions. We look at the category, the audience, the budget, the competitive landscape, past benchmarks and we form a point of view. But let’s be honest: what we’re presenting is not an answer. It’s a hypothesis.
Clients often seek an agency for expertise and expect the digital strategist to give them certainty.
“This channel and this audience targeting combination is optimal.”
It sounds reassuring. It looks good on a slide. It gives everyone something solid to hold on to.
The truth is that this is simply a starting assumption waiting to be tested.
Anybody can make a plan and try to convince you that it’s the best one. A narrative always looks clean on paper (or in a deck):
“We’re going to find this very specific group of people who are going to love your product, and they’re currently on this platform consuming this type of content.”
Reality is messier. The number of possible combinations in a digital campaign, audiences, creative, formats, placements, bidding strategies, frequency, timing, is so vast that thinking you’ll stumble upon the best setup on the first try is almost absurd. Even small changes can swing performance dramatically. Markets move. Platforms evolve. People behave inconsistently. Signals get noisy.
The real work of performance marketing starts when someone says:
“We’re going to try a few things, learn what actually performs, and then push harder on what’s yielding the highest return.”
Sometimes it feels counterintuitive, even uncomfortable, to tell a client that we’re not really sure yet. Certainty sells better than curiosity. Confidence reads better than nuance. But uncertainty is not a weakness. It’s the natural operating environment of anything that deals with human behaviour at scale.
In practice, performance marketing behaves much closer to the scientific method than to prediction. We observe. We form hypotheses. We run experiments. We measure. We learn. We adjust. A media plan isn’t a conclusion. It’s an experiment design.
Good strategy, then, isn’t about being right upfront. It’s about asking the right questions, choosing what to test first, structuring experiments properly, separating signal from noise, and reallocating budget intelligently as evidence accumulates. The advantage doesn’t come from bold claims. It comes from faster learning.
This way of thinking isn’t unique to marketing. Look at predictive analytics, machine learning and AI. Neural networks start with almost no understanding of the world. They’re trained on massive volumes of data, make countless mistakes, receive feedback, and slowly learn to approximate useful patterns. They don’t “know” in the human sense. They continuously update their confidence based on new information.
The smartest systems are not the ones that assume certainty. They’re the ones designed to learn relentlessly.
Performance marketing works the same way. Every campaign begins with a prior belief. Data challenges or reinforces it. Budgets move accordingly. Over time, clarity emerges, not because someone predicted the future correctly, but because the system was built to adapt.
Maybe the real value an agency should offer is not the illusion of having all the answers, but a faster, more disciplined path to discovering them.
The art of performance marketing is not knowing, and building the conditions to learn better than everyone else.