Is Your Brand Sending the Right Signal?

Is your brand signal relevant to the algorithm and strong enough to reach the audience you want?

You made a search this morning, perhaps you were looking for a restaurant, a pair of shoes, a news story, a holiday, a recipe. You thought you were looking for information, but actually, you were also leaving a signal.

You clicked on a result, another signal. You watched a video, yet another signal. Even if you skipped the next one, it becomes a signal. You liked something, shared something, saved something, bought something. The system was learning, and then, almost invisibly, it began changing what you would see next. That is the paradox of the digital world we now live in.

We think of algorithms as something outside us, a piece of technology sitting somewhere behind the screen, deciding what appears on our feed, but the fact of the matter is the algorithm does not arrive fully formed. In many ways, we help build it.

Our searches, clicks, our pauses, our choices teach it, and once it has learned enough, it starts making predictions about what might deserve our attention next. So here is an uncomfortable question:

Did you make the algorithm, or did the algorithm make you? The honest answer may be both.

Platforms such as YouTube openly describe this feedback loop. Its recommendation system uses signals including watch history, search history, subscriptions, likes, dislikes and direct feedback to predict what a viewer may want to see next. YouTube’s own guidance to creators makes an equally important point: the algorithm ultimately follows audience behaviour. It is learning from what people choose, ignore and enjoy.

That should matter to every brand, because marketing has traditionally been built around a relatively straightforward assumption: create the message, buy the media and reach the audience. Today, there is an increasingly powerful system sitting between the message and the audience: the algorithm.

A brand can have a great product, a brilliant campaign, a million followers and still struggle to reach the people who supposedly chose to follow it, because following is no longer the same as reach. Somewhere between your brand and your audience sits a system constantly deciding what is likely to be relevant at that moment.

This changes a fundamental marketing question. For decades, brands asked, how do we get people’s attention? The more relevant question may now be, what signals are we sending that make the system believe our brand deserves the opportunity to earn that attention?

That does not mean marketers should start building brands for algorithms; that would be a dangerous misunderstanding. The algorithm is not the customer, the human being is, but the algorithm is increasingly the gatekeeper between the brand and the human being, and this is where behavioural science becomes important.

Robert Zajonc’s work on what became known as the mere-exposure effect helped establish a powerful idea: repeated exposure to a stimulus can increase familiarity and, under certain conditions, preference. That does not mean repetition automatically makes us like everything. It doesn’t, but it does raise an important question for the digital age.

If algorithms increasingly influence what we encounter repeatedly, could they also influence what becomes familiar, salient and worth considering? Think about your own behaviour.

The singer whose songs keep appearing in your recommendations, the restaurant you keep seeing on Instagram, the product that appears repeatedly after you searched for something similar, the creator whose videos somehow keep finding their way into your feed. Perhaps you genuinely like them, but where did you first encounter them? How often did you encounter them before they began to feel familiar?

How much of what we call preference begins with the simple fact that something was given the opportunity to enter our attention in the first place? The algorithm does not have to decide what you think. It does not even have to decide what you like. Its influence can begin much earlier. It can influence what you see, what you discover or what appears again, most importantly, what never gets the opportunity to enter your field of vision at all. That is why the question of mindspace matters. People who own the audience have enormous access to mindspace; increasingly, the algorithm decides what gets access to that audience.

There is only so much attention available. The competition for it is no longer simply between brands. It is between millions of pieces of content, creators, conversations, recommendations and commercial messages, all competing to become the next thing a person chooses to notice. Therefore, the larger question is, where does this leave the brand? With a challenge that is both technological and deeply human.

A brand must understand the signals, but it must not become obsessed with gaining them, because the strongest signal a brand can send is still human relevance. Marketing needs to evolve.

The emerging model looks more like this: create relevance → earn response → generate signals → become discoverable → earn more attention. The distinction is critical: you can buy reach, but you cannot permanently buy relevance. You can try to please an algorithm, but algorithms eventually learn from what people actually do.

Also read: Cutting Through the Clutter

The algorithm follows behaviour → Behaviour follows relevance. This is also where the future becomes particularly interesting.

As artificial intelligence becomes better at recognising patterns, predicting intent and personalising recommendations, brands will increasingly operate in environments designed to anticipate what consumers may want before they explicitly ask for it, because in a digital world overflowing with content, the battle is no longer just about cutting through the clutter; it is about becoming relevant enough to be brought back into the conversation.

The uncomfortable truth is you may own the brand and its content along with the followers, but if someone else controls the gateway to your audience, you do not completely control your reach.

The algorithm is not your customer, but increasingly, it is standing between you and your customer. Therefore, the objective is not to beat it, not to trick it and it is certainly not to build a brand around it. The objective is to understand what it is learning from human behaviour and then build a brand worth choosing.

The algorithm may decide what gets the opportunity to be seen, but only people can decide what deserves to matter. Perhaps that is the signal that matters most.