Mara didn’t think she was building a feedback loop. She thought she was building a brand.
As head of growth at a mid-sized fashion company, she pushed her team to „learn from the best.” That meant studying platforms like TikTok and Instagram, not just for marketing ideas, but also for signals. What works? What spreads? What converts?
At first, the date was clear. Short videos with strong emotional hooks (confidence, transformation, aspiration) performed best. Posts with conventionally attractive models drove more clicks. Content that leaned into urgency („last chance,” „don’t miss out”) converted faster.
So the team adjusted.
They hired creators who fit a narrower look. They edited videos to be faster, sharper, more intense. They cut anything subtle. Sales went up. Engagement skyrocketed. The dashboard glowed green.
Mara reported success.
Three months later, customer support tickets started changing:
“I like your clothes, but they make me feel… not enough.”
“Do you have any models who look like me?”
“This content feels kind of aggressive.”
At the same time, something else was happening, harder to notice, but more important.
The algorithm had learned.
Because Mara’s team fed it high-performing, high-intensity content, platforms like YouTube and TikTok began showing their ads to users who responded best to that tone: people more sensitive to comparison, urgency, and social validation.
Those users clicked more. They bought more. They stayed longer.
And the system optimized further.
Meanwhile, a different company, let’s call them „Northwell,” ran a quieter experiment.
They noticed something similar in their analytics, but chose a different path. Inspired partly by public conversations about algorithmic accountability, they asked a different question: „What kind of behavior are we training?”
So they changed their inputs. They featured a wider range of body types, slowed down the pace of their content, removed the manipulative urgency cues, and decided to highlight more customer stories over polished perfection.
At first, performance dipped. Fewer clicks. Lower watch time.
The algorithm resisted.
However, over time, something shifted.
Slowly but surely their audience changed. Engagement became less explosive, but more stable. Comments became more thoughtful. Return customers increased. Support tickets dropped.
And most importantly? The algorithm finally adapted. It began to find users who responded to authenticity rather than intensity. It began to reward trust, not just reaction.
Now, back at Mara’s company, the opposite loop had tightened.
Creators they partnered with started exaggerating even more…. because that’s what performed, right? Customers expected higher emotional stimulation. Calm content felt „boring.” The brand had unwittingly trained both its audience and its algorithm to demand escalation.
When Mara finally paused to review a year’s worth of data, she noticed it: they hadn’t just followed the algorithm, they had shaped it, and it had in turn shaped their customers.
That’s the part many businesses miss.
AI systems on platforms (like Instagram, TikTok, etc.) don’t just reflect behavior. They learn from what you reward.
Every click you optimize for, every emotion you amplify, every pattern you repeat… becomes training data. And that training data doesn’t stay abstract. It comes back in the form of customer expectations, brand perception, market norms.
A year later, Mara changed her strategy. Not only because performance dropped, but because she realized something more uncomfortable: the system was working exactly as designed. It just wasn’t designing the kind of relationship with customers she actually wanted.
So she asked her team a new question: „If the algorithm learns from us… what do we want it to learn?”
That’s the real risk and responsibility for any business using AI-powered platforms these days. You don’t just react to the system. You teach it how to behave.
***
We like to imagine the algorithm is in charge….And yet it isn’t. It’s nothing more and nothing less than a mirror and a megaphone. It shows us what’s working and then it makes more of it. Not because it cares, but because that’s its job.
So we track the numbers. We see what gets clicks, what spreads, what converts. And then we do more things like that.
Of course we do. Because the dashboard is clear, the pressure is real, and the story we tell ourselves is simple: this is what the market wants.
But markets don’t simply want….They learn.
Every signal you send, every spike you celebrate, every shortcut you repeat, teaches the system what to find. And it listens. Quietly. Relentlessly.
Soon, it’s not just showing your work to more people. It’s finding more people who respond the way you’ve taught it to expect.
People who click faster. People who compare more. People who feel the urgency you keep insisting is normal. And then something subtle happens. You look at your customers and think: this is who they are… But it’s not about who they were. It’s who the system found, because of what you taught it.
This is the part that’s easy to miss: you’re not just optimizing content, you’re selecting an audience. And once you select an audience, you start serving it. And once you serve it, you reinforce it. And once you reinforce it, it becomes the only thing that feels like it works.
A loop…a very efficient one.
The good news? There’s another way, of course. There’s always another way.
You can choose to be less loud. Less urgent. Less insistent.
You can choose signals that don’t spike the chart at full speed, but settle into something steadier. Signals that say: you’re already enough. Signals that take longer to work because they’re not designed to interrupt, they’re designed to resonate.
At first, it feels like it’s not working. Because the system you’ve trained resists you. It keeps looking for the old patterns. The fast ones. The loud ones.
And you have to teach it again… Slowly… Patiently.
You send a different signal. Then another. And another. Not because it wins today, but because it compounds tomorrow. And over time, the system adjusts.
It finds different people: People who aren’t in a hurry. People who don’t need to be pushed. People who come back.
„People like us do things like this.” That’s how culture is built. Not with a campaign, but with consistency and definitely not with a spike, but with a pattern.
The algorithm will learn whatever you teach it.
The question is not whether it works. The question is: what does it learn from you?
Because whatever it learns, it will give back. AMPLIFIED.
***
So, we’ve been taught to believe that markets reveal themselves through data. But data does more than reveal. It reinforces.
In algorithmic environments, businesses don’t just respond to demand, they participate in creating it. Every optimized click, every amplified emotion, every repeated pattern becomes part of a feedback loop that shapes not only performance, but people. Customers adapt. Platforms learn. Markets shift.
What appears to be neutral optimization is, in practice, large-scale behavioral conditioning.
Two paths emerge: One draws attention through intensity, speed, and pressure (effective, immediate, and fragile). The other builds trust through consistency, resonance, and patience (slower, quieter, and persistent).
And the difference is not technical. It is a choice about what to amplify and what kind of system a company is willing to train.
Let’s take a more detailed approach for a better understanding:
From measurement to influence. We start with a simple idea: measure what works. And so we do it. We turn to platforms like TikTok, Instagram, YouTube, etc. We track the numbers. We refine the message. We adjust in real time.
It feels empirical, objective, and safe. Yet there’s something else going on beneath the surface. The system is not just reporting outcomes, it’s learning from them. And so are we. Every iteration becomes a signal. Every signal becomes a lesson. And every lesson is reflected in the system that distributes, filters, and amplifies what comes next.
We think we measure behavior. In fact, we shape it. As Marshall McLuhan observed, „We become what we behold. We shape our tools and then our tools shape us.” In algorithmic markets, this is no longer a philosophical idea, rather it has become an operational reality.
The loop that learns. The mechanism is deceptively simple: something is published, someone reacts, the system rewards the reaction, the pattern repeats itself… a loop.
Efficient, scalable, self-reinforcing. And yet the loop doesn’t stop at content. It reaches all the way to the very composition of the audience itself.
When a business consistently amplifies urgency, comparison, or emotional intensity, the system begins to identify the people most receptive to those signals. It finds them, prioritizes them, and finally returns them, and so on…
Gradually, the audience changes. Not all at once. Not dramatically. But enough.
Enough to shift expectations. Enough to redefine what feels „normal.” Enough to make anything outside the pattern seem ineffective.
You think it’s targeting, but in fact it’s selection and, over time, it becomes destiny.
Markets that learn how to feel. We often talk about demand as if it were fixed, waiting to be discovered. But demand is not static. It is trained. Repeated signals do more than capture attention; they shape perception. They teach customers what matters, what is desirable, what is missing.
Scarcity teaches urgency. Perfection teaches comparison. Intensity teaches impatience. And over time these lessons compound.
As Herbert A. Simon warned, “In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
Therefore, an abundance of information creates a scarcity of attention. In response, we compete more intensely for that attention (louder messages, sharper hooks, faster delivery.
And in doing so, we do not simply win attention, we redefine it. We raise the threshold. We narrow the range. We train the market to respond to less, unless it’s more.
Two paths, one choice. At some point, every business makes a choice, whether deliberately or by default.
One path is built on extraction. It’s fast, it’s measurable, and it works. Content is designed to provoke reactions. Urgency compresses time. Aspiration amplifies desire. The numbers grow, and the system responds with more reach, more visibility, more of the same.
Yet there is a cost. Audiences adapt. Signals weaken. What once worked must be intensified. And so the system demands more (more energy, more exaggeration, more pressure) just to maintain the same result. Growth becomes dependent on escalation.
The other path is built on accumulation. It doesn’t start with performance, it starts with intention: „Who is this for?”, „ What do we want them to feel?”, „ What kind of relationship are we building?” The signals are different. Less urgent. More grounded. Less reactive. More consistent.
At first, it seems like a failure. The system holds up. The indicators soften. The feedback slows. But if it’s sustained, something changes. A different audience emerges. One less driven by impulse, more by alignment. One less volatile, more enduring. Trust begins to compound. And what grows is not just attention, but affinity.
What the system teaches us inside the business. These loops don’t just shape markets. They shape organizations. Metrics become language. Language becomes culture. Culture becomes behavior.
If success is defined by clicks, teams will produce clicks.
If success is defined by speed, depth will be sacrificed.
If success is defined by reaction, challenge becomes a skill.
Over time, this narrows the field of possibilities. Creativity gives way to replication. Judgment gives way to optimization. Ethics gives way to efficiency. ….and so on. And everything until you change the signals, then the system within the company changes as well.
Measures trust and teams learn patience.
Reward consistency and they build coherence.
Value long-term relationships and they begin to think in time, not in spikes.
After all, as Peter Drucker reminded us, „what gets measured gets managed,” and what gets managed becomes who we are.
The weight of what we amplify. There is no neutral ground in learning systems. Every signal has a consequence.
To amplify anxiety is to normalize it.
To amplify comparison is to deepen it.
To amplify trust is to strengthen it.
The platform doesn’t choose, only your business can. Although the effects may be delayed, they are not diminished. Customers feel what is repeated. They take things beyond the moment of interaction (into perception, into loyalty, into reputation). And so, what is optimized today becomes expectation tomorrow.
The illusion of early success. One of the most persistent challenges is time. The extractive path seems right (immediate, compelling, measurable). The relational path seems wrong… Until it doesn’t.
Short-term metrics are loud. Long-term outcomes are quiet. By the time the quiet ones speak out (through churn, fatigue, or eroded trust), the system has already been trained. The audience has already been shaped and reversing course requires more than a new campaign. It requires unlearning.
From participation to stewardship. It is tempting to see your business as a participant in a system that it does not control. But this is only partially true. Businesses are not just users of the system, they are its teachers.
With every choice, they instruct ut: Who to find. What to reward. What to ignore. This is a form of authorship and with it comes responsibility. Not only to performance, but also to consequences, and not only to efficiency, but also to impact.
And in this way the question shifts. From „What works?” to „What are we teaching?” to „What will this become if we keep going?”
These are harder questions, but they are the only ones that lead somewhere worth going.
Finally, the system listens. The system works as it always has… It reflects what it is given. It scales what it learns. It returns what it is taught, multiplied.
So the real question is not whether to optimize or not, but what to optimize for. Because your business doesn’t simply grow through these systems, it shapes them. And by shaping them, it shapes its customers, its culture, and its future.
As the system learns, so must your business. Less fast, more wise.
***
Most businesses chase the next spike. Few shape what lasts.
Think like a DJ: The goal isn’t to drop hits, it’s to own the room.The set you choose defines the audience you attract, the taste you build, and the memory you leave behind.
What you optimize for becomes your business. Short-term intensity creates buzz. Long-term discipline builds trust.
This is an invitation to collaborate differently, to design systems that don’t just capture attention, but cultivate it, to build brands people return to, not just react to.
If this is the direction you’re aiming for, let’s talk. Until then, keep it handy!
