By Swastika Singha Published on : May 7, 2025
Are marketers finally breaking free from the tyranny of scale?
For decades, scale was the golden idol of marketing. Larger audiences equaled better performance—or so it was thought. From the mass media heyday to the early days of digital, the quest for reach too often trumped a more fundamental question: are we reaching the right person at the right time, for the right reason?
Today, that question has never seemed more pressing. In an atomized attention economy ruled by algorithms, micro-moments, and behavioral subtlety, the age of unadulterated volume is over. In its place is emerging a more considered, more cerebral model: intent-driven targeting.
Classic targeting techniques, based on demographic generalizations, have failed to deliver in anticipating how consumers will behave. Having information that an individual is a 30-year-old male who resides in a metro city doesn't tell us much about what they need at this moment. Intent, however, sends a much clearer signal. It's not who someone is—but what they're attempting to do—that makes them relevant.
In truth, evidence favors this change. A McKinsey study found that fully 90% of consumer-brand interactions happen spontaneously, and not as pre-meditated encounters. Context-aware engagement increases customer satisfaction threefold, Forrester evidence indicates. This is not marginally better performance; it points to a full-scale rethinking of what is effective targeting.
Intent is dynamic. It's derived from the digital trail individuals leave behind—search queries, clickstream, content engagement, time-on-page, or even hesitation at checkout. It refers to the mindset and not a fixed persona.
Intent can occur in various layers:
A navigational intent could be a user entering a brand name.
An informational intent could be an individual reading reviews or comparison blogs.
A transactional intent appears when the user adds products to cart or views return policy.
Importantly, these indicators can appear within minutes or over weeks. Translating this dynamic digital activity means brands must cease segmenting users based on who they are and begin targeting them based on where they are in their journey.
There's an unpleasant reality many marketing departments must now face: broad reach doesn't translate into influence. Campaigns that are impression volume-optimized tend to have low click-through rates, low conversion, and high cost of acquisition.
Suppose a traditional campaign reaches a million individuals with a 0.5% engagement rate and a 0.4% conversion rate. Then compare that with an intent-targeted campaign reaching only 100,000—but generating a 3% engagement and 2.5% conversion rate. The latter not only generates more real value—it does so with much lower media waste.
Here, precision isn't only effective—it's scalable. The difference in results between high-intent and mass-reach segments increases as marketing gets smarter.
The martech stack of today provides the capabilities to tap into this new style of targeting. Machine learning models read between behavior patterns, NLP algorithms understand subtle intent in real time, and Customer Data Platforms stitch together multi-touch journeys across devices.
Take Amazon: its recommendation system doesn’t guess what you’ll like based on age or region. It builds associations from observed behaviors—what others with similar digital actions did next. Google’s Performance Max campaigns similarly optimize spend based on real-time intent, not prebuilt segments.
What this reveals is a broader conceptual shift: from identity graphs to intent graphs. We’re no longer just tagging users—we’re following their curiosity, anticipation, hesitation, and desire.
At a fundamental level, intent-based marketing requires a philosophical shift. Instead of asserting to "know" the user, we start by sensing them. This is very much in line with probabilistic thinking—where marketers refine their hypotheses in real-time based on new signals, similar to how a Bayesian model continually updates its notion of the world.
Rather than a guess that a last-year buyer will repeat, marketers start to notice: are they coming back to replicate what they've seen before? Are they weighing alternatives? Are they indicating they need it now? Assumptions give way to inferences, and precision is born out of humility in this architecture.
Growth of intent-targeting isn't merely a strategic development—it's a privacy-savvy one. With third-party cookies' demise and regulations like GDPR and CCPA on the global scene, brands now have to operate within tighter limits.
Ironically, this limitation has been freeing. First-party intent signals—voluntarily disclosed or directly seen on owned sites—are both more ethical and more precise. Marketers no longer must stalk users throughout the web to be pertinent; they simply must comprehend their behavior in the moment.
This is a rare convergence of user privacy and marketing performance. Relevance now necessitates permission—and wins trust.
To make this change operational, brands need to rethink the very structure of their marketing systems:
Segment not by demographics, but by behavior. Seek out recency, frequency, and substantial interaction.
Disaggregate internal silos. Search, content, and performance teams need to work together to construct cohesive intent stories.
Reframe creative strategy. Message based on whether the user is discovering, considering, or deciding—not on generic "personas."
Invest in infrastructure that enables real-time agility. Intent has a shelf-life. If you’re too slow to act, you’ve already missed the moment.
In an age where attention is finite and personalization is expected, volume is no longer victory. Precision, powered by intent, is what drives meaningful engagement. It tells a brand not just who to speak to—but when, why, and how.
This is not just a tactical shift. It is a foundational rethink of what relevance looks like. Marketing has long tried to reach people where they are. Now, for the first time, it can reach them as they're thinking.
And in that brief, potent moment—intent becomes influence
Are marketers finally breaking free from the tyranny of scale?
For decades, scale was the golden idol of marketing. Larger audiences equaled better performance—or so it was thought. From the mass media heyday to the early days of digital, the quest for reach too often trumped a more fundamental question: are we reaching the right person at the right time, for the right reason?
Today, that question has never seemed more pressing. In an atomized attention economy ruled by algorithms, micro-moments, and behavioral subtlety, the age of unadulterated volume is over. In its place is emerging a more considered, more cerebral model: intent-driven targeting.
Classic targeting techniques, based on demographic generalizations, have failed to deliver in anticipating how consumers will behave. Having information that an individual is a 30-year-old male who resides in a metro city doesn't tell us much about what they need at this moment. Intent, however, sends a much clearer signal. It's not who someone is—but what they're attempting to do—that makes them relevant.
In truth, evidence favors this change. A McKinsey study found that fully 90% of consumer-brand interactions happen spontaneously, and not as pre-meditated encounters. Context-aware engagement increases customer satisfaction threefold, Forrester evidence indicates. This is not marginally better performance; it points to a full-scale rethinking of what is effective targeting.
Intent is dynamic. It's derived from the digital trail individuals leave behind—search queries, clickstream, content engagement, time-on-page, or even hesitation at checkout. It refers to the mindset and not a fixed persona.
Intent can occur in various layers:
A navigational intent could be a user entering a brand name.
An informational intent could be an individual reading reviews or comparison blogs.
A transactional intent appears when the user adds products to cart or views return policy.
Importantly, these indicators can appear within minutes or over weeks. Translating this dynamic digital activity means brands must cease segmenting users based on who they are and begin targeting them based on where they are in their journey.
There's an unpleasant reality many marketing departments must now face: broad reach doesn't translate into influence. Campaigns that are impression volume-optimized tend to have low click-through rates, low conversion, and high cost of acquisition.
Suppose a traditional campaign reaches a million individuals with a 0.5% engagement rate and a 0.4% conversion rate. Then compare that with an intent-targeted campaign reaching only 100,000—but generating a 3% engagement and 2.5% conversion rate. The latter not only generates more real value—it does so with much lower media waste.
Here, precision isn't only effective—it's scalable. The difference in results between high-intent and mass-reach segments increases as marketing gets smarter.
The martech stack of today provides the capabilities to tap into this new style of targeting. Machine learning models read between behavior patterns, NLP algorithms understand subtle intent in real time, and Customer Data Platforms stitch together multi-touch journeys across devices.
Take Amazon: its recommendation system doesn’t guess what you’ll like based on age or region. It builds associations from observed behaviors—what others with similar digital actions did next. Google’s Performance Max campaigns similarly optimize spend based on real-time intent, not prebuilt segments.
What this reveals is a broader conceptual shift: from identity graphs to intent graphs. We’re no longer just tagging users—we’re following their curiosity, anticipation, hesitation, and desire.
At a fundamental level, intent-based marketing requires a philosophical shift. Instead of asserting to "know" the user, we start by sensing them. This is very much in line with probabilistic thinking—where marketers refine their hypotheses in real-time based on new signals, similar to how a Bayesian model continually updates its notion of the world.
Rather than a guess that a last-year buyer will repeat, marketers start to notice: are they coming back to replicate what they've seen before? Are they weighing alternatives? Are they indicating they need it now? Assumptions give way to inferences, and precision is born out of humility in this architecture.
Growth of intent-targeting isn't merely a strategic development—it's a privacy-savvy one. With third-party cookies' demise and regulations like GDPR and CCPA on the global scene, brands now have to operate within tighter limits.
Ironically, this limitation has been freeing. First-party intent signals—voluntarily disclosed or directly seen on owned sites—are both more ethical and more precise. Marketers no longer must stalk users throughout the web to be pertinent; they simply must comprehend their behavior in the moment.
This is a rare convergence of user privacy and marketing performance. Relevance now necessitates permission—and wins trust.
To make this change operational, brands need to rethink the very structure of their marketing systems:
Segment not by demographics, but by behavior. Seek out recency, frequency, and substantial interaction.
Disaggregate internal silos. Search, content, and performance teams need to work together to construct cohesive intent stories.
Reframe creative strategy. Message based on whether the user is discovering, considering, or deciding—not on generic "personas."
Invest in infrastructure that enables real-time agility. Intent has a shelf-life. If you’re too slow to act, you’ve already missed the moment.
In an age where attention is finite and personalization is expected, volume is no longer victory. Precision, powered by intent, is what drives meaningful engagement. It tells a brand not just who to speak to—but when, why, and how.
This is not just a tactical shift. It is a foundational rethink of what relevance looks like. Marketing has long tried to reach people where they are. Now, for the first time, it can reach them as they're thinking.
And in that brief, potent moment—intent becomes influence