Brand Makers
Dil Ka Jod Hai, Tootega Nahin
AI-generated audiences are poised to unlock a new era of media planning and buying: Report
As the boundaries between research, creative, and media continue to blur, AI-generated audiences help brands strike the right balance between reach and relevance — starting broad and refining intelligently based on performance feedback.
In the algorithmic era, legacy approaches to audience targeting and consumer insight generation are fast losing relevance. Traditional tools that once helped brands understand and reach customers — such as consumer panels, deterministic ID-based systems, and federated learning models now struggle to deliver the scale, speed, and adaptability required to win in today’s dynamic marketplace, according to dentsu's "Human Truths In The Algorithmic Era" report.
Consumer panels, while rich in insight, are often expensive, time-consuming, and difficult to operationalize across campaigns. Deterministic, ID-based systems that rely on verified customer data like emails perform well for known audiences but falter when it comes to acquiring new ones, given that their data often becomes outdated and lacks scalability. Meanwhile, federated learning systems that analyze behavioral patterns are agile but lack the grounding of verified truth sets and remain dependent on deterministic signals like cookies — making cross-platform activation increasingly challenging.
Against this backdrop, AI-generated audiences are emerging as a transformative force in marketing and media planning. These AI-driven audience profiles simulate real-world attitudes, sentiments, and behaviors, offering an unprecedented ability to understand, test, and engage with consumers at scale.
From insight to orchestration
Modern campaigns demand a deeper orchestration of three key layers of intelligence:
Culture signals that uncover emotional and timely opportunities for connection.
Commerce signals that reveal purchase intent, propensity, and emerging patterns.
Context signals that help decode motivations and habits.
AI-generated audiences bring these signals together, allowing brands to design more relevant, emotionally attuned, and contextually aware campaigns — moving beyond broad demographic targeting to dynamic, behavior-based audience design.
Smarter, sharper, and swifter marketing
AI-generated audiences are reshaping how marketing teams operate across three key dimensions:
Smarter: By offering simulated feedback loops, AI audiences can quickly test creative ideas, messages, and product features. This enables marketing teams to validate campaigns before launch, ensuring relevance and resonance. They also make it possible to replicate insights from hard-to-reach or niche audiences, helping research teams scale faster and more cost-effectively.
Sharper: Teams can now interact directly with these personas through conversational AI, creating virtual focus groups in real time. This not only reduces research costs but also prevents downstream waste by identifying suboptimal creative early in the process. Because AI-generated audiences can operate with limited or no data — and scale effectively with high-quality first-party data — they are especially valuable for industries like Consumer Packaged Goods (CPG), where first-party data access is often restricted.
Swifter: By making insights more accessible and automating feedback cycles, AI-generated audiences free up time for strategic and creative thinking. They shorten the path from ideation to activation, enabling continuous optimization in media planning and buying.
A new paradigm for media planning
As the boundaries between research, creative, and media continue to blur, AI-generated audiences help brands strike the right balance between reach and relevance — starting broad and refining intelligently based on performance feedback.
By embedding AI-generated audience modeling into their planning cycles, marketers can move from static audience segments to living, learning systems that evolve in real time. This evolution marks the beginning of a new era — one where media decisions are not just data-driven, but intelligence-driven, powered by continuous learning and human-AI collaboration.
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