For decades, marketers have been trying to answer one fundamental question: what does my audience want? It sounds simple, but it isn't.

The traditional answer has been to create personas. Give the CEO a name, a job title, an age, a set of interests and a list of challenges. Then use that simplified picture to guide campaigns, content and propositions.

There’s nothing inherently wrong with this. Personas have helped us bring audiences to life and create a shared understanding of who brands are trying to reach. But the world in which those personas were created has changed.

People are now using AI to research problems, explore options and work through decisions. They can ask increasingly specific questions, follow up on the answers, challenge assumptions and refine their thinking in real time. Their behaviour is becoming more nuanced and more contextual. So the old, simplified view of the audience is becoming a liability.

Take a busy CMO. Let’s call him Brian. Depending on when and why you encounter him, Brian could be thinking about brand strategy, campaign performance, digital transformation, employer brand, marketing technology, budgets, organisational change…or any number of other priorities.

He doesn't become a different person, but the conversation changes. Each conversation comes with different needs, competitors, triggers, objections and proof points. The Brian looking for help with marketing performance isn't necessarily looking for the same things as the Brian fretting about brand identity. Each of those situations (or Brians, if you will) creates a different opportunity for your brand to be relevant.

Traditional audience segmentation often forces all this complexity into a handful of convenient categories. But people don't exist neatly inside the boxes we create for them. They move between challenges and contexts, belong to different buying groups, and face different pressures depending on what they are trying to achieve at a particular moment.

AI changes the economics of understanding people

We can now interrogate much richer sets of audience information and identify patterns, connections and nuances that would previously have been too time-consuming to uncover. AI has changed the audience insight game at the exact time your audience is changing the way it searches. You can no longer afford to make strategic decisions based on assumptions about what your audience cares about.

When someone encounters a problem, they no longer have to start with a Google search, click through ten websites and gradually piece together an answer. They can ask an AI system to help them understand the problem. They can ask what options exist. They can ask which solution is best for their particular situation. They can describe their organisation, their constraints and their objectives. They can challenge the answer and ask follow-up questions.

The research journey can become much faster, more conversational and more personalised. For marketers, that creates a new challenge.

Do you genuinely understand the conversations your audience is having? Not just their job title or stated challenges, but the questions behind those challenges. The triggers that make them look for a solution. The objections that stop them buying. The alternatives they are considering. Who else is involved in the decision. And what evidence they need before they will believe you.

That doesn’t mean abandoning segmentation altogether, just that it’s time to stop treating a persona as the finished answer. Instead, think about your audience as a source of intelligence; as a dynamic landscape of people, needs, questions and conversations.

Rather than asking: “What does Brian care about?” (yes, him again) we should be asking: “What conversations could we have with Brian, in which contexts, and what would make us relevant to each one?” This question connects audience understanding directly to the work marketers actually need to do: deciding where to focus, what to say, what propositions to develop and what content to create.

The good news is, the technology now exists to make this richer understanding real. Instead of creating a static persona document, marketers can build an interactive representation of their audience: a living body of data and insight that can be interrogated, challenged and updated.

This turns audience understanding from something you look at occasionally into an interactive audience model that becomes a strategic decision-making tool. You can use it to test messaging and propositions, explore potential campaign territories, identify content gaps and determine which conversations to pursue.

This is also where audience insight connects to the wider challenge of AI search.

If the first problem is understanding and organising everything your brand can say (the supply) the second is understanding what your audience actually wants to hear (the demand).

Your organisation might have enormous expertise in a particular area. But if you understand the questions your audience is asking, you can make that expertise more meaningful. You can make your content, campaigns and propositions more relevant. And you can position your brand more effectively in the conversations happening within AI search.

Our offer

At The Frameworks, we're exploring a new approach to audience understanding that takes advantage of what AI makes possible. Brand Proximity, our new service offering, runs on an AI-powered platform and is designed for always-on customer insight and understanding.

Rather than reducing audiences to a fixed set of personas, we create a richer, interactive representation of the people, needs, challenges and conversations that matter to a brand. Each representation can be interrogated to understand the evidence behind an insight, explore the drivers behind a challenge, test ideas and identify where a brand can make a meaningful connection.

Most importantly, these representations are designed to keep moving. Because your audience isn't a static group of people captured in a PowerPoint presentation. It's a living, changing network of needs, questions, pressures and decisions. The brands that understand that complexity – and can turn it into useful strategic action – will be better equipped to compete for attention in an increasingly AI-driven world.

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This article is Part 2 in a 3-part series on getting closer to your customers with AI.