Buyer personas are the backbone of content marketing—because let’s be honest, you can’t craft a message that truly resonates if you don’t know who you’re talking to.
Yet, all too often, these so-called "personas" end up as lifeless, one-dimensional profiles—more like corporate paper dolls than dynamic reflections of real people. And when that happens, they don’t drive strategy, spark insight, or fuel engagement. They just sit there, collecting digital dust in a slide deck.
At least, that’s what we always tell our clients. But when we stepped back and did an audit of our own buyer personas that we use to drive Clariant Creative’s marketing strategy – we realized we weren’t following our own advice.
We know a lot about our agency’s best buyer persona. We call her “Resource-Challenged Rita”, and she’s an experienced marketer who has big growth goals but lacks the internal resources to accomplish those goals on her own. Here’s a look at one section of our legacy documentation on Rita:
And yet, there is also so much more going on in Rita’s life that is important for us, as her marketing agency partner, to understand – that we hadn’t formally documented.
This gap had potentially huge implications:
Our buyer persona documentation was in dire need of a glow-up.
That’s where I came in. I’m an Inbound Marketing Associate at Clariant Creative, and I was tasked with breathing some life into how we defined Resource-Challenged Rita. I also wanted to see if there are any other buyer personas we should be targeting as well. This was a tall order, and I knew I would need to gather a lot of information and sift through a lot of research.
And I also knew that AI is phenomenally well-suited for those sorts of tasks.
In this post, I’ll share the exact process I used to leverage AI to dramatically enhance our buyer personas and make them as actionable, relatable, and effective as possible – truly reflecting the real-life journeys of our target audience.
After members of our team watched Christopher Penn (Co-Founder and Chief Data Scientist at Trust Insights) present on using AI to map customer journeys at HubSpot’s annual INBOUND Conference last fall, I found a recording of that presentation, Building the Data-Driven, AI-Powered Customer Journey Map, online – and I’m so glad I did.
In his presentation, Penn showed how AI could transform an often arduous, time-consuming mapping process into something streamlined and deeply insightful. By pulling in reams of customer data from a wide range of sources – including search behavior, website traffic, and CRM data – and by using generative AI to analyze all that data, Penn’s process leads to amazing outputs in a fraction of the time it would take me to process it on my own.
After watching this video, I now had a framework to guide me in my project. Using the right data and carefully crafted prompts, AI would help me uncover the insights buried deep in the data, turning our original, static persona documentation into vibrant, real-world portraits that reflected the full complexities of the real people we need to reach and engage with our marketing.
Taking my cue from Christopher Penn’s presentation, here is the three-step process I used to leverage AI to dramatically improve the buyer persona documentation we use to drive our marketing strategy.
I first needed to understand the data we had on hand about Rita, so I could identify opportunities to integrate even more data in richer formats.
Knowing basic facts like job titles and high-level business goals wasn’t enough. I needed to know why our best clients behave the way they do. What are their interests, challenges, values, and motivations? How do they make buying decisions? How do they define success in their roles?
With this information, I could turn our persona documentation from characters on a slide deck to real people with complexity and nuance.
I began by filling in gaps in our existing data. Although we lacked some of the quantitative information Penn suggested, we made up for that with rich, first-hand qualitative information. A key component of this was transcripts from client interviews we’ve conducted over the years. These interviews included great questions, such as “Why did you hire us?”, “How do you stay on top of marketing industry developments?”, and “What types of gated content makes you willing to hand over your email address these days?” This provided valuable details about our clients’ decision-making drivers, thought process, and pain points.
I also dove into LinkedIn and found six individuals who represented potentially good-fit clients, who were also active on LinkedIn and had rich activity histories to provide further insights into the mindsets of our buyers. I uploaded their public profiles to my growing AI model.
My set of data now had a good amount of information for AI to create complex, real-world personas.
AI isn’t magic — it needs structure to turn data into gold. To make my process work, I had to prime my AI tool with rules and direction. Think of it like setting the groundwork for a painting; you need a rough sketch before laying down your colors.
In other words, I couldn’t just toss data at AI and hope for the best. Instead, I created specific prompts to push the model to think about the strategy behind building buyer personas. Here are the questions I used to prime my AI model:
Lastly, I shared a Word document with AI that explains how Clariant Creative has typically built out our buyer personas. This gave the AI a framework to format its findings, as well as an opportunity to suggest ways we could improve our legacy process.
I now had my data ready, and I had made sure my AI tool was ready to process it. Now it was time to start cooking.
I dutifully input what we already know about Rita, along with all of the additional information I had gathered in step 1.
But as my AI tool started producing its outputs, I quickly realized that this was not going to be a one-and-done process.
The original AI results were okay, but not exactly the instant perfection I had hoped for. The details still felt hollow – more like marketing noise than actual insights. Several elements completely missed the mark, and overall, it lacked depth.
So, I started refining.
I treated the data input process like sculpting – and I started chipping away at the rough edges of the original outputs by refining my prompts to be more specific about what I wanted, and then critically reviewing each new set of results.
With every iteration, the personas became clearer and more real, shifting from flat characterizations into dynamic profiles full of personality and complexity.
After several rounds of trial and error with my refinements, I finally felt like I landed at a great place. I now had persona documentation that felt balanced, intuitive, and deeply rooted in both data and human experience. These weren’t placeholders anymore — they were vibrant, actionable representations of the people we’re here to serve.
Once again, here’s a section from our original documentation for Resource-Challenged Rita:
Initially, Rita was just a sketch – a senior-level marketer at a mid-sized business, overwhelmed by her workload and constrained by a mid-range budget. But we didn’t really know who she was. She lacked depth, nuance, and the emotional drivers that make a persona truly relatable. She was a placeholder, someone defined more by generic challenges than real motivations.
By inputting my broad mix of information into my AI model and by further refining the AI-generated outputs to incorporate a wider range of insights and context, Rita transformed into someone we could really understand.
This process turned her from a vague outline into a dynamic, multi-dimensional person.
What started as an experiment with improving our personas revealed something much greater: AI’s potential to enhance every area of our marketing strategy – from persona creation to campaign ideation, analytics, customer strategies … the possibilities are endless.
But most importantly, I realized that AI isn’t here to replace marketers; it’s here to work alongside us. AI enhances what we do, taking our ideas, expertise, and strategies to the next level. What once felt overwhelming now feels not only manageable but genuinely exciting.
If you’re intrigued by what AI can do but aren’t sure where to begin, start small. Pick a single area where precision or depth feels lacking—perhaps like your buyer personas—and experiment. Don’t aim for perfection on day one. Approach it as a partnership between you and the tool, and let curiosity lead the way.
You might just transform something stale or ineffective into one of the most impactful tools in your marketing arsenal. And isn’t that what great marketing is all about?
The possibilities are out there—now’s the time to explore them.
Want more tips on creating buyer personas? We spelled out our legacy process in The Marketers Guide to Buyer Personas – this process, combined with the new AI-based steps we’ve outlined here, will give you everything you need to know!
And if you see yourself in Resource-Challenged Rita and would like to know how Clariant Creative can help you overcome your challenges and reach your goals, contact us and let’s talk!