I’m the creative and user experience director for a marketing agency that works with hundreds of CPG and ecommerce brands. I love using AI in my day-to-day job.
Before you start wondering about the likelihood of a creative guy embracing AI, know this: It’s not for producing the actual work. Rather, I use it as a research tool that frees up time for me and my team to spend on original copy and visuals that elicit engagement.
In this article (which, by the way, was not a product of ChatGPT), I’ll spell out my favorite use cases for AI, add a bit about my favorite AI tools (and the ones I won’t trust yet) and throw in best practices for refining the output.
Use cases for AI in brand and user experience research
I use AI for two main types of research: user research and competitive research.
Let’s start with user research. AI can absolutely help you learn more about your audience. It’s beneficial to start with what you know (e.g., if you’re selling jogging strollers, you know your audience is active parents of young kids). But even if you’re starting from scratch, you can ask: “What’s the best audience for {product}?”
Once you get a demo, you can pepper the tool with questions as though it’s a focus group. The AI will generalize responses, arriving at a likely consensus you might hear from the group.
In the jogging-stroller example, you might ask what the biggest challenge is for a new parent’s exercise routine. The response might be: “finding more time in the day.” You could use that knowledge to craft messaging around how the stroller can seamlessly add exercise to their existing routine. You can also use AI to ask about audiences outside of your target demographic to gauge the prospects of expanding your market.
AI is also particularly good for helping with competitive analysis. Use the tool to drill down into each competitor by asking about their annual revenue, most popular products or services and differentiators.
My favorite (and least favorite) AI tools
To tackle the above initiatives, the first AI tool I started using seriously was ChatGPT. It’s still my first choice for prompt-based research. Recently, I’ve been dabbling with Perplexity for prompt use as well, and I’ve been impressed by the results.
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On the other hand, Gemini’s early results were patchy at best and downright offensive at worst. Google’s rush to get it to market didn’t serve anyone. I’m open to testing anything that comes along, and I make a practice of doing so. But I’ll need to see a ton of improvement in Gemini before I start paying any attention to it again.
Best practices for refining AI-produced research
This article won’t go into depth about how to create prompts; that topic is worthy of its own piece. But here’s one bit of advice: The more detailed and specific you can make the prompt, the better output you’ll get.
Instead of: “Can you give me information about Brand X’s competitors?”
Try: “Can you provide me with the top five competitors in Brand X’s space, their annual revenue and top offering and a unique quality that differentiates them from their competition?”
You’ll still need to cast a critical eye with plenty of quality assurance on the answers no matter the prompt, but you’ll get richer information from smarter queries.
Essentially, I carry the same expectations for AI research as I would for an entry-level research assistant: They’re not experts, so they lack context; they do what you ask and no more. Ultimately, if you do a little work upfront to give them good direction, you’ll save yourself a boatload of time you can put to good use elsewhere.
Great creative is built on empathy and understanding of the audience meant to see it. That’s still as true as ever. Using AI to help build a base of that understanding isn’t creepy; it’s a good use of available tools.
The key is to shift your resources: Let machines help so humans can do what only humans can do – come up with original ideas and continue to break new creative ground.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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