I had a client last year—a massive WooCommerce store—who was convinced they needed a complete UX overhaul because “Sarah the Millennial” wasn’t buying enough. They sent over a 50-page PDF full of stock photos, fake hobbies, and “Sarah’s” favorite brand of soy milk. It was absolute fluff. For a developer, that document is useless. It tells me nothing about why people are hitting “back” on the checkout page or why they can’t find the shipping calculator.
I’ll be honest, my first move was a total amateur mistake. I figured if the client wanted a redesign, I’d just clean up the UI, add some trendy CSS animations, and swap out the hero images to match “Sarah’s” vibe. Total waste of time. The conversion rate didn’t budge. The real problem wasn’t the aesthetics; it was the friction in the functional tasks. I realized we were designing for a poster, not a person with a goal. That’s when I pivoted to functional personas with AI.
Why Traditional Personas Are Breaking Your Design
Traditional personas focus on who someone is on paper. Functional personas focus on what they are trying to do. If I’m building a complex checkout flow, I don’t care if the user is 24 or 54. I care if they have five items in their cart, if they’re worried about return policies, and if they have a discount code that isn’t applying correctly. You need to map the tasks, not the demographics.
Using AI to build these isn’t just about speed—it’s about processing the “messy” data you already have but never look at. Think chat logs, support tickets, and raw review data. Instead of guessing, we use the machine to find the patterns. This builds on a lean concept I saw in a recent Smashing Magazine piece about functional personas with AI.
A Practical Workflow for Busy Devs
Start by setting up a “Project” in ChatGPT or a “Space” in Claude. Don’t just dump one file in. Give it the context it needs to stop hallucinating. I usually run a quick SQL export of customer notes or feedback entries to give the AI real, raw human friction to chew on. Trust me, it’s better than any survey.
<?php
/**
* Simple export for AI persona feeding.
* Prefix everything to avoid collisions.
*/
function bbioon_export_feedback_for_ai() {
global $wpdb;
// Grabbing recent customer notes from WooCommerce
$results = $wpdb->get_results( "SELECT comment_content FROM {$wpdb->prefix}comments WHERE comment_type = 'order_note' LIMIT 100" );
$output = [];
foreach ( $results as $row ) {
$output[] = strip_tags( $row->comment_content );
}
return json_encode( $output );
}
Once you have your data, brief the AI. Tell it: “Act as a UX researcher. Segment these users by their primary tasks and the specific questions that stop them from acting. Ignore age and income.” You’ll get segments like “The Comparison Shopper” or “The Quick Restocker.” These are things you can actually code for. Period.
The Reality Check: Validation
Don’t just take what the AI spits out and run with it. That’s a recipe for a nightmare. Take those draft personas to your support team—the people in the trenches. Ask them, “Does this sound like the person who calls us every Tuesday?” If they say yes, you’ve got a winner. If they look at you like you have three heads, the AI hallucinated. Refine the prompt and try again.
Look, this stuff gets complicated fast. If you’re tired of debugging someone else’s mess and just want your site to work for your actual customers, drop my team a line. We’ve probably seen it before.
So, What’s the Real Lesson?
- Stop obsessing over soy milk and start obsessing over task completion.
- Use AI to synthesize the messy feedback you already have in your database.
- Functional personas should change your navigation, your button text, and your API logic.
- Treat these documents as living toolkits, not static PDFs that gather digital dust.
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