Cracking the Customer Code: Using AI for Deep Consumer Insights
I recently had the pleasure of hosting Kay Allison inside my Women’s Technology Integration Collaborative, and this was one of those sessions that quietly changes how you think about business.
Kay is not another person recycling thin marketing advice and calling it strategy. She is a seasoned consumer insights and innovation expert with more than 30 years of experience helping brands understand what people actually want, not just what they say they want when asked directly. Her work has been connected to major brands like United Airlines and PepsiCo, and what stood out in our session was not just her experience, but the way she explained the difference between how entrepreneurs see their business and how customers actually experience their problems.
That difference matters more than most people realize.
Most of us build from the map. We create clean frameworks, tidy offers, polished positioning, and neat little diagrams about what our clients need. But customers do not live inside our map. They live inside emotion, contradiction, confusion, hope, resistance, and language that is often messy and unfinished.
That is where the insight lives.
Not in your elegant explanation of the problem, but in the gap between your explanation and their lived reality.
That was the heart of Kay’s training inside WTIC. She showed us how to move beyond standard marketing personas and into something far more useful. Instead of relying only on surveys, interviews, or our own assumptions, she uses AI and scraping tools to listen to peer-to-peer conversations where people are more honest, more emotional, and less filtered.
This is where tools like Apify become powerful
Apify lets you gather public conversations from places like Reddit, YouTube, Substack, X, Instagram, and more, so you can study what people are already saying in their own words.
The value is not in collecting random noise. It is in hearing the raw language of the market. Not the polished answer people give when asked directly, but the real words they use when they are frustrated, confused, ashamed, curious, or trying to solve something on their own.
That is the difference between surface-level research and actual consumer insight.
Why this matters
A lot of business owners still build messaging from the wrong source. They build from what sounds smart, what they think people should care about, or what other experts in their space are already saying. The result is content that sounds fine but does not land. Offers that make sense intellectually but do not create urgency. Positioning that feels polished but generic.
Kay’s point was that people often “hallucinate” in direct surveys or interviews. They give socially acceptable answers. They say what they think they are supposed to say. But in peer-to-peer conversation, their real concerns show up. Their contradictions show up. Their workarounds show up. Their emotional truth shows up.
That is where you find the language that actually moves people.
She talked about this as the gap between ideal and real. People say they want one thing, but their behavior and emotional language reveal something else. They say they want visibility, but they avoid being seen. They say they want accountability, but what they really want is permission to rest. They say they want support, but they do not want to feel dependent.
That tension is not a problem to ignore. It is the heart of the opportunity.
What made Kay’s framework so valuable
What I appreciated most about Kay’s approach was that it does not stop at insight for the sake of insight. It turns research into strategy.
This is not about making prettier personas. It is about finding the emotional and linguistic patterns that shape stronger offers, sharper messaging, and more relevant content. It is about hearing what people actually mean, not just what they say on the surface. It is about understanding not only the problem they want solved, but the identity tension, shame, hope, and contradiction wrapped around that problem.
That is also why this process is so useful if your content feels flat or your offers are not converting the way you want them to. It gets you out of your own head. It shows you where your market is emotionally. It gives you language you can use in your Substack posts, webinar pages, LinkedIn content, and sales copy.
Kay also shared that she uses an AI-based Board of Directors approach, where different AI agents or roles push on ideas from different angles. I liked that a lot, because one of the biggest problems founders have is falling in love with their first interpretation and calling it insight. This kind of structured challenge helps you think more clearly.
If you want more trainings like this, with guest experts, practical AI strategy, and smart conversations about tech, messaging, visibility, and business growth, you can check out my Women’s Technology Integration Collaborative here:
https://www.skool.com/womens-tech-collaborative-2106/about
And if you want to start experimenting with this kind of listening-based research yourself, here is the Apify link again: https://apify.com?fpr=viveka
Because better offers do not start with louder marketing.
They start with better listening.
How to do deep consumer research with Apify and AI
Here is the step by step process Kay walked us through, translated into something practical you can use in your own business.
Upgrade here on Substack - or pop over to the Women’s Technology Integration Collaborative for the training, worksheets and PPT.
