"Most people don't want to be sold to-they want to be understood. They want proof you understand what's at stake enough not to waste their time, money or reputation. That's always been true, but now our world is flooded with noise, algorithms and cookie-cutter content, what cuts through is not a louder message but a familiar one. Here's the problem as I see it: Most businesses are using AI to write at their customers, not to them."
"What It Means To Write In Your Customer's Voice This isn't about segmenting personas into buzzword-filled decks. This is about learning how your customers actually speak-their pain points, their goals, their worldview-and training AI to replicate that language. It's a repeatable, scalable and, ironically, more human way of creating messaging that connects. And yes, it's wildly effective. Real Data From Real Conversations So how do you actually do this in a way that's authentic and effective?"
"If you want to train AI to write like your customer, you need to feed it the right source material. The best messaging doesn't come from a sales deck or even website copy. It's hiding in: * Sales calls and demos (recordings and transcripts) * Customer support tickets and calls * Google reviews, Yelp and G2 feedback * Testimonials and case studies * Client emails and onboarding Q&As"
Most customers want to be understood rather than sold to and expect proof that their time, money and reputation will not be wasted. Familiar messaging cuts through noise, algorithms and cookie-cutter content more effectively than louder promotion. Many businesses misuse AI to write at customers instead of mirroring their voice. Training AI on real conversational sources—sales calls, support tickets, reviews, testimonials, emails and onboarding Q&As—captures phrasing, metaphors, anxieties, hopes and emotional cues. Using that material produces repeatable, scalable, and more human messaging that connects and demonstrates genuine understanding.
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