# How to use AI for a ‘voice of the customer’ analysis > Source: > Published: 2026-10-12 09:00:00+00:00 You can read endless online advice telling you how to train [AI](https://www.fastcompany.com/section/artificial-intelligence) to sound like you. Most suggest using AI to analyze your blog, your newsletter, and your social posts.  That’s all fine, but you should also be asking AI to analyze your *customers*—the words they use to describe their pain points. A “voice of the customer” analysis or document is what companies often use to guide everything from web pages to sales material.  If you’re a [solopreneur](https://www.fastcompany.com/section/solopreneurs), you’re the whole research team for a voice-of-customer analysis. The good news is that AI can help you build this document from conversations you’ve already had with clients. And the results might change how you describe your own work. Earlier in my career, I was the product manager at a [financial technology](https://www.fastcompany.com/section/fintech) company. Part of my job was translating what customers asked for into something the development team could build. I conducted endless interviews because it was critical to hear how customers described their problems, in their own words.  You probably have similar context and conversations for your solo business, just not compiled in one place. A voice-of-customer analysis should capture your clients’ problems and goals. It’s understandable that most solopreneurs skip this step. You talk to clients every week, so you probably feel like you already know what they need. But when you write about their problems, you’re likely using your own vocabulary. Your clients’ words are useful anywhere you market your business, whether you use generative AI to help or write entirely from scratch. You can use your voice-of-customer analysis to guide proposals or to guide the questions you ask during discovery calls. They also work for email sequences or landing pages. When potential clients see their problems described using language they connect with, it’s easier for them to trust that you understand what they need. Start by collecting raw material from wherever it already exists: Conversations with people who *didn’t* [hire](https://www.fastcompany.com/section/hiring) you are also useful. Their objections often show you why someone hesitates. One word of caution: You’ll want to strip out client names and identifying details before you upload anything, especially if you have agreements with your clients that govern the use of their data with AI tools. AI is good at sorting through a big pile of transcripts and other documents. The catch is that AI summaries tend to smooth out the specific language you’re after. So your prompt needs to ask for direct quotes, along with the source for each one. Here’s a prompt you can use: *“I’m uploading [describe documents] from my clients and prospects. Find the problems they mention most often and the outcomes they want. Also flag any hesitations they had about hiring me, and any words or phrases they use again and again. Group everything by theme. For each theme, include direct quotes word for word, with the source. Don’t paraphrase or summarize.”* When the results come back, you’ll want to [spot-check](https://www.fastcompany.com/91280650/ai-hallucinations-could-get-lawyers-fired-law-firm) some of the quotes against your original transcripts, since AI is known to [hallucinate](https://www.fastcompany.com/91417492/deloitte-ai-report-australian-government). If a “quote” doesn’t appear anywhere in the source material, remove it from the document. I plan to refresh my voice-of-customer analysis regularly—at least once a year, and maybe more often. Now that I have the prompt and baseline document, it should be a quick update. Most of the work comes afterward, when you go back through your website and sales copy. The voice-of-customer analysis is simply a starting point to rework the language you use to describe your business.