Every support ticket, chat transcript and review is a customer telling you something in their own words. Most companies read them one at a time and then forget them. Language models make it practical to read all of them together.
What to extract
- Themes: the recurring problems and requests, ranked by frequency and by how much frustration they carry.
- Language: the exact phrases customers use, which are often better than the ones in your marketing.
- Signals: mentions of competitors, budget, deadlines, or features people assume you have.
A monthly routine
Export the month’s conversations, remove personal data, and ask for a structured summary: top ten themes with example quotes, anything new compared with last month, and questions that came up more than five times. Share it with product, marketing and sales in the same meeting. The conversation that follows is usually the most useful hour of the month.
Privacy first
Strip names, emails and account details before anything leaves your systems, use tools that do not train on your data, and tell customers in your policy how conversations are used. Intelligence built on trust is the only kind that lasts.
