AI for Customer Insight

The data is already there

Most companies have more customer insight than they can process. Call recordings, support tickets, NPS verbatims, review sites, sales call notes. The data exists. The bottleneck is synthesis: there are not enough humans to read all of it and extract the patterns.

Feed large volumes of text to an LLM, ask for patterns, and get structured insight back in seconds.

Analyzing customer reviews at scale

Pull 50-100 reviews from G2, Capterra, or the App Store, yours and your competitors'. Paste them (or a sample) and ask:

• "What are the top 5 reasons customers love this product? Quote the specific phrases they use."
• "What are the top 5 frustrations? What language do they use to describe the problem?"
• "Compare the language in positive reviews vs. negative reviews. What does this suggest about the gap between promise and delivery?"

The resulting language is gold for your own messaging. You are using words your customers already use to describe the problem you solve.

Sales call analysis

If you use Gong, Chorus, or Otter, you have transcripts of every sales call. Feed a sample to an LLM weekly and ask: "What objections came up most often? What questions did prospects ask that our materials do not answer? What competitor names came up and in what context?"

Your sales team is generating this market research every day. Most companies never harvest it.