An AI product needs a buyer, not just a pitch.
I worked on the initial go-to-market for a conversational AI product: figuring out who it was for, building an outbound pipeline, and using sales conversations to inform product decisions.
AI products can sound impressive in the abstract. The harder part is getting a specific buyer to recognize where the product fits into their world.
The challenge
The product needed an initial go-to-market approach. That meant getting more specific about the ideal customer, starting conversations with potential buyers, and learning what happened once the product was demonstrated.
What I worked on
- Refined ideal customer profiles for the product.
- Built outbound pipeline to get the product in front of potential buyers.
- Worked through sales conversations and product demonstrations.
- Fed customer objections and demo insights back into product iteration.
The useful part wasn’t just the pipeline.
Sales conversations create feedback that a product team can’t get from a pitch deck alone.
The objections people raise, the use cases they respond to, and the questions they ask during a demo can reveal something about the product’s positioning and fit with the buyer.
My work connected those conversations to the product’s early GTM process.
What I took away
A demo isn’t just a chance to sell. It’s a chance to find out whether your story matches the problem the buyer actually has.
When you’re taking an AI product to market, the feedback from a sales conversation can be just as useful as the next meeting on the calendar.
Have an early-stage product and a messy GTM question?