A company solved its sales team's information gap by treating 25,000 hours of recorded Gong calls as the ultimate source of truth. This existing internal data, previously ignored, became the foundation for a company-wide AI automation strategy that transformed their go-to-market operations.

An enablement team replaced a third-party tool with a custom AI agent to analyze sales calls. They discovered top-performing reps don't discuss product features until an average of 17 minutes into a call. This data-driven insight revealed their existing training methodology, focused on product knowledge, was fundamentally flawed.

Upload call recordings or transcripts from tools like Gong or Fathom into an AI model. Ask specific questions like, 'Where was the most friction?' to identify disconnects you missed in the moment. Use this insight to craft hyper-relevant follow-ups that address the core misunderstanding.

A primary AI agent interacts with the customer. A secondary agent should then analyze the conversation transcripts to find patterns and uncover the true intent behind customer questions. This feedback loop provides deep insights that can be used to refine sales scripts, marketing messages, and the primary agent's programming.

To create resonant content, move beyond guessing customer problems. Analyze transcripts of past sales calls with an AI tool to identify recurring pain points, common questions, and the exact language your audience uses to describe their challenges.

Instead of guessing keywords, an LLM analyzes customer call transcripts to identify the exact terms customers use to describe their needs. These keywords are then automatically added to Google Ads campaigns, creating a closed-loop system that ensures marketing spend is aligned with the authentic voice of the customer.

An LLM analyzes sales call transcripts to generate a 1-10 sentiment score. This score, when benchmarked against historical data, became a highly predictive leading indicator for both customer churn and potential upsells. It replaces subjective rep feedback with a consistent, data-driven early warning system.

Feed recordings of sales calls from lost deals into an AI for a post-mortem. The AI can act as an impartial sales coach, identifying what went wrong and what could be done better, providing instant, actionable feedback without needing a manager's time.

A powerful AI use case is running automated agents on sales call transcripts. These agents can perform tasks like extracting and populating MEDPICC data into Salesforce or summarizing competitor mentions for battle cards, saving sales teams hours of manual work per week.