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.

Platforms like Axio go beyond spotting trends by analyzing customer pain points from negative reviews on sites like Amazon. This identifies specific product flaws and reveals clear, data-backed opportunities for creating superior products.

To combat a high 44% churn rate, the company implemented a simple feedback loop. They surveyed every user who canceled to ask why and what features they wanted. Each month, the team reviewed the feedback and built the most popular requests, steadily improving the product and retention.

Systematically call every customer who has churned, not to win them back, but to thank them and understand why they left. This provides invaluable, unfiltered market research. By the 19th call, you'll have identified core product or service issues that data alone cannot reveal.

By connecting Medallia's CX data with its CRM, CIBC dynamically identifies customers who have had a recent negative interaction. It then suppresses marketing offers to these individuals, prioritizing relationship repair over immediate cross-selling attempts to preserve long-term value.

Use an AI agent to systematically analyze sales call transcripts. By automatically extracting and categorizing data like competitor mentions and objections into a structured format (e.g., a spreadsheet), product marketers can quickly identify trends and prioritize their roadmap and messaging.

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.

A custom internal AI tool can act as a command center by integrating with HubSpot, Slack, and call recordings. It creates a unified customer view, automatically analyzing sentiment to predict renewal likelihood and proactively suggesting specific expansion opportunities.

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.