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.
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Don't expect an AI agent to invent a successful sales process. First, have your human team identify and document what works—effective emails, scripts, and objection handling. Then, train the AI on this proven playbook to execute it flawlessly and at scale. The AI is a scaling tool, not a strategist from day one.
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.
The critical flaw in most sales tech is its failure to correlate rep behavior with performance outcomes like quota attainment. The real value is unlocked not just by knowing what reps do, but by connecting those actions to who is succeeding, thus identifying true winning behaviors and separating A-players from C-players.
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.
The primary ROI of sales AI isn't just saved time, but the reallocation of that time. Evaluate and justify AI tools based on their ability to maximize Customer Facing Time (CFT), as this directly increases both the quantity and quality of customer interactions, leading to better performance.
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.
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.
An automated workflow analyzes call transcripts and sends immediate, private feedback to the sales or CS rep on what they did well and where they can improve. This democratizes high-quality coaching, evens the playing field across managers of varying skill, and empowers motivated reps to upskill faster.
Go beyond the native summaries in conversation intelligence tools like Gong. Copy and paste the full transcript of a sales call into a generative AI like ChatGPT and ask for deeper insights, hidden objections, or recommended next steps. This cross-platform workflow can reveal nuances that a single tool might miss.
When successful reps get bored and start changing their effective talk tracks, their performance can dip. To coach them, anchor the conversation in data from their peak. Review past call recordings and metrics to show them precisely how their messaging has deviated and guide them back to their proven strategy.
