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 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.
After a promising sales call, combat 'happy ears' by feeding your meeting notes into an AI. Ask it to identify the top three reasons the deal might *not* go through. This provides an unbiased third-party analysis, revealing red flags and potential objections you can address proactively.
Every customer call is a potential blog post. An AI workflow systematically redacts all sensitive and identifying information from call transcripts, then rewrites the core use-case discussion into an SEO-optimized article. This creates a scalable content machine fueled by real customer problems, generating thousands of posts.
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.
Keyword tools are useless for identifying the ultra-long-tail queries (often 60+ words) that drive Answer Engine Optimization. The best source for this content is your own first-party data. Analyze support tickets, sales call transcripts, and Reddit threads to discover the highly specific questions your customers are actually asking.
AI can't replicate insights gained from direct customer interaction. Methods like joining sales calls, reading product reviews, and one-on-one interviews provide "first-party data" essential for creating resonant content and differentiating your brand from competitors relying on public data.
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.
Instead of asking AI to generate generic blog posts, use it for strategic ideation. Prompt ChatGPT with a detailed description of your ideal client and their transformation, then ask it to list their top 25 problems or questions. This provides a roadmap for creating highly relevant, problem-solving content.
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.
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.