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 company's overall win rate was low (6-7%) and decreasing. Analysis showed this decline mirrored a drop in marketing 'signals' (e.g., event attendance, content downloads) before an opportunity was created. This provided a clear data link between mid-funnel marketing activities and sales success.

By measuring success on 'last lead source,' the company was incentivized to pour money into paid search for product trials—a clear final touchpoint. This model blinded them to the higher value of other lead types and actively discouraged investment in demand creation activities that build brand and generate higher-quality leads.

Limiting marketers' visibility after a lead is passed to sales is 'unconscionable.' Full CRM access allows them to see deal progression, read sales notes, and understand win/loss reasons, providing crucial feedback to align messaging from the first ad to the final close.

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 practice of automatically creating an opportunity for every free trial sign-up was a critical flaw. It treated unqualified sign-ups as sales-ready pipeline, forcing reps to reject many of them and artificially deflating the true win rate of genuinely qualified deals.

To identify which events actually drive business, analyze your last 5-20 closed-won deals. Look for recurring, time-bound triggers that you didn't create. This data-driven approach provides clarity on where to focus your efforts, revealing the organic drivers behind your biggest successes.

Companies struggle to get value from AI because their data is fragmented across different systems (ERP, CRM, finance) with poor integrity. The primary challenge isn't the AI models themselves, but integrating these disparate data sets into a unified platform that agents can act upon.

Despite wide acceptance of committee-based buying, an alarming number of sales pipelines remain flawed. In some organizations, over 80% of deals in the CRM have only one contact person attached. This data highlights a critical execution gap between knowing the right strategy and actually implementing it.