Don't just measure SDR calls and emails. Systematically track the *reason* for outreach—the sales trigger. Was it an intent signal, a form fill, or cold outreach? This crucial data reveals which initial signals actually lead to the best outcomes and deserve more investment.

Despite lower volume, leads from high-intent forms like 'demo request' converted at double the rate of product trials. They also resulted in deals that were twice as large, highlighting a massively undervalued pipeline source that was being ignored in favor of high-volume, low-quality trials.

Traditional funnels jump from a marketing signal (like an MQL) to an opportunity, creating a blind spot. They miss the 'Engagement' period of initial interaction and the 'Prospecting' phase of active sales pursuit. Ignoring these stages makes it impossible to diagnose performance issues or identify improvement levers.

The company's win rate collapsed to a catastrophic 3-5%, well below benchmarks. This inefficiency was a direct result of their 80% pipeline visibility gap. Without knowing which triggers produced quality deals, they were trying to fix the problem with a blindfold on, unable to make data-driven decisions.

Most GTM systems track initial outreach and final outcomes but fail to quantify the critical journey in between. This "ginormous gray area" of engagement makes it impossible to understand which activities truly influence pipeline, leading to flawed, outcome-based decision-making instead of journey-based optimization.

Instead of debating multi-touch attribution, first identify the single, independent event that caused a sales rep to engage a prospect. This "trigger" (e.g., demo request, MQL score) reveals the true efficiency of your GTM motions, which is a more fundamental problem to solve.

A key reason for the company's low win rate wasn't just poor execution; it was a flawed process. Sales reps created 'opportunities' to track target accounts for prospecting, not actual qualified deals. This practice completely polluted their pipeline metrics and disguised the true performance of their sales motion.

One company discovered that while MQLs were plentiful, they took 130 days to convert. In contrast, "hand-raiser" leads converted in just 12 days at a much higher rate. Focusing on conversion velocity reveals where to allocate resources for efficient growth.

A startup with a sales-driven pipeline leveraged intent data to identify accounts actively researching their solution category. By targeting these accounts with relevant content and webinars, the marketing team transformed the pipeline to be 56% marketing-driven within a single quarter.