By Gertrude Van Horn, SVP & CIO, Cien.ai

“Relying on flat quota data to judge a sales team is a major mistake. If you don’t know the actual execution effort behind the numbers, you are managing your most expensive resource entirely by gut feel.“

– Rob Kall, CEO & Co-Founder, Cien.ai

The Vague Reality of Rep Performance

When a data executive or business leader asks, “Why is Rep X underperforming?”, the answer they get is almost always vague. Managers fall back on lagging quota metrics or subjective opinions because they lack real visibility.

The real culprit is hidden under a massive mountain of dirty, uncaptured activity data.

Despite heavy investments in modern CRM platforms, the human factor remains a major weakness in go-to-market data. Reps simply dislike logging meetings, phone calls, and emails. This lack of adoption creates an “activity black hole” where a massive chunk of critical GTM execution data is completely lost. For a data leader, this makes accurate pipeline attribution and effective performance coaching nearly impossible.

What AI Sees: Shining a Light on the Activity Black Hole

Advanced data science solves this visibility problem by measuring what is missing. Instead of relying on manual data entry, AI platforms analyze existing patterns to calculate an automated Activity Capture Level. This metric deduces exactly what percentage of sales activities are missing for an individual in any given month.

By looking across the gaps, data science can uncover structural behavioral trends across your teams. The system evaluates:

True Activity Levels: Tracking logged versus unlogged efforts based on historical and peer baselines.
Time Allocation: Determining the average duration a sales professional spends on a specific deal or process step.
Execution Gaps: Automatically flagging skipped pipeline stages or dates backfilled after the fact.
This process standardizes dirty GTM data across multiple categories, converting raw operational noise into structured, reliable metrics.

What Does Success Look Like?

Success means moving leadership from gut-feel management to precise, data-driven coaching. When execution data is clean and visible, you establish an objective dataset that protects both your culture and your bottom line.

With these insights, data and revenue leaders realize immediate operational benefits:

• Targeted Coaching: Managers get clear feedback loops to address the specific weaknesses of each professional.
• Smart Talent Retention: Instead of defaulting to firing reps who might have good potential, leaders can accurately identify and keep the coachable ones.
• Accurate Resource Planning: Leadership can pinpoint exactly why top producers win and build a repeatable playbook to ramp more reps into true A-players.

By deploying a proven, third-party AI platform, you bypass the risk of internal projects failing due to poor data baselines. You get clear operational visibility in days, turning messy CRM activity into an executive driver of revenue growth.

About The Data Exec Series

This article is part of our Data Exec Series, inspired by our work with B2B business leaders, transformation consultants, and PE operating partners. These articles focus on the strategic and operational realities of becoming a truly data-driven executive—ready for the AI revolution. If you’re interested in improving GTM performance and data, check out our Growth Essentials Series and Practical RevOps Analysis Series as well.