Metrics like "Marketing Qualified Lead" are meaningless to the customer. Instead, define key performance indicators around the value a customer receives. A good KPI answers the question: "Have we delivered enough value to convince them to keep going to the next stage?"

When a useful metric like "average handling time" becomes a performance target, employees game the system. Reps may hang up on customers to meet quotas, destroying the metric's ability to reflect actual customer satisfaction.

Transformational growth doesn't require a single massive change. Instead, it comes from making small, incremental improvements in a specific sequence: first, boost CSR conversion; then, improve technician close rates; finally, focus on increasing average ticket size. Each step builds on the last.

Go beyond obvious metrics. Measure rep confidence—their belief and authenticity on calls—as a leading indicator of success. Also, measure velocity as the reduction of friction across the entire customer journey, from lead to successful onboarding, not just a simplistic 'time-to-close' metric. These qualitative measures are key.

With infinitely scalable AI agents, cost and time per interaction are no longer primary constraints. Companies should abandon classic efficiency metrics like Average Handle Time and instead measure success by outcomes, such as percentage of tasks completed and improvements in Customer Satisfaction (CSAT).

Go beyond connect rate by measuring 'Conversation Rate'—the percentage of connected calls lasting over a set threshold (e.g., two minutes). This metric filters out immediate hang-ups and provides a truer signal of an SDR's ability to effectively engage a prospect.

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.

Don't wage a direct war on familiar but flawed metrics. The politically savvy approach is to introduce new, more insightful KPIs alongside them. As the new metrics prove their superior value in driving decisions, the legacy ones will naturally become obsolete and be outgrown.

Unlike other business areas, contact centers have highly sophisticated, pre-existing metrics (like average handle time). This allows businesses to apply the same measurement tools to AI agents, enabling a direct and precise comparison of performance, cost, and overall effectiveness against human counterparts.