Most contact centers have more metrics than they know what to do with.
Recently, a leadership team walked me through a dashboard containing dozens and dozens of measures: wait times, staffing levels, quality scores, handle times, customer satisfaction, sentiment analysis, AI-generated insights, and more.
After about an hour poring over the data, I asked a simple question: Which of these metrics actually change decisions?
The room went quiet.
That moment captures a challenge showing up in many organizations. According to ICMI's State of the Contact Center 2026 report, 69% of contact center leaders believe they efficiently use metrics data to identify gaps and improve performance. Yet 23% say their biggest challenge is translating that data into actionable insights. And roughly a third acknowledge that some metrics are producing mixed or counterproductive effects on employee behavior.
In our experience working with contact centers across virtually every industry, only about 10% to 15% of organizations are truly leveraging the strategic value of their contact centers. Not having the right supporting metrics is one of the major limitations. The problem is not a lack of information. It’s that many organizations are still measuring yesterday's priorities and getting yesterday's results.
Most organizations measure activity. The best measure causes, outcomes, and impact. That distinction is becoming one of the clearest dividing lines between organizations running efficiently and those improving the business.
Beyond Measuring Activity
For decades, contact center metrics focused on two major themes: operational efficiency and quality. They included service level, quality scores, average handle time, occupancy, first contact resolution, and cost per contact. These measures remain important. Every operation needs to be well managed.
But the environment has changed. Customers increasingly resolve routine issues through digital channels, self-service tools, and AI-powered support. The interactions that reach employees are more complex, emotional, and consequential than before. Many organizations have responded by measuring more things. The best are measuring better things and have become far more focused on the causes of demand than the volume of interactions.
Most organizations measure how many contacts they receive. The best ask why those contacts exist. Every contact represents a customer need, a customer effort, or a signal about how the organization is performing. That shift changes how leaders think about nearly every metric they use.
Seven Areas Where the Best Are Pulling Away
We've found in working with our clients that seven areas deserve leadership attention. What has changed is how the best organizations work within each area and how far they are pulling ahead.
1. Anticipating Customer Needs
Most organizations measure forecast accuracy. That remains important. But in the 2026 research, only 29% of leaders cited it among the metrics they valued most, near the bottom of the list. Only 19% forecast and schedule across all supported channels, and nearly half (45%) still rely on manual processes for intraday adjustments.
Leaders in the best managed contact centers have a different mindset: if you don’t have a good handle on the work coming your way, how can you count on anything else going well? Accordingly, they view forecasting as more than a planning exercise. They use AI and interaction analytics to understand why customers are contacting them and where future demand can be prevented. A spike in billing contacts may signal a confusing process. A surge in technical support may reveal a product issue to fix upstream.
The goal is no longer predicting workload. It is understanding customer behavior well enough to shape it.
2. Anticipating Resource Requirements
Traditionally, leaders focus on staffing levels, schedule adherence, and utilization. Those remain foundational. But today's customer journey may involve self-service tools, AI assistants, advisors, specialists, and multiple digital channels, often within a single interaction.
Most organizations measure whether schedules were met. The best ask whether customers reached the right resource at the right moment, be it human or AI. The question is no longer whether enough people are scheduled. It is whether the customer journey is working.
3. Accessibility
Customers do not experience service levels. They experience effort. A customer who spends ten frustrating minutes navigating self-service before reaching an advisor may technically encounter excellent queue performance, but that does not mean the experience was easy. And their frustration level will be even higher if they spend time searching for hard-to-find contact numbers.
In the 2026 research, 57% of leaders want new or improved metrics for measuring total customer effort across channels, and most do not yet have them. Another 55% identified self-service effectiveness as a priority. The best organizations are asking how hard customers had to work to get the help they needed.
4. Quality of Interactions
As AI handles more routine work, human interactions create value through judgment, empathy, creativity, and problem solving, not checklist completion. The best organizations evaluate outcomes. Was the issue fully resolved? Was trust strengthened? How did they feel about the interaction?
In the 2026 research, 54% of leaders said AI-assisted interactions need their own quality framework. The best organizations resist the urge to build separate quality frameworks for AI-assisted and human interactions. Customers don't experience the difference; they experience the outcome. Splitting the framework creates complexity without adding clarity. Even so, the evaluation tools most organizations use today were not designed for a world where a human and an AI are working side by side. The best organizations are not waiting to figure this out.
5. Employee Engagement
The 2026 research surfaces a striking tension. In the survey, 80% of leaders believe their organizations have gotten better at addressing the root causes of turnover, and 78% believe agents feel valued and supported.
Unfortunately, these views have not translated to retention. In the same survey, 42% reported annual turnover rates above 50%. The perception and the reality are not matching up.
Traditional engagement measures are largely lagging indicators. By the time they signal a problem, it has been building for months. The best organizations pay closer attention to readiness. Do employees have the skills and confidence to handle increasingly complex interactions? In many organizations right now, readiness risk and retention risk are the same risk.
6. Customer Satisfaction and Loyalty
Surveys tell only part of the story. A customer can rate an interaction highly and still not come back. Another can express frustration and remain loyal for years.
The best organizations connect experience metrics to actual behavior: retention, repeat contacts, referrals, and customer lifetime value. They are also using AI-generated sentiment data to surface signals in real time rather than waiting weeks for survey results. Loyalty is reflected in what customers do, not what they say.
7. Strategic Value
Most organizations treat customer feedback as something to report. The best treat it as something to act on.
Consider two organizations facing the same surge in contact volume. One improves staffing and works harder to keep pace. The other investigates the underlying causes, discovers customers are getting stuck at the same point in an online process, and works across departments to eliminate the friction. Both organizations manage the workload. Only one reduces it.
The goal is not to eliminate customer contact. Many interactions create real value. The goal is to eliminate avoidable customer effort. The best organizations measure how contact center insights contribute to product improvements, process simplification, policy changes, customer retention, and growth. They track whether change actually happened.
They are not just reporting insights. They are driving them into the organization and serving as catalysts for innovation and improvement.
Measuring Beyond the Contact Center
Not all customer service work reaches the contact center. Customers seek answers in online communities, social networks, and review sites, often without ever contacting the company directly. Increasingly, some of the most important customer conversations never appear in a contact center report.
The best organizations engage with relevant communities where appropriate and use analytics to identify emerging issues that would otherwise be invisible. They gain earlier visibility into problems, changing expectations, and opportunities for improvement before those issues appear in traditional reports.
The Real Difference
The distinction between average and exceptional contact centers is becoming harder to ignore.
The rest measure contacts. The best measure why contacts happen.
The rest optimize demand. The best work to eliminate demand that should not exist.
The rest report insights. The best drive change.
The rest optimize the contact center. The best optimize the customer journey.
The rest use metrics to manage activity. The best use metrics to understand customers, improve decisions, and influence the direction of the organization.
Those differences matter more now than ever. Customer interactions are becoming more complex. AI is reshaping how work gets done. Customer expectations continue to rise. Organizations measuring yesterday's priorities may find themselves running an efficient operation while falling behind strategically.
AI is not reducing the need for meaningful metrics. It is raising the stakes for getting them right. The organizations pulling ahead are not those with the most dashboards. They are the ones using measurement to create focus, surface the right questions, and drive decisions that improve both customer outcomes and business results.
The best contact centers are redefining what matters. In the process, they are doing something even more important: helping their organizations listen better, learn faster, and adapt more effectively.