Improve Contact Center Agent Performance: 14 Strategies
TL;DR: Agent performance combines efficiency and quality, and both drive business results. To improve it, measure across four categories (efficiency, quality, customer experience, and agent experience) and apply strategies that address root causes like inadequate tools, poor knowledge access, disconnected coaching, and gaps in training.
Every contact center leader knows the difference between what their agents could be doing and what's actually happening on the floor. Agent performance shapes customer satisfaction, controls costs, determines whether you hit revenue targets, and influences whether your best people stick around or burn out.
And the stakes keep rising. A McKinsey report found that generative AI applied to customer service agents increased issue resolution by 14% per hour and reduced handle time by 9%, with a 25% reduction in attrition and escalations. Organizations that combine AI with strong agent fundamentals are pulling ahead, while those that don't are stuck in a cycle of high turnover, inconsistent quality, and rising costs.
What is agent performance?
Agent performance has two sides. The first is operational efficiency—the basic mechanics of getting work done. The second is quality, which is what actually drives long-term business outcomes.
When organizations focus only on efficiency, they often sacrifice the quality that determines whether customers stick around or leave. An agent who rushes through calls to hit speed targets might look great on a dashboard while quietly hurting customer relationships. Meanwhile, an agent who takes extra time to solve problems might seem slower but creates more value through loyalty and fewer repeat contacts.
This distinction shapes how you invest in improvement. If you think of performance narrowly as speed and cost control, you end up optimizing for the wrong things.
How to measure agent performance
To get a full picture of performance, you need metrics across four categories.
Efficiency metrics track operational performance. Average Handle Time (AHT) measures total interaction duration including talk time, hold time, and after-call work. An ICMI analysis noted that shorter is not always better, since top-performing centers achieve the 7 to 10 minute range while maintaining high satisfaction and resolution rates. Schedule adherence, occupancy rate, and call abandonment rate round out this category.
Quality metrics capture whether agents are doing the job right. First call resolution (FCR) measures whether an agent solves a customer's issue completely during the first interaction. According to SQM Group, which has benchmarked 500+ centers over 25 years, the cross-industry FCR average sits just under 70%. "Good" FCR falls between 70 and 79%, while 80% or above is achieved by only 5% of contact centers. The financial impact is significant: every 1% improvement in FCR translates to approximately $286,000 in annual savings for a midsize contact center, according to SQM Group's benchmarks (FCR Benchmark 2024 Results by Industry). Beyond FCR, quality management (QM) scores, transfer rate, and error rate complete the picture.
Customer experience metrics reflect how customers perceive the service they receive. These include Customer Satisfaction (CSAT) scores, Net Promoter Score (NPS), and Customer Effort Score (CES).
Agent experience metrics help predict retention—yet they're often overlooked. According to ICMI's 2025 report "What Contact Centers Are Measuring," only 38% of contact centers currently measure agent satisfaction and well-being metrics, a significant blind spot given the direct link between agent experience and attrition. That gap is costly. ICMI's 2025 report "How to End the Contact Center Attrition Crisis," citing ContactBabel's 2024 US Decision-Maker's Guide, found that 54% of contact centers experience attrition ranging from 21% to over 50%, and replacing one agent can cost over $35,000 when including all direct and indirect costs.
Balancing all four of these categories matters more than going all-in on any single one.
Fourteen strategies to improve agent performance
These fourteen strategies tackle the root causes of poor performance rather than just treating symptoms. They fall into three groups that cover technology and tools, agent development and retention, and operational processes.
1. Quality management that analyzes every conversation
Traditional QM reviews about 1 to 2% of conversations because supervisors can only manually listen to so many recordings. Machine learning-powered quality management changes this by analyzing every conversation automatically, scoring interactions against your rubrics and spotting patterns across your entire operation. Some organizations report visible improvements within their first quarter.
To put this into practice, Cresta's conversation intelligence analyzes every interaction for improvement opportunities, while the broader Cresta platform connects real-time agent assistance with quality management and coaching in one system.
2. Real-time agent assistance and knowledge delivery
Agents need help during conversations, not just after. Agent assistance provides real-time support while agents talk to customers instead of making them dig through knowledge bases or wait for a supervisor. The technology brings up relevant information and suggests next-best-action recommendations right in the agent's desktop.
One of the biggest drags on productivity is what Cresta calls the "toggle-tax"—the mental fatigue caused by constantly switching between CRMs, knowledge articles, and help desk tools. Cresta Knowledge Agent addresses this by continuously listening and delivering precise, cited answers in real time through a persistent browser sidebar, grounded in both conversation and on-screen context.
For broader coverage, Cresta Agent Assist provides real-time guidance across voice and digital channels. Behavioral Guidance delivers situation-specific hints and compliance reminders during live conversations, and chat efficiency tools minimize keystrokes so chat agents can handle multiple conversations at once.
3. Centralized knowledge management and content governance
Real-time delivery only works if the underlying knowledge is accurate and well-organized. When company policies, product information, and troubleshooting procedures live in dozens of disconnected repositories, agents waste time searching instead of solving problems. New agents suffer the most because they don't yet know which systems to check first.
Effective knowledge management requires consolidating content into a unified system with clear ownership and regular review cycles. On the delivery side, Knowledge Agent puts cited answers from connected sources directly into the agent workflow, closing the gap between where knowledge lives and where agents need it.
4. Automate after-call work and administrative burden
After-call work eats up a significant portion of agent time without adding direct value for customers. Tasks like record updates, call notes, follow-up emails, and transaction processing all pull agents away from the next customer in the queue.
AI-generated summaries are one of the highest-impact ways to cut this burden. AI can generate accurate summaries in real time and push them directly to your CRM, which brings handle times down and improves agent satisfaction.
5. Build a connected contact center technology stack
Agent performance suffers when CRM, quality management, knowledge management, analytics, agent assistance, workforce management, and automation tools operate in isolation. Disconnected systems force agents to bridge the gaps, manually transferring information between tools and maintaining context that should flow automatically.
Some functions like routing and workforce management are handled by dedicated systems within the broader contact center infrastructure. Others—like quality management, coaching, agent assistance, and conversation analytics—benefit from being unified on a single platform where data flows freely between them.
6. Coaching workflows connected to performance data
Good coaching needs a structured approach where feedback connects directly to specific behaviors from actual customer interactions. Coaching workflows tied to QM scores create targeted development by pinpointing exactly which skills each agent needs to work on. Brief, frequent coaching conversations tend to produce better results than monthly or quarterly reviews because the feedback stays fresh. The data backs this up: Deloitte's 2025 report "Global Human Capital Trends" found that effectively developing direct reports can boost their performance by up to 27% and make them 1.5x more likely to exceed goals.
Cresta's coaching tools put this into practice by finding specific coaching moments based on what top performers do differently, connecting conversation intelligence directly to agent development.
7. Structured training and onboarding programs
While coaching refines existing skills, training builds the foundational knowledge agents need before they ever take a live call. In complex operational environments, agent onboarding still requires 4 to 12 weeks even with AI-assisted training (COPC, "Quantifying CX Transformation ROI"). The upfront investment pays for itself through lower early-stage attrition and faster paths to competent performance.
Effective training goes beyond product knowledge to include soft skills like active listening, empathy, and objection handling. That foundation then needs ongoing reinforcement, since product changes, policy updates, and seasonal shifts all demand continuous learning.
8. Gamification and recognition programs
Recognition tied to specific, measurable behaviors has a stronger impact on performance than general praise or monetary incentives alone. COPC's research on contact center retention reinforces this point: recognition programs tied to specific behaviors show the clearest causal evidence for reducing voluntary turnover, while generic programs have limited lasting effect.
The key is connecting gamification programs to real performance metrics rather than vanity activities. Cresta's Behavior Tracking and Gamification functionality tracks agent behaviors in real time and reinforces positive behaviors with kudos, connecting recognition directly to the conversation moments that matter.
9. How to address agent burnout and wellness
Agent burnout typically manifests as emotional exhaustion that leads to cynicism toward customers and reduced effectiveness over time. One pattern that catches leaders off guard is agents reporting burnout while simultaneously showing high idle time—which usually points to scheduling problems or uneven workload distribution rather than too much work.
At its core, preventing burnout comes down to a few essentials: reasonable performance expectations, enough autonomy to handle interactions naturally, tools that genuinely make the job easier, and a visible path forward in their career. When those conditions are missing, even well-scheduled agents burn out.
10. Transparent career development pathways
Many agents see contact center work as a dead-end job, and that mindset contributes directly to high turnover. Documented career ladders showing how someone can progress from agent to specialist, team lead, quality analyst, trainer, or manager—with transparent promotion criteria tied to performance metrics—turn an abstract promise into something tangible.
The impact on retention is clear. Gallup's meta-analysis research on engagement and business outcomes found that in high-turnover organizations, highly engaged business units experience 21% less turnover. Career visibility is one of the strongest drivers of that engagement because it gives agents a reason to invest in their own improvement.
11. Workforce engagement management systems
Workforce Engagement Management (WEM) connects operational functions that are typically managed in silos—from scheduling and forecasting to performance tracking, quality management, and coaching. When these systems work together, forecasting data informs scheduling, scheduling data feeds into performance tracking, and performance patterns trigger coaching workflows.
Scheduling and forecasting are typically handled by dedicated workforce management tools rather than by any single AI platform. Making sure these systems connect to your quality and coaching workflows ensures insights flow in both directions.
12. Customer self-service and deflection strategy
When contact centers successfully deflect low-complexity interactions to self-service channels, agents spend less time on repetitive questions and more time on complex problems that benefit from their skills. Well-designed IVR systems and chatbots can handle straightforward requests without agent involvement. For more complex, multi-intent conversations, Cresta AI Agent handles interactions autonomously across voice and digital channels with natural, human-like conversations.
The challenge is knowing which interactions to automate. Cresta's Automation Discovery analyzes conversations by topic to identify automation candidates, providing a readiness score based on flow complexity, conversation volume, and resolution rates.
13. Performance management for remote and hybrid teams
Distributed work introduces specific challenges for coaching visibility, consistent quality standards, and equitable treatment. Remote agents may have fewer informal learning opportunities and less access to peer support, and supervisors can't walk over and listen to a conversation or offer quick guidance between calls.
QM systems that analyze 100% of conversations are especially valuable in remote environments because they eliminate the visibility gap between on-site and remote agents. Real-time agent assistance tools like Cresta Agent Assist fill the remaining gap by providing in-the-moment guidance that remote agents might otherwise miss.
14. Operationalize your agent performance measurement framework
Different levels of the organization need different views. Frontline supervisors need daily visibility into quality scores and adherence. Contact center leadership benefits from weekly views that connect efficiency, quality, and agent experience trends. Executive stakeholders typically need monthly or quarterly summaries that tie contact center performance to business outcomes like revenue and retention.
The framework becomes most powerful when you connect metrics to decision triggers. For example, when first call resolution drops below a threshold, that decline should automatically generate a coaching focus area. If agent satisfaction scores decline for a specific team, the framework should prompt a review of workload distribution and scheduling patterns before the problem shows up as attrition.
Making agent performance improvement work in your operation
Cresta brings these strategies together on a single AI platform built for contact centers. What conversation intelligence reveals about top performers feeds directly into real-time guidance and coaching workflows. Knowledge Agent puts answers at agents' fingertips without searching. After-call work gets automated so agents stay focused on customers.
Visit our resource library to explore more guides on contact center performance, or request a demo to see how Cresta can help your operation.
Frequently asked questions
How long does it take to see results from agent performance improvements?
Most organizations see initial improvements within a few weeks of rolling out new tools or processes, though this varies based on deployment scope and baseline maturity. Bigger changes to metrics like first call resolution and customer satisfaction typically show up within one to two quarters.
Should I focus on improving my worst performers or my average performers?
Average performers usually offer the biggest opportunity. Your worst performers may have fundamental fit issues, while your top performers are already doing well. Moving your middle tier up even slightly can have a huge impact because they represent the largest group.
How do I get buy-in from agents on new performance initiatives?
Be upfront about what's changing and why. Agents respond better when they understand that new tools are meant to help them succeed, not just monitor them more closely. Involving agents early and showing them how changes make their jobs easier builds buy-in faster than any formal rollout plan.
What's the biggest mistake contact centers make with agent performance?
Focusing too heavily on efficiency metrics like Average Handle Time while ignoring quality and agent experience. This creates a pressure cooker where agents rush through calls and customers don't get problems solved, which keeps turnover high and wipes out any short-term cost savings.
How often should agents receive coaching?
Brief weekly sessions focused on a single skill produce better results than longer monthly reviews, because agents can connect feedback to conversations they still remember. The critical factor is tying coaching to specific, recent interactions rather than generic performance trends.
How does routing affect agent performance?
Skills-based routing reduces transfers and repeat contacts by matching customers to agents with the right expertise. When agents consistently receive interactions they're equipped to handle, first call resolution improves and handle times decrease. Routing is typically managed by dedicated workforce management or CCaaS systems within the broader contact center stack.
