Quality assurance (QA) has always been the heartbeat of call center performance. Yet, even as customer expectations rise and digital channels multiply, many contact centers still struggle with old QA challenges: inconsistent evaluation, resource drains, low agent morale, and shifting customer demands.
Here’s the kicker—up to 65% of contact centers still rely on manual, sample-based QA processes, according to SQM Group. That means most calls go unreviewed, patterns are missed, and agents don’t get the timely coaching they need.
As one VP of CX quipped at a recent conference:
“We’re essentially judging a restaurant based on tasting one spoon of soup from a giant pot.”
It’s clear: traditional QA won’t cut it anymore. In this blog, we’ll walk through eight common call center QA challenges with practical solutions—and then show you how Omind’s AI QMS software addresses each one, at scale.
Key Takeaways
- • Traditional manual QA reviews only a small sample of calls, leaving patterns undetected and coaching delayed; up to 65% of contact centers still rely on this method (SQM Group).
- • Common QA challenges include resistance to change, inconsistent evaluation, resource constraints, balancing quality with volume, vague feedback, data overload, low agent morale, and shifting customer expectations.
- • Solutions include clear rubrics, real-time coaching, automated scoring, structured feedback, KPI-focused dashboards, gamification, and dynamic QA templates.
- • Omind’s AI QMS automates 100% of call reviews, provides real-time actionable feedback, gamifies performance tracking, and adapts to evolving customer needs.
1. Facing Resistance to Change
The Challenge: Agents and supervisors may view QA as a punitive process rather than a supportive one. New QA initiatives often feel like “Big Brother” watching over their shoulders.
The Solution:
- Position QA as a growth enabler, not punishment.
- Involve agents in designing evaluation criteria.
- Communicate career benefits and customer outcomes.
- Celebrate wins to build trust and momentum.
How Omind Helps: Omind smart QA system offers real-time coaching feature makes feedback constructive and immediate, not scary. Gamified dashboards and automated recognition (badges, positive reinforcement) show agents the upside of QA. Instead of fearing evaluation, agents actually look forward to progress tracking.
“If you want buy-in, make QA feel less like detention and more like a fitness tracker.”
2. Combating Inconsistent Evaluation
The Challenge: Human evaluators often interpret standards differently, leading to unfair or inconsistent scoring.
The Solution:
- Create clear rubrics with examples.
- Run calibration sessions regularly.
- Customize scorecards by call type.
- Use automation for consistency.
How Omind Helps: Omind’s AI-powered automated scoring evaluates 100% of interactions using standardized benchmarks. No more “it depends who scored you.” Historical analytics and calibration modules keep evaluation fair, reliable, and up to date.
3. Resource Constraints
The Challenge: Manual QA is slow, labor-intensive, and can’t scale. Supervisors spend more time auditing than coaching.
The Solution:
- Deploy speech analytics and automated QA.
- Prioritize reviews for high-impact calls.
- Integrate QA with CRM systems to reduce duplicate effort.
How Omind Helps: Omind’s AI QMS automatically reviews 100% of calls using machine learning, slashing manual workload. Supervisors can finally shift focus from “checking boxes” to developing people. Gartner estimates that AI-driven QA reduces auditing time by up to 80%—that’s hours freed for coaching.
4. Balancing Quantity and Quality
The Challenge: High call volumes force QA teams to cut corners, trading accuracy for speed.
The Solution:
- Set realistic evaluation targets.
- Use analytics to optimize review ratios.
- Implement real-time coaching tools.
How Omind Helps: Instead of random sampling, Omind’s AI QMS flags priority calls needing human review. The rest are auto-scored. This hybrid approach balances speed with depth—so every call counts without burning out QA teams.
5. Providing Actionable Feedback
The Challenge: Vague, generic feedback (“be more empathetic”) frustrates agents.
The Solution:
- Deliver feedback tied to specific call moments.
- Provide structured coaching programs.
- Use AI-driven summaries for targeted insights.
How Omind Helps: Omind’s AI QMS pinpoints exact behaviors—for example, identifying when empathy dropped in a retention call. Integrated coaching tools turn those insights into clear, actionable steps, so agents know exactly what to do next.
6. Limiting Data Overload
The Challenge: QA platforms often drown managers in reports without clear priorities.
The Solution:
- Focus on KPIs that align with business goals.
- Use data visualization for clarity.
How Omind Helps: Omind’s AI QMS transforms huge datasets into visual dashboards and trend reports. Managers can see at a glance whether customer satisfaction is rising, where compliance risks lurk, or which agents need targeted coaching.
7. Maintaining Agent Morale
The Challenge: Too much monitoring creates stress and resentment.
The Solution:
- Balance feedback with recognition.
- Use gamification to encourage progress.
- Reward high-quality performance.
How Omind Helps: Omind’s AI QMS’ feedback engine delivers both praise and constructive tips in real time. Add in gamification and recognition programs, and suddenly QA feels like progress, not punishment.
One agent summed it up after a pilot program:
“It’s like having a coach in your ear who also remembers to say ‘good job.’”
8. Adapting to Evolving Customer Expectations
The Challenge: Standards quickly become outdated as customer needs evolve.
The Solution:
- Review QA criteria regularly.
- Involve frontline agents in updates.
- Stay open to new metrics and technologies.
How Omind Helps: Omind’s dynamic QA templates and continuously updated AI models adapt to market shifts, customer feedback, and compliance changes. That means QA always reflects what customers value today—not last year.
Summary Table
Final Thoughts
QA isn’t just about catching mistakes—it’s about building a culture of improvement, fairness, and customer obsession. The right strategy can make QA less of a bottleneck and more of a growth engine.
But as call volumes surge and customer expectations skyrocket, manual QA simply can’t keep pace. That’s why forward-looking contact centers are moving to Omind’s AI QMS platform that scales effortlessly, delivers actionable insights, and keep sagents motivated.
“Manual QA is like using a flip phone in the age of smartphones. Sure, it works—but why would you?”
By solving each of these eight core challenges with intelligent automation, real-time coaching, and gamified recognition, Omind helps call centers achieve higher performance, happier agents, and customers who actually stay loyal.
The future of QA isn’t just about measuring—it’s about empowering. Contact us to learn more about AI QMS.
About the Author
Robin Kundra, Head of Customer Success & Implementation at Omind, has led several AI voicebot implementations across banking, healthcare, and retail. With expertise in Voice AI solutions and a track record of enterprise CX transformations, Robin’s recommendations are anchored in deep insight and proven results.