Free Guide
The 2026 US Contact Center Guide to AI Interaction Analytics
Discover how contact center leaders are using AI to improve quality assurance, customer experience, agent coaching, and revenue. Find inside:
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Adoption benchmarks
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Use-case examples
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Research findings
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Practical context for decision-makers
207 Contact Center Leaders Surveyed | Sponsored by Miarec
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Why Download This Guide Now?
Operational pressure is rising
Leaders need to improve customer experience and efficiency at the same time.
The market is moving
46% of respondents already use interaction analytics, while 48% plan implementation at some point.
AI is expanding the value of analytics
Use cases now span QA, CX, churn reduction, customer journey insight, and revenue opportunity detection.
What You’ll Learn in the Guide
Adoption trends
See how interaction analytics adoption is evolving across US contact centers.
Most-used capabilities
Understand which types of analytics are most commonly used today, from post-call speech analytics to multichannel and customer journey analytics.
QA and coaching use cases
Learn how analytics is used to automate or speed up quality monitoring and identify agent-level training needs.
Real-time analytics
Explore how real-time analytics supports guidance, compliance, escalation handling, and in-call intervention.
Customer journey visibility
See how analytics helps teams understand process breakdowns and friction across channels and departments.
Voice of the customer
Understand how analytics contributes to customer feedback loops, root-cause analysis, and continuous improvement.
Key Insights from the Research
The guide is designed as a practical briefing, not just a trend summary. Here are a few of the signals it explores.
Post-call analytics remains the foundation
Among analytics users, 86% say they use historical post-call speech analytics. This suggests many organizations still begin with scalable insight after the interaction before moving deeper into real-time or journey-wide use cases.
Multichannel visibility is becoming more important
53% of analytics users say they use multichannel analytics, and 47% say they use customer journey analytics. As non-voice interactions grow, teams increasingly need a broader view of customer behavior across channels.
QA is one of the clearest value areas
The report shows strong usefulness ratings for automating and speeding up quality monitoring through analytics. This remains one of the most practical starting points for adoption.
CX improvement is a major application area
Respondents using analytics reported strong usefulness for improving customer experience, including checking interaction quality, identifying dissatisfied customers, and spotting opportunities for self-service or process fixes.
