Contact center AI sits at the intersection of speech analytics and quality management, using cutting edge speech technology and natural language processing to transcribe and analyze support calls at a massive scale. It enables organizations to analyze 100% of customer conversations with the ultimate goal of improving agent performance and the overall customer experience.
With contact center AI, key moments in conversation can be unearthed to provide a more accurate picture of how the contact centers as a whole, and the individual agents staffing them, are performing across key metrics. Analytics on interactions like sentiment, emotion, dead air, hold times, supervisor escalations, redaction, and more are often game-changing for businesses who previously had low QA coverage, and contact center AI is the key to identifying them.
Once transcribed and analyzed, contact center AI automatically scores some parts of conversations and enables organizations to create tailored coaching programs for agents.
Contact center AI emerged as a result of the inefficiencies of highly manual traditional quality management (QM) programs. Organizations struggled to fully-understand performance, monitor mission-critical KPIs and compliance, and better enable their agents with relevant training.
Contact center AI, built around Analytics-enabled Quality Management, radically transforms an organizationās quality programs in a number of ways:
āāSuccess for our team means bringing out the best in each agent. Weāre able to do that by throwing out the one size fits all coaching approach and tailoring conversations on an individual basis. Contact center AI helps ensure youāre an optimized leader by identifying and addressing the right gaps.ā
- Kyle Kizer, Compliance Manager at Root InsuranceĀ
Contact center AIĀ provides a wide variety of benefits to improve processes across a contact center. Next, weāll dig into some real-world use cases of how contact center AI and quality automation is used today.
Why It MattersĀ
Regulatory compliance is paramount across all industries, most notably financial, insurance, and healthcare. It ensures the protection of customer data, backed by strict legislation to enforce it. As a result, monitoring mandatory compliance dialogues and categorizing voice calls relevant to specific compliance regulations is mission-critical.Ā
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Why It MattersĀ
The beginning of a conversation is important from both a customer experience and a compliance standpoint. The end of a conversation is also important for customer experience, and it also is an opportunity to both better confirm how the call went and create next steps.
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Why It Matters
Supervisor escalations are a strong indicator of a negative customer experience, a metric for agent call-handling, or an organizational inefficiency. Escalations in any contact center are costly due to the amount of time and resources required to resolve them.
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Why It Matters
Customer sentiment analysis is an indicator of how people feel about a brand, its products, and its service. Simple sentiment analysis is determined based on words alone (what's being said), while advanced sentiment analysis (tonality-based) considers tone and volume as well (what, how, and why it's said).
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Measurable KPIs
ContactĀ center AIĀ is transforming the contact center as we know it, uncovering deep insights across every single voice call that takes place, and providing the data needed to drive more targeted training programs for agents.
āWhatās exciting about contact center AIĀ is that we can change the way weāre coaching and re-write our quality cards. We can move away from check-boxes and focus on real skill development. Using contact center AI helps us change behavior faster.ā
- Dale Sturgill, VP Call Center Operations, EmployBridge
Joe Hanson leads content marketing at Observe.AI. Want to guest blog? Or maybe you have some expertise you want to share?Ā Connect with him on LinkedIn.ā