Harry Chang
Harry Chang
Updated: October 20, 2021

Call Center Analytics, Insights, & Conversational AI

Call Center Analytics, Insights, & Conversational AI

Call Center Analytics, Insights, and Conversational AI

Many people can probably remember feeling a sense of dread when calling a business and finding themselves stuck in an automated phone tree. Fortunately, artificial intelligence (AI) driven call center analytics technology has made significant strides in recent years, both in terms of being more helpful to consumers as well as companies.

On the consumer side, pressing choice-limited buttons has been replaced by conversational AI technology, improving customer experience. Consumers can now find answers to common questions using natural language much faster than remaining on hold for long periods of time. According to a Harris Poll, business executives have replaced cost-cutting with an improved customer experience as the first reason to invest in conversational AI.

On the business side, AI technology allows companies to not only divert basic, easy-to-answer questions to an automated solution but also to collect a vast amount of data that can provide actionable analytics and insights for continuous improvement and new business development.

How can real-time analytics help my call center?

Real-time and predictive analytics can provide deep insights into everything that happens on a call. An effective conversational AI analytics tool should analyze call disposition, generate tags for conversation turns and events, and produce transcripts of every call. All of this data provides the business with opportunities to improve customer service.

How can analytics improve call center procedures?

A good dashboard should show opportunities like the percentage of calls that present upselling potential, or the percentage of calls that are being abandoned and the reasons why. These trends can present opportunities to optimize call flows, which, in turn, increases customer satisfaction.

Do conversational AI records contain sensitive customer data?

Although consumers are willing to share more personal data than ever in order to have a customized experience with businesses today, the question of security and sensitive information is an important one.

As you consider AI-driven solutions for call center operations, be sure you choose one that is compliant with both the Health Insurance Portability and Accountability Act (HIPAA) and the Payment Card Industry (PCI). Logged transcripts of customer-based data should automatically redact sensitive information like credit card numbers.

What are the benefits of conversational AI?

By collecting business intelligence data from AI-driven call center technology, businesses can gain real time insights and easily review and improve call performance. AI systems should be machine learning continuously, and every call flow can be compared by building in A/B testing to optimize the efficiency of how requests are handled.

Conversational AI doesn’t just automate and resolve customer phone calls, it provides unparalleled insights into customer behavior. According to GetVOIP, a cloud communication advisor, there is a 61 percent improvement in customer satisfaction in companies that combine AI with human interaction. By using call center analytics, businesses can better view and analyze customer needs through regularly generated reports that will track key performance indicators and resolve issues that are causing longer handle times. 

Conclusion

Data and analytics is what drives artificial intelligence to provide meaningful customer experiences. The right solution can help businesses scale up quickly. Learn more about how fast and accurate our conversational AI solutions are.