Empowering Call Centers with AI-Based Automation and Analytics

call center artificial intelligence

Empowering Call Centers with AI-Based Automation and Analytics

As customer expectations continue to increase, businesses look for effective ways to improve customer satisfaction with minimum costs. AI technology arises as an effective solution to ensure self- service automation and accurate data analytics. When implemented in self-service applications, AI technology enhances customer experience while minimizing costs. The same technology contributes to objective performance evaluation and accurate decision making through analytics. Both applications boost call center efficiency and contribute to overall business effectiveness.

How to build AI-based automation in call centers?

Conversational AI is the answer. This technology uses natural language processing to enable a natural dialog between humans and machines. It transforms any system into a voice-driven one and allows users to interact with simply by having a conversation.

Conversational AI has two basic forms: IVR bots (conversational IVR systems) and chatbots. These systems interact with users through a voice user interface which means a practical use and enhanced user experience. Call centers can choose among these technologies to answer various business needs such as higher automation, higher customer satisfaction, and decreased costs.  In some cases, combining these technologies through an omnichannel approach can offer better results.

Conversational IVR Systems

When implemented in IVR systems, conversational AI transforms touch-tone menu navigation into a voice-based version. Users can reach the right menu by stating their needs in plain language instead of dealing with complicated menu options.  In other words, the technology lets customers speak to businesses in their own words. This allows for friendly automated customer self-service. In addition to increasing customer satisfaction, the technology offers a consistent omnichannel self-service experience, increases customer service efficiency and boosts brand perception.

Sestek offers a conversational IVR solution that differentiates with its state-of-the-art features. Sestek Speech Enabled IVR not only ensures a smooth customer experience through human-like dialog; but also provides a practical use for the organization thanks to its easy-to-use structure. For example, with intent recognition feature, customers don’t need to repeat themselves. Because this feature understands the meaning behind customer queries with high accuracy. The solution simplifies organizational tasks too. With its user-friendly interface, businesses can easily design their conversation tree from start to finish.

With Sestek Speech Enabled IVR, TEB BNP Paribas Joint Venture achieved  5% increase in IVR completion rates, resulting in annual savings of $250,000. The same solution helped Garanti Pension to reach 82% of IVR completion rate for self-service calls.

Conversational AI Bots

Conversational AI bots, as known as chatbots are being increasingly used in customer services. NLP-based chatbots differ from basic FAQ bots thanks to their ability to understand and interpret meaning. These chatbots enable a human-like interaction by allowing customers to solve problems with their own words.

Chatbots contribute to call center efficiency by automating routine customer service tasks with self-service. Higher automation decreases operational costs by lightening the workload of contact center agents. Since customers can accomplish tasks easily by interacting with a chatbot, call center agents have fewer calls. This allows agents to focus on more important tasks and increase their motivation.

Sestek offers an NLP-based conversational AI bot: Sestek Chatbot. This solution ensures a personalized customer experience by allowing businesses to design tailor-made dialogs for each customer segment.

Sestek Chatbot can interpret both textual and vocal input. So, customers can interact with Sestek Chatbot via speech or text messages. Sestek Chatbot contributes to business efficiency thanks to its high-tech features. For example, named-entity recognition feature automatically tags dynamic fields in the script and saves businesses from losing time with defining customer service fields like dates, credit card numbers and more.

AI-based Analytics

One of the biggest concerns of call centers is quality management.  To ensure the efficiency of a call center, following an accurate quality evaluation process is a must. The only way to adopt a sustainable performance is to apply an objective analysis.

Many organizations accomplish this by using speech analytics software. Speech analytics transcribes recorded interactions and analyzes them by applying textual and emotional analysis. The technology has different use cases including call center monitoring and reporting, agent performance analysis and training, customer satisfaction and service quality analysis, automation of quality monitoring processes, and competition, market and campaign feedback analysis.

With the advancements in artificial intelligence and machine learning, speech analytics is transforming into an AI-powered solution. With features like sentiment analysis, emotion detection, topic categorization, real-time analysis, and predictive modeling, AI-powered speech analytics solutions identify customer sentiments and offer prescriptive insights. These insights contribute to call center efficiency by improving customer experience and sales effectiveness.

AI-based speech analytics helps organizations to:

  • Extract an unprecedented level of business insight from customer conversations
  • Identify customer sentiments and problems to improve customer experience
  • Get prescriptive insights to increase sales and drive growth
  • Quantify the impact of new trends and issues that arise
  • Gain competitive advantage

Sestek Speech Analytics has an NLP-based AI technology which combines deep neural network and machine learning. A supervised neural network is used in post-call and real-time speech analytics application, speech recognition, and emotion detection. Sestek Speech Analytics also offers an AI module which uses tagged calls as training data. Once trained, the system acts as a predictive analytics solution that assists on issues like fraud, churn, collection, and sales.

Conclusion

Today’s customers expect immediate and convenient services. This requires businesses to balance enhanced customer services with minimized costs which is possible with self-service automation. When implemented in call centers, conversational AI improves customer experience by allowing human-like natural dialog. By offering a practical self-service, the technology not only improves customer experience but also increases cost savings due to automation.

Ensuring continuous success requires continuous and accurate performance evaluation. This is where AI-based analytics steps in. By automating the insight generation process, AI-based analytics contributes to business efficiency through evidence-based decision making and process optimization.

Learn More

Sestek was named an RPA vendor working with CSPs in Gartner’s “Maximizing Value from Analytics, AI and Automation in CSP Contact Centers” report. Read the report (subscription may be required).

Gartner, Market Trends: Maximizing Value From Analytics, Artificial Intelligence and Automation in CSP Contact Center, Charlotte Patrick, Ed Thompson, Olive Huang, 23 August 2018.

Author Hilal Bakanay

Senior Marketing Specialist, Sestek https://www.linkedin.com/in/hilalbakanay/

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