How AI and Speech Analytics Can Improve Customer Experience

by | May 22, 2020 | Call Center Analytics, Contact Center Technology

Artificial intelligence is present in virtually every industry now, and contact centers are no exception. Although it isn’t perfect, people can use this technology to enhance or facilitate their daily work. In addition to its learning and predictive capabilities, AI also augments the customer experience when combined with speech analytics.

AI systems identify positive and negative behavior and make suggestions for improvement. Using AI and speech analytics benefits your company by engaging your customers. It monitors the conversation to detect anomalies and facilitates information and feedback exchange between them.

Ways to Use Speech Analytics

Speech analytics gives business owners insight into the quality and content of inbound and outbound calls. The technology goes over the conversations that your agents have with customers and “learns” over time. The more calls analyzed, the more accurate and efficient the analytics become.

Speech analytics also help with:

  • Improving call quality: Speech analytics identify which words and speech patterns result in favorable outcomes with the client. Speech analytics allows your agents to adjust their speaking style to get the best results.
  • Gauging levels of satisfaction: By recognizing tone, phrases, pauses, and other patterns, speech analytics helps companies gauge how happy their customers are with the service provided.
  • Identifying customers at risk of leaving: Speech analytics identify patterns indicating a customer is at risk of losing interest. It allows companies to re-target them and representatives to approach them with the intent of re-generating interest.
  • Pinpointing receptiveness: Speech analytics helps business owners and marketers see how receptive people are to their messages. Based on the reactions, reps can make adjustments if the initial approach isn’t leading to conversions.
  • Identifying common questions: By assessing thousands of calls, speech analytics help pinpoint the most common queries that your customers have. It also determines what products or services get the most complaints.
  • Highlighting positive and negative agent behavior: Speech analytics identify patterns of speech from your representatives as well. In addition to other technology, it shows you which representatives are high performers, and which need training.

That’s great but how does it work?

AI improves the efficiency of speech analytics because it learns from conversations while making real-time suggestions. It removes the guesswork from interactions and gives your agents support if they receive unusual or complex requests.

Consistent Learning

AI continually learns and updates, recognizing patterns of speech and emotions as they evolve with time. This process helps your company stay relevant because the speech strategy of your reps can change in real-time based on AI analysis suggestions.

Increasing Productivity

AI decreases the effort that your call center agents exert overall, and lets them perform more efficiently. For example, having a customer go through an automated AI system narrows down options for customers. It performs tasks instead of the agent in some cases, freeing them for more complex issues that need human intervention.

Virtual Assistance

A virtual assistant for callers gives them answers to common queries and makes announcements as well. Another useful application of AI is that it makes suggestions.

While the call is ongoing, the AI technology makes keyword suggestions based on the conversation history. These suggestions are useful when the representative faces a question they have trouble answering.

Real-time Suggestions

AI enhances the listening process, as you have the power of humans and technology to analyze the speech.

Since most customers call support services with negative emotions, such as aggression and irritation, AI analyzes the words and phrases the customer uses. Then, it generates real-time suggestions to the agent to decrease that aggression.

Monitoring Quality Assurance in Call Centers

Using the power of speech analytics and AI technology, call center solutions can now identify customer satisfaction levels and spot quality issues with customer conversations. Since the technology sifts through large volumes of call data and conversations, patterns can indicate that something is wrong.

  • Pinpoints emotional changes: AI and speech analytics assess the tone of your callers in addition to the statements they make. It highlights emotional changes and can tell what emotions your customers and agents exhibit.
  • Indirect feedback assessment: Not all customers provide feedback. With AI technology, the system identifies how customers feel in all phases of the call based on input, such as tone, pitch, words, and speech patterns.
  • Monitoring pauses: Long pauses and silence from either the customer or the agent are not a good sign. Common reasons include an agent not having the answer to a caller’s question, or an unhappy client. By monitoring pauses, the AI system and speech analytics detect pauses and silences and generate recommendations based on the conversation.
  • Identifying solutions: When a query results in an adequate resolution that satisfies the customer, the AI system takes note. Over time, it identifies the most common questions and publishes suggested responses based on previous calls and their success rate.
  • Maintaining engagement and experience: As AI “learns” from your calls, it starts to identify patterns in individual client behavior. The system then alerts the agent when a customer’s response is changing and when interest wanes from the company’s product or service.

The power of AI and speech analytics means more efficient call center processes and happier customers. By identifying patterns and deviations, these systems provide call center employees and managers with tools to enhance their work processes.

AI and speech analytics are already an indispensable part of the call center landscape. Although they are not fool-proof and need human intervention, it is exciting to see what this technology will bring to businesses in the future.

Jessica Johnson
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