AI-Powered Speech Analytics: Is the AI Overlord Taking Over the Contact Center?

AI-powered speech analytics provides contact centers with real-time customer insights. As a result, supervisors and agents can understand and respond to customer needs. 

Even so, AI in the contact center is just starting. By 2022, AI-enabled agents will handle 20 percent of all customer service requests. Indeed, contact center leadership cites customer experience (CX) as the main reason for investing in AI. 

Here’s how AI-powered speech analytics is helping revamp the contact center and redefine CX. 

The Promise of AI-Powered Speech Analytics

1. Automation

AI can help organizations to automate simple and repetitive tasks in an expedited manner. In essence, speech analytics tools transcribe, translate, and analyze each customer interaction and automate repetitive tasks for the agent. The tools can identify negative sentiments on calls and escalate critical issues with an e-mail or SMS alert to a supervisor in real-time, log a ticket into your CRM system or invoke rest API to log events into your backend database. This way, agents can resolve problems faster and focus on delighting the customers.

2. Discovery

Previously, some hidden business rules, such as data patterns in large contact centers, would go under the radar because of sampling analysis. Using AI to process data from billions of interactions makes it easier to extract actionable insights that optimize agents and drive predictive recommendations. Overall, AI makes the contact center more efficient.

3. Improvement of Prediction Models

Most contact centers have prediction models in place that help improve efficiency. But traditional measures that relied on surveys don’t provide the complete CX picture. A disgruntled customer is unlikely to respond to a survey. As a result, management may never know why he or she walked out the door.

Speech analytics allows organizations to capture emotions, keywords, themes, and phrases from conversations. As a result, management can predict and anticipate customer needs and pain points. Even it can replace post-call surveys.

4. Prescription

Organizations can empower agents with AI guidance to recognize patterns in real-time and suggest the best actions to help resolve customer issues faster.

5. Alerts

Contact centers are continually accumulating and processing enormous volumes of data. When something goes wrong, AI-powered speech analytics can send an alert about the issue. Identifying agent errors in real-time can help reduce both long- and short-term training efforts.

6. Data Lakes

An Aberdeen survey concluded that enterprises with a data lake outperform similar companies by 9 percent in growth revenue. Harnessing the power of data lakes allows organizations to utilize more data quickly, leading to faster decision-making. Consequently, enterprises can improve customer interactions and increase operational efficiency. 

Intelligent speech analytics tools stream results from departmental silos directly into a customer data lake. As a result, organizations can identify sales optimization opportunities and improve self-service. 

7. Optimization

Organizations can use AI-powered speech analytics to optimize the metrics that define the contact center’s day-to-day performance. As an illustration, management can improve customer satisfaction by eliminating search and browsing tasks by agents. Hence, organizations reduce agents’ stress and boost their productivity.

8. Virtual Assistance

AI-powered speech analytics can discover the most common use cases to build the virtual assistance bot and bring additional automation opportunities. 

9. Knowledge Management

Transcriptions, interaction metadata by tagging with the best resolution can be leveraged as Knowledge Management and training agents.

Visibility, Insight, and Integration with the Contact Center 

AI-powered speech analytics tools analyze every customer interaction across the customer journey. This gives 100 percent visibility into all omnichannel interactions in the contact center. As a result, leaders can uncover insights that affect both the agent and the customer.

AI and machine learning go beyond basic metrics and KPIs by providing analytics insights to identify areas where organizations can improve. Integration with back-office and CRM systems allows contact center software to access customer information to provide intelligent self-service experiences. 

Conclusion

AI is taking contact centers to the next level by working with agents, not replacing them. Contact centers can take advantage of AI-powered speech analytics to make better decisions from every sale, service, or conversation. Leveraging AI-powered Speech Analytics, Enterprises can reap significant benefits by realizing the hidden value in the massive amounts of caller-agent audio recordings from their contact centers. By deriving meaningful insights, enterprises can enhance both efficiency and performance of call centers and improve their overall service quality to end customers.

SuccessKPI provides out-of-box integration with Amazon Connect, Genesys Cloud, and UJET based contact center platforms with integrated speech & text analytics and Quality Monitoring tools to give organizations a 360-degree view of the contact center. SuccessKPI SaaS platform achieved PCI-DSS Level 1, SOC 2, Type 2, HIPAA Compliant with BAA support through 3rd party Auditors. Find out more here: Speech and Text Analytics.

In my next blog post, I will discuss how SuccessKPI has been using advanced features to optimize transcription costs, supporting global languages, and redaction for PII data.