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Better Automation Makes Better Agents

Better Automation Makes Better Agents

/ Technology, Artificial Intelligence
Better Automation Makes Better Agents

How emerging new technologies enable agents to perform their best.

If you’ve ever called customer service to dispute a bill, cancel a service, or return an item, there’s a chance the conversation could end in frustration.

If it did, your first instinct might have been to blame the agent, but it may not have been the agent’s fault. Maybe the agent just didn’t have the organizational support needed to resolve your issue quickly and completely, and to also make you feel like a valued customer at the same time.

Consumers’ demand for both efficiency and reassurance in these situations is often difficult to satisfy. But new automation tools based on artificial intelligence (AI) are boosting efficiency and, by extension, empowering human agents to bring more of the empathy, flexibility, and judgment that leaves customers feeling understood and valued. That can only be good for the bottom line.

To be clear, I believe that concerns about unanticipated consequences from groundbreaking technologies like ChatGPT are legitimate. But in the contact center, I’m convinced that the impact of emerging automation technology will be overwhelmingly positive.

These tools will bring much-needed efficiency by taking over execution of simple transactional requests, streamlining delivery of training and other agent development functions, and providing more responsive in-call support. That will free agents to focus more attention on the uniquely human skills that are so essential to positive customer service experiences.

Humans at the Wheel, Technology Under the Hood

The “human touch” is at the core of customer service. No matter how fast and smart technology becomes, it’s still unlikely to be a satisfying substitute for a human-to-human connection in high-stakes interactions.

The only thing most of us will tolerate less than an inefficient customer service agent is not being able to reach one at all. We long for efficiency but at the same time we’re wary of technology taking over too much of how we experience customer service.

In fact, automation technology is already deeply embedded in the process - from IVR systems that distribute calls - to automated customer service follow-up surveys that register our level of satisfaction.

Automation of these and other processes has streamlined contact center workflow efficiency, but it hasn’t improved agents’ ability to satisfy customers once they’re connected.

That’s because the agent’s job entails handling calls directly and also processing and interpreting the data needed to resolve the caller’s issue. That takes time and stretches agents thin, and as expanding processing capabilities make data more accessible, the limits of human processing efficiency have become more glaring.

These tools...will free agents to focus more attention on the uniquely human skills that are so essential...

In a fraction of the time required by a human agent, AI can process massive amounts of data to identify relevant patterns and predict the best path to solving whatever issue is at hand.

By removing a major source of inefficiency in the process, automation produces a dual benefit. One, faster problem resolution by rapidly placing critical information at the agent’s disposal. Two, agents will have more capacity to bring empathy and nuanced judgment to customer interactions because they no longer need to process as much background information.

Tackling Problems at the Source

One of the benefits of today’s new generation of automation technology is its unique ability to identify and prevent many of the back-office inefficiencies that add complexity to customer service inquiries. This is true for contact centers serving retailers as well as financial institutions, healthcare or insurance groups, government service providers, and other organizations with large customer service centers.

By leveraging AI technologies such as machine learning (ML), natural language processing (NLP), and predictive analytics, organizations can glean valuable insights from customer data. They can then implement proactive measures to bypass traditional sources of confusion and frustration for both agents and customers.

By analyzing customer interactions, transaction history, and feedback, AI algorithms can detect and solve recurring sources of dissatisfaction. For example, if AI algorithms detect a significant number of customers asking the same question or experiencing the same technical issue, they can alert the organization to investigate and address the problem before it escalates further.

By identifying negative sentiments and potential issues early on, companies can take preemptive action to address and prevent customer complaints.

In addition, advanced NLP capabilities enable chatbots to decipher and respond to common transactional customer inquiries and resolve them without the need for human intervention.

These chatbots can ensure consistent and accurate responses across various channels, including websites, social media, and other messaging platforms. This accelerates the pace of problem solving and relieves some of the pressure on contact center managers to allocate precious human resources to staff the expanding list of customer service access channels.

New AI-powered technologies can also leverage predictive analytics to anticipate the needs and preferences of retail customers, for example, and enable businesses to take proactive measures to offer better post-purchase customer service.

By analyzing historical data, AI algorithms can identify patterns and make predictions about future customer behavior. For instance, the technology can anticipate when a customer is likely to require assistance based on their browsing patterns, previous transactions, or engagement history.

By reaching out to customers before they encounter problems, businesses can offer personalized support, recommend relevant products or services, or provide preemptive solutions. All of which can reduce the need for or at least the complexity of customer service intervention.

Sentiment analysis, another AI-powered technique, can monitor and analyze customer feedback as well as social media posts and online reviews to gauge customer satisfaction levels.

By identifying negative sentiments and potential issues early on, companies can take preemptive action to address and prevent customer complaints. This proactive approach not only helps in preventing problems but also enhances overall customer experience (CX) and loyalty. Embracing AI in customer service can help create more efficient and effective support systems and provide a more seamless CX.

Learn From the Past…

The emergence of ChatGPT and other new AI tools represents an exciting new phase in the capacity of technology to reshape the world we live in. Things are moving quickly, and businesses need to think now about how they can harness the power of AI within their own customer service operations to improve performance beyond what basic process automation has long made possible.

That said, customer service organizations need to avoid the mistake made with early chatbots, which were falsely presumed to be simple replacements for human agents.

The Wall Street Journal posted an article demonstrating the potential “people versus machines” conflict lurking just below the surface. It reported that some call centers are using AI models to remove decision-making responsibility from agents by scanning conversations and recommending precise agent responses based on words and sentiments expressed by customers.

Businesses must make plans to leverage new technologies to remain competitive...

Agents interviewed for the article said they valued AI’s ability to help them make better decisions by accessing information quickly, but they objected to being required to use AI-generated scripts against their own judgment.

“’It’s hard for robots with no emotions to judge how a call is going,’” said one agent. Another joked that he and his colleagues were “’taking up a collection to get a hearing aid’” for the AI assistant deployed in their contact center, which has been prone to mistakes.

Technology in the Service of Humans

The business climate remains fragile in the wake of major recent disruptions caused by the COVID-19 pandemic, supply chain issues, inflation, and geopolitical uncertainty. Businesses must make plans to leverage new technologies to remain competitive, while at the same time making contingency plans for economic recession, which may or may not be just ahead.

The labor market also remains relatively tight, and businesses are still obliged to attract workers with promises of greater job satisfaction and work-life balance.

Contact center leaders that adopt intelligent automation will be better positioned to deliver on those promises, and more likely to attract high quality employees. For maximum advantage, they must deploy today’s powerful new technologies to help make their live agents better customer servants.

Matt McConnell

Matt McConnell

Matt McConnell is Chairman and CEO of Intradiem. He founded the company in 1995 with a vision of reinventing customer service through automation and AI. Today, Intradiem is the leading provider of intelligent automation solutions for customer service teams. Matt graduated from The Georgia Institute of Technology with a Bachelor of Science degree in Industrial and Systems Engineering.

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