Conversational AI in Call Centers: Resolving the 5 Biggest Bloopers

Customer experience is a key differentiator in almost every vertical, and AI in call centers can be a big part of achieving that. Extraordinary customer service can make you stand out from the competition – and keep your profit margins healthy too.

Gladly’s Customer Expectations Report found that 62% of customers will recommend a brand because of its great service, and according to Salesforce, 88% say that customer experience is just as important as the company’s products or services. This makes call centers one of the most critical areas of your business.

You need agents who are efficient and empathic, able to establish a relationship with the customer while quickly resolving their issue. Unfortunately, too many call centers see the same mistakes arise again and again, harming the customer experience.

The rise of AI in call centers, though, could change all that and bring excellent CX back to your organization.

5 biggest bloopers of call centers

Many call centers see the same common bloopers recurring on a frequent basis, like agents who sound unconcerned about the customer’s issues and aren’t able to resolve them efficiently. Here are the 5 main errors that call center agents make and which deter customers from returning.

1. Reading from a script

Scripted customer interactions can hold agents back from truly listening to customers and responding to their real concerns. It limits the agent’s ability to actively listen and adapt responses appropriately, leading to frustration and dissatisfaction among customers.

Even if your organization does require agents to follow a script, you don’t want that to sound obvious to the caller. Robotic call agents speaking in a monotone sound like they don’t care about the caller’s needs and aren’t really paying attention.

2. Speaking without clarity

Customers rely on call center agents to communicate with them clearly and accurately. The most knowledgeable and helpful agent in the world could still cause frustration if customers have trouble understanding that agent’s speech.

When agents mumble or speak too fast, it’s difficult for the customer to follow what they’re saying. Call center agents who speak vaguely, use jargon, and don’t clearly communicate instructions or next steps can cause confusion. This damages customer experience and can harm the company’s reputation.

3. Lack of knowledge about the product or service

Customers reach out to call centers to find solutions to their questions and issues, and agents need deep knowledge to deliver those answers. If agents don’t know the answer, or give incorrect information, customers may take their business elsewhere.

What’s more, agents with weak product or service knowledge are less confident. This has a compounding effect on their ability to speak authoritatively to the customer and engender trust.

4. Poor problem-solving skills

Solid problem-solving skills are vital for call center agents. This includes capabilities like excellent listening skills, so the agent can discern a customer’s core complaint; extensive product knowledge, so they understand what might have caused the issue; and the ability to think creatively and critically under pressure, to come up with constructive solutions.

Without these skills, customers can be left with unresolved issues and unanswered complaints for extended periods of time. As their frustration grows, so does their irritation, driving up the risk of churn and negative reviews.

5. Insufficient empathy and emotional intelligence

Empathy and emotional intelligence are vital traits for call agents. It allows them to make customers feel heard and cared for, and ensures that agents remain calm and composed during difficult conversations.

When agents lack empathy, customers may feel dismissed or unimportant, even if the agent solves their problem. This can lead to a breakdown in trust and loyalty to the company and increase churn. Agents with low emotional intelligence may respond poorly to an agitated or aggressive customer, which can drive customers away. Empathy and emotional intelligence are at least as important as an agent’s ability to solve the customer’s issue.

How can AI address these call center bloopers

At a time when customer patience is low, it’s more important than ever to ensure that every call agent has the skills and product knowledge to reassure the customer and deal with their concerns. Here are 4 ways that AI in call centers can make this a reality.

1. AI can turn practice into something that agents enjoy

There’s no real replacement for an efficient, caring customer support agent, but you can use conversational AI in call centers to train more agents to this standard. Second Nature applies AI to deliver interactive, engaging, and realistic role play simulations that help agents hone their listening skills, improve their speaking tone and pace, and sharpen their problem solving abilities.

When agents enjoy practicing customer calls, they’ll practice longer and more often, which inevitably strengthens their skills for the real call.

2. AI can shorten time to case resolution

There are many ways that AI tools can help agents resolve customer inquiries more quickly. For a start, AI chatbots can handle many routine inquiries, which gives agents more time to focus on more complex issues and lowers overall call-handling times.

AI analytics can understand customer queries faster than humans can, and deliver accurate insights into the problem, while AI-powered knowledge systems can push relevant information in real time, which helps agents decide more quickly how to address the issue.

3. AI can power more efficient onboarding for new agents

It can take time for new agents to master the many skills needed for efficient customer support. They need to learn all about your solution, understand the primary pain points and motivations of your customer base, and strengthen their ability to forge trust relationships with customers.

AI-powered onboarding can shorten the time it takes for agents to achieve all these capabilities. AI role play partners that are available 24/7 let new hires try their call handling skills, receive instant feedback, and immediately put the advice into practice to strengthen their capabilities.

4. AI can improve agents’ accuracy and consistency

Human agents can use AI in call centers to become more accurate and consistent when responding to customer calls. When agents practice with Second Nature, the AI engine delivers reminders about key points to cover, as well as timely feedback about pace and tone. This helps them follow standardized scripts without sounding robotic.

AI-driven sentiment analysis can also help agents to better understand customer emotions, motivations, and pain points, so they can respond more appropriately.

AI in call centers can drive a new level of customer service

There’s a lot riding on the conversations that call center agents have with customers. When agents forge a trust connection with customers, understand their issues, and resolve them quickly and efficiently, it helps boost customer loyalty and strengthen your brand image.

AI in call centers brings many ways to assist agents to deliver this higher standard of service. By helping agents strengthen listening and empathy skills, improving product and service knowledge, giving feedback about the tone, pace, and clarity, and guiding agents to better ways to solve problems, AI tools like Second Nature can boost your customers’ experience and bolster your brand reputation.

FAQs

Will AI completely replace human agents in call centers?

It’s hard to predict the future, but we think it’s unlikely to completely replace humans. Ultimately, people prefer support from other humans, especially for complex issues. AI can’t replace the empathy and understanding that a human call agent can deliver.

But AI can help humans to give better service. AI chatbots, automated call routing, AI customer insights, and AI call center training can all play their part in improving the CX that customers enjoy.

How can call centers ensure a successful implementation of AI technology?

Successfully implementing AI in call centers requires a strategic approach. Call centers need to begin by assessing existing processes to find areas where AI could add the most value, like by automating repetitive tasks.

Then they need to invest in the AI platforms that align best with their needs, and train and upskill call center agents to use new AI tools effectively. It’s best to introduce AI systems gradually, and establish regular monitoring and feedback loops to quickly spot and address any issues as they arise.

Finally, it’s vital to maintain a customer-centric focus, so that AI enhances human interactions rather than replacing them.

Will AI impact employment opportunities for call center agents?

As AI technologies get better and better, it’s likely that they’ll take over more of the routine tasks that call center agents currently have to do, like answering simple customer inquiries and providing basic information. This could lead to fewer openings for unskilled call center agents.

But new opportunities are likely to emerge for agents with higher level skills, like dealing with complex customer issues, providing specialized support in sensitive fields, and managing AI tools for customer support.

In the long run, the impact of AI on employment opportunities for call center agents will depend on how organizations integrate AI into their workflows. Companies with effective upskilling and reskilling programs will be able to retain their experienced agents and tap into the benefits of AI.

Are there any privacy concerns associated with AI in call centers?

It’s important to be aware of the privacy risks of using AI in call centers, so you can take steps to ensure customer privacy. You’ll typically need vast amounts of customer data to train AI technologies, so make sure this doesn’t compromise data security or privacy regulations like GDPR.

Call centers should be transparent with customers about their use of AI, and make sure to get the appropriate consent for data collection and processing. At the same time, organizations need to put robust security measures in place to protect customer data and reduce the risk of data breaches.