Why call center automation needs voice AI

What’s the best way to manage calls without driving up costs or impacting service quality? Call center automation, or a “conversational AI voice bot.” 

Powered by machine learning (ML) and Natural Language Understanding (NLU), call center automation gives customers a more conversational experience, with the freedom to respond how they want instead of being trapped in a rigid menu. But not all call center automation is created equally.

If you’ve ever picked up the phone to call customer service (and we know you have), chances are you’ve encountered an interactive voice response (IVR) system —  the most basic and quite frankly, outdated, form of call center automation. It’s just as likely that you’ve had a frustrating experience with one, too. 

Despite migration to digital channels in recent years, voice is still the most popular support channel — making it essential for customer service leaders. But with rising call volumes, many companies are looking to technology to shoulder some of the burden. 

Let’s look at the difference between traditional IVR, a conversational AI voice bot, and call center automation so you can make the right investment for your business.  

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What is call center automation?

Call center automation uses technology to carry out repetitive, labor-intensive processes and tasks. It significantly lowers the requirement for human intervention.

IVR: An early approach to call center automation

The landline was the original customer service channel. In fact, not so long ago it was the only way consumers could contact companies outside of a brick-and-mortar store. IVRs were developed to help companies increase call center efficiency by collecting information from callers and routing them to the right agent or department.

IVR is an automated system that uses a phone-tree framework to gather information about why a customer is calling and potentially let them take action, such as paying a bill, or be routed to an agent. You know how these calls go: “For A, say ‘A’ or press 1. For B, say ‘B’ or press 2…” and so on. To get where they need to go, callers have to work their way through the menu by providing pre-set responses. 

An IVR system is usually paired with other call center software like automatic call distribution (ACD), which routes incoming calls to the best department or agent, depending on a caller’s need. Routing to the right agent the first time is critical for brands, because customers really don’t like getting bounced around. 

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The downside of IVR

The biggest issue with old-school IVRs is that they’re not designed to truly resolve customer issues; they’re better suited to gather information about intent and route calls to the right place. And while that matters, it’s not enough for today’s independent customers who expect to be able to self-serve for most issues. Rather than helping them get what they need, callers often see the IVR as standing in their way.

Legacy IVRs don’t use NLU technology to discern what callers are saying. They use voice recognition, but it’s limited on its own and the caller’s response has to match the menu tree-based system, which can follow a long, maze-like path, adding to frustration. 

If a caller’s need isn’t addressed in the menu or the system doesn’t understand them, they can get stuck waiting on hold or be bounced around between departments. Callers often resort to dialing zero to try and bypass the system and reach an agent. This phenomenon, known as “zeroing out,” shows that customers see the IVR as being difficult to use and time consuming, without actually helping them reach resolution.

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In addition to being complicated for customers to navigate, traditional IVR systems can be complex on the back end. Many are clunky and difficult to set up, typically requiring a heavy lift on the part of IT teams. Poor integration capabilities often prevent customers from doing anything beyond providing information. And when they do finally reach an agent, the customer often has to start over and explain why they’re calling. With today’s higher customer expectations, and shorter patience, this leads to frustration that can impact a brand’s reputation, and the bottom line. 

Conversational AI voice bots: The next step in call center automation

Unlike legacy systems, conversational voice AI is driven by ML and NLU. By combining NLU with automatic speech recognition (ASR), these voice bots are able to recognize callers and understand what they’re saying, giving them the freedom to use everyday language. Making conversations feel more natural and human-like immediately improves the customer experience. Better understanding also leads to higher resolution and containment rates, boosting CSAT and efficiency.

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Unlike legacy systems, this next generation of conversational AI voice bots can be easier to integrate with core business systems such as a customer relationship management (CRM) or order management system (OMS), as well as other customer support tools, making it possible to personalize the experience and automate actions over the phone. This is a giant leap forward, as today’s customers expect to be able to get things done by themselves — not just get through the menu. 

Another key advantage is that AI and ML have the ability to continually learn and optimize in ways that traditional IVR tools simply can’t. This not only improves recognition and resolution rates, it identifies improvements and other automation opportunities, compounding business value over time.

How to apply conversational AI across the call center

Call center automation can be used to enhance efficiency on the front end as well as behind the scenes, and can be deployed in a number of ways. 

On customer-facing channels, including messaging and voice, conversational AI bots can automate self-service interactions. With a robust automation platform, integration with third-party tools allows for automation of additional processes, making it easier for customers to resolve inquiries themselves. Automation can also help to reduce long wait times by facilitating call backs so customers don’t have to wait on hold. 

Automation is a valuable tool for agents, too, improving performance and resolution.

When integrated with core systems, conversational AI can help agents serve customers better by providing information about preferences, past purchases, and other relevant data. 

Conversational AI can even collect customer information up front and pass it along to the agent when a conversation is escalated, reducing average handle time (AHT) and making the agent’s job easier. A smooth, contextual handoff also reduces customer effort by not making them repeat themselves. 

With the right vendor, conversational AI can be deployed across channels, including chat, voice, SMS, and social media. This allows brands to increase Automated Resolution and decrease AHT. Plus, companies can create seamless experiences across channels. 

The benefits of a conversational AI voice bot

Happier customers

We all know that customers today expect a lot. They want to get what they need as fast as possible with the least amount of effort. Conversational AI makes it possible for more customers to resolve their issues quickly and easily, without waiting to speak with an agent.

Happier agents

Working in a call center isn’t always easy — or rewarding. High volumes and repetitive tasks lead to frequent burnout and high turnover — 42% in 2021, according to one study. Another study found that 74% of contact center agents are at risk of burnout. 

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Not only is this bad for morale, it’s bad for business. Frustrated agents are less likely to provide top-quality service. Plus, the cost of hiring and training new agents can be up to double the cost of retaining an existing agent. So making life easier for agents isn’t just the right thing to do, it’s also a smart business strategy.

Increasing self-service lightens the load on agents by decreasing their call volumes. And automating the most common tasks and inquiries relieves them of the repetitive work that quickly becomes mundane, freeing them up to focus on more valuable and rewarding work instead.

Lower costs

Call center automation helps brands manage rising call volumes as well as the spikes that occur around special events like Black Friday/Cyber Monday (BFCM), without needing to constantly increase headcount. This makes a big difference to the bottom line because agents are the most costly resource. At the same time, automation boosts agent efficiency by handling repetitive tickets, authenticating customers and passing context, and decreasing AHT.

According to Gartner, automation also lowers cost-per-interaction: “Gartner’s 2019 Customer Service and Support Leader poll identified that live channels such as phone, live chat, and email cost an average of $8.01 per contact, while self-service channels such as company-run websites and mobile apps cost about $0.10 per contact.” 

This is why many companies no longer show a phone number on their website, trying to drive customers to other lower-cost channels instead. But with voice still being the most preferred channel for customer support, that’s a short-sighted approach. By adding automation to the support lineup, companies can cater to customer preferences without driving up costs.

Greater availability

In today’s always-on world, customers expect to be able to contact a company wherever and whenever they prefer. Relying solely on live agents limits the places and channels that brands can be in, as well as the time they’re available for customers.

With call center automation, brands can meet their customers where they are and offer 24/7 support across all the channels they’re already using. This is especially critical for businesses that need to handle issues outside of regular business hours, such as travel companies, as well as those that sell across time zones and around the world. 

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Time to zero out of legacy IVR

The bottom line is this: businesses need to be where their customers are, and that means making voice available — and easy. Replacing outdated systems with modern, conversational AI voice automation shortens queues, boosts efficiency, and makes it easier for both customers and agents to resolve issues as quickly and easily as possible.

Sarah Fox
Sarah Fox

Sarah Fox is a scuba-diving, animal-loving journalist turned content marketer. In her career, she’s covered stories on development, written profiles on notable philanthropists, and interviewed celebrities with a passion for giving back. When she’s not producing content for Ada, Sarah’s likely fawning over her dog somewhere in the woods.

More info about Sarah Fox: LinkedIn

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