Boosting Contact Center Productivity With Natural Language Understanding

  • Lower Average Handling Time because the agent doesn’t need to ask a lot of questions.
  • NLU can help by recognizing categories of information like names and addresses and prompting agents to confirm and update them.
  • It frees up agents to ‘play to their strengths’. That means helping people, empathizing and being supportive.

Natural Language Understanding (NLU) has attracted a lot of interest for its role in conversational IVR service. That makes sense – interactive conversational services are a pretty exciting prospect for customer service providers. But that’s not the only application for NLU technology in the contact center. Agent productivity is another area with massive potential to benefit from NLU.

Studies have shown that agent experience improves dramatically when businesses automate tedious research and data-entry tasks.

Before we dive in – what’s Natural Language Understanding?

In short, NLU is what enables a computerized system to listen to human speech and understand what the speaker wants. Most people encounter this all the time in systems like Alexa and Siri. These days it’s not sci-fi. It’s just a part of life! It’s useful for contact centers because it streamlines their work.

Some queries can be handled 100% by an automated voice system. In other instances, the conversational system can help gather information before routing a customer to a human agent.

Other productivity benefits for contact center agents

Contact center agents can directly benefit from NLU in the workplace.

Here are just three ways we’ve seen that in action.

1. Understanding what customers want

When you think of automation in service, you probably think of it ‘replacing’ humans. In reality, automation tends to supplement human labor. Take this example: a customer calls your business about a late delivery. It’s possible for automated systems to handle 100% of the interaction, but maybe you don’t want that.

(Maybe the customer doesn’t want that either!)

But… automation still plays a part. In this case the automated system can gather information about who’s calling and what help they need. That way, when the customer is handed over to the agent, the agent already knows how to proceed.

Why is that better?

This approach makes for far lower Average Handling Time because the agent doesn’t need to ask a lot of questions. They don’t even need to look up the customer in your directory because the NLU-base system can provide it.

That might sound like it benefits your business more than it benefits the agent, right? In truth, you both win. Studies have shown that agent experience improves dramatically when businesses automate tedious research and data-entry tasks.

Basically, you need to let the computer do the heavy lifting and let agents do what they do best – having conversations and helping people. During the average customer service call, just 25% is spent interacting with the customer. The rest is spent (wasted?) on manual research.

2. Virtual assistance for staff

You’ve probably seen virtual assistants used to aid customers. But did you know that they can do the same for contact center agents? They’re especially useful for new agents. Sales staff can find this especially useful. It generally takes around ten months for a salesperson to become fully productive.

With NLU-based assistance you can bring that down to just a few months. Here are the best examples:

There are chances to upsell and cross-sell

Most businesses have only loose structuring for their upselling and cross-selling goals. NLU presents an opportunity to formalize this and can prompt agents to think about linked products. Machine learning means that NLU systems get better and better at identifying those opportunities.

You’ve probably seen virtual assistants used to aid customers. But did you know that they can do the same for contact center agents?

Upgrading your data hygiene

It’s not super exciting but data hygiene is vitally important in the contact center. In a very real sense, data is what customer service teams deal in. Data hygiene projects are almost always comprised of small incremental activities. NLU can help by recognizing categories of information like names and addresses and prompting agents to confirm and update them.

Better training for agents

There’s always a learning curve. It’s especially true for new agents, but also for existing agents as processes change over time. Step-by-step guidance through best practice processes can really help to reduce workload. Often, agents develop their own workarounds when the best approach isn’t clear. The breeds inconsistency and limits the potential of anyone who learns the ‘wrong’ way to do things

3. Reducing unnecessary contacts

Let’s take a moment to think about what productivity is. It can be a misleading concept. An office full of busy people looks productive. But if they’re all busy performing pointless tasks, they’re not productive at all! Just imagine walking around your office counting the power sockets. You’d be busy. But you wouldn’t be productive.

So when agents are ‘busy’ doing tasks that should be automated, they’re not really being that productive. Calls about resetting passwords or double checking purchase info are just a waste of time.

This is the real reason that NLU matters in the inbound contact center – it frees up agents to ‘play to their strengths’. That means helping people, empathizing and being supportive. Not only does it make your contact center more effective, it makes the work that agents do a lot more interesting and fun.

It’s vitally important that the daily grind of pointless conversations are eliminated. It improves the working day and drives down agent attrition. Luckily, NLU tech is already moving into the mainstream. Within a few years these kinds of tools will be the default in any contact center, just CRM or Helpdesk tools.

Ralf Llanasas

Ralf is a blogger and digital marketing expert. He writes anything that is related to mobile marketing, phone review and the latest technology news and he's writings can be seen in several publications aimed at IT industry.  
http://Whatphone.co.au

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