Types of Agent Augmentation You Should Know

What are the different types of Agent Augmentation?

5
Types Agent Augmentation Should Know
Contact Center

Published: September 27, 2019

Rebekah Carter

Contact centre agents are under a lot of pressure these days.

Increasingly, to make the customer service environment more efficient, businesses are automating many common interactions. For instance, consumers can speak to a chatbot or use self-service FAQs to answer common questions, which means less pressure placed on today’s agents.

However, on the other hand, because the simple work is automated, that means that agents are spending more of their time handling complex queries and in-depth customer issues. Since today’s customers expect their service interactions to be more personalised, efficient, and impressive than ever before, agents have a lot to live up to.

Fortunately, for employees that need to be available to delight customers on a multitude of different platforms, there are solutions available in the form of agent augmentation.

Agent augmentation connects your workforce with the latest in artificial intelligence, machine learning, and natural language processing, to help them perform their tasks more effectively.

So, what are the kinds of agent augmentation available?

Type 1: Systems for Reducing Repetitive Work

If you want your agents to spend more of their time focusing on high-value interactions and complex queries, then the first thing you’ll need to do is cut down their number of mundane, repetitive tasks. One of the best ways to do this, is with chatbots.

Chatbots are a common part of the customer experience narrative today. It’s hard to find a consumer that hasn’t had at least one conversation with a  chatbot or virtual assistant. These tools, when used correctly, can act as a kind of immersive FAQ system, helping customers to serve themselves before they seek assistance from a human agent.

For instance, software brand Autodesk implemented a chatbot called Autodesk to respond to customer questions posed in natural language. This solution is available 24/7, so customer can access the help they need at any time. According to case studies, AVA reduced resolution times for Autodesk customers by 99% and improved customer satisfaction rates by 10 points.

Type 2: Intelligent Call Routing

Another way to augment your agents in today’s modern marketplace, is to make sure that they’re only dealing with the interactions that are most relevant to their skills and talents. When you’re trying to solve customer queries quickly, it may seem like a good idea to push calls through to the first available agent. However, if this agent needs to transfer a call to someone else because they don’t have the right specialist knowledge to serve a customer, satisfaction levels decrease.

Customers don’t want to be passed around from one employee to the next. Additionally, agents don’t want to waste their time addressing issues that aren’t suited to their skills. An intelligent routing system will improve the chances that your customers will reach the right agent the first time around. If the correct person isn’t available to answer their call, you could even implement an automated “call back” system in your contact centre.

This means that instead of waiting around for someone to answer the phone, your customer can opt to have their number dialled automatically when the right agent becomes available.

Type 3: Predictive and Automated Diallers

Speaking of intelligent dialling solutions, it’s also possible to augment and support your contact centre agents by giving them access to predictive and automated dialling solutions. This saves crucial agent time as the dialler will be able to detect things like busy signals and disconnected phone numbers.

Predictive dialling is now available not just in the audio communication industry, but over social media, chat, and texting too. The right system can detect a customer’s channel of choice and deliver interactions straight to an agent when a customer actions. This system can also be a great way to provide customers with proactive outreach in the case of an emergency or issue. Like automatic call distribution systems and intelligent IVR, predictive and automated diallers increase the chances that the right people will be connected first time around.

If your contact centre doesn’t just deal with inbound calls, these diallers could be a powerful way to make sure that you’re getting the most value out of every call.

Type 4: Virtual Assistants

Now that today’s contact centre agents are under more pressure than ever to deliver quick and personalised experiences to customers, they need some extra help. As great as bots and artificial intelligence might be, your consumers don’t want to interact with bots alone. They still want the human touch of a real-life agent. Fortunately, hybrid AI systems where agents are assisted by their robotic counterparts can create a more efficient contact centre.

Virtual assistants with access to back-end data like CRM information and customer contact details can offer agents plenty of useful contextual information to help them transform their conversations with clients. For instance, before an agent is given a call to answer, a virtual bot could surface information about the customer’s previous discussions with agents, their name and background, and the products that they’ve purchased.

Not only does access to this contextual information mean that agents can provide a more personalised experience straight away, but it also helps professionals to decide when they need assistance from a specialist too. If the query requires additional insight, the agent can immediately contact someone else on their team using a collaboration tool to get extra help.

Virtual agents can even offer tips and insights as the conversation progresses, while analysing things like customer sentiment to track the performance of a discussion.

Type 5: Enhanced Analytics for Training

Finally, the automated systems and intelligent tools in the contact centre can also help to make agents more efficient and effective over time. For instance, as AI virtual assistants continue to gather information about conversations from agents, they can deliver that data to supervisors to help them see where the team needs additional training and support.

As the contact centre environment continues to spread across multiple channels, analytics are becoming crucial to ensure that businesses know how to properly serve their customers. Through in-depth insights into the conversations that agents have every day, supervisors can set up training systems that make advisors more effective over time. What’s more, they can gain insights into the kind of tools that are helping the contact centre agent to be more productive.

In the complex customer service environment, the more information we have, the easier it is to evolve to suit the ever-growing needs of consumers.

 

Artificial IntelligenceChatbotsInteractive Voice ResponseVirtual Assistant
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