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Home Artificial Intelligence

How Artificial Intelligence Can Be Used In The Contact Center

Contributor by Contributor
February 26, 2018
in Artificial Intelligence
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In Brief
  • Technology bigwigs Mark Zuckerberg and Elon Musk even had a series of very public discussions about it recently.
  • Consumer solutions such as Apple’s Siri and Amazon’s Alexa have become certified runaway hits and are quickly changing how people interact with their personal and home...
  • But despite the growing interest around AI, a lot of people in the business industry are still wondering about what exactly can this innovation bring to...

The world has been abuzz about artificial intelligence or AI. Technology bigwigs Mark Zuckerberg and Elon Musk even had a series of very public discussions about it recently. Consumer solutions such as Apple’s Siri and Amazon’s Alexa have become certified runaway hits and are quickly changing how people interact with their personal and home devices.

But despite the growing interest around AI, a lot of people in the business industry are still wondering about what exactly can this innovation bring to the table. For instance, a lot has been said about how AI can make a huge impact on contact centers and customer service, but company owners and IT decision makers still raise many questions regarding its definitive benefits to the business process.

It’s probably because it is still a relatively new and emerging technology. There’s also a looming fear that sophisticated programs may one day reduce, if not completely replace, the workforce. In the call center industry, wherein operations are fueled by individual human operators, this poses a potential threat so it will be best to have even a general understanding of how AI technology can be implemented in contact center environments.

Predictive Analytics

Predictive analytics is a powerful tool that companies can use to gain a deeper understanding about both employees and customers. With this technology, contact centers are able to make predictions about the future through a combination of statistics, machine learning, data mining, big data, and of course, artificial intelligence.

For instance, agents can gather information about a customer and use it to predict his next move through the use of “intelligent” software. After analyzing the information provided by the software, the agent can learn about the client’s behavior and preferences. How frequent does this person contact the company? How much are we earning from him? This can help lead to better customer interactions and result to a sale or a higher level of customer satisfaction (depending on the nature of the transaction).

Voice Analytics

Voice analytics can provide an overall picture of how each contact center transaction goes. Say, you have a sales representative attempting to entice several leads into subscribing to a cloud PBX product. Traditionally, they will be transacting over the telephone, without any body language or any other clues usually present in face-to-face transactions. By using AI technology to analyze voice patterns, managers can easily pinpoint which customers are about to buy and which customers are still undecided. They can then move to aggressive selling or offer the qualified prospects something that will definitely make them convert.

If you have a team that handles customer complaints, they could use the information to see which customers are at the risk of ending their relationship with the company. This team can then focus their efforts on retaining customers who are on their way out.

Voice analytics can also be a powerful tool in measuring how reps handle customer calls. Are they engaging? Are they enthusiastic and confident while speaking to clients or are they monotonous and robotic? By monitoring the agents’ pitch or their use of keywords and scripts, managers will be able to find out which agents are productive or effective in performing their duties. They can also barge in to intercept negative interactions between agents and clients when needed to keep customers satisfied.

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Additionally, contact center decision makers can use the information they gathered from voice analytics tools for agent training.

Natural Language Processing

In 2016, American fast food chain Taco Bell introduced TacoBot, an AI-powered service that allows customers to place orders through a messaging app built on Slack. The tool is able to answer questions, recommend menu items, and facilitate transactions from beginning to end.

This is just an example of how, through the use of Natural Language Processing or NLP, simple apps are quickly becoming virtual assistants that are capable of interacting with customers in an efficient, logical, and natural manner.

The beauty of using artificial intelligence in contact centers is that data can be collected from both ends of the phone line; a win-win situation for both sides. Decision makers are able to analyze agent performance to improve processes and at the same time get a good idea of which callers are on their way to making a purchase or are completely satisfied with their service.

With AI, your call center will truly be able to see and understand what happens in every conversation and help you make informed decisions – and informed decisions usually result to higher quality performance. Ultimately, such technology would be a good supplement to your workforce.

And mind you, this is only the beginning for artificial intelligence in call centers. Such products are becoming more and more sophisticated and powerful to create more effective contact centers in the near future.

Author info

Klaris Chua is a passionate content creator who has written a lot about cloud communications, particularly in the fields of web meetings and team collaboration. She has a trained eye in digital design and print magazine layout. Connect with her through LinkedIn or Twitter.

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