AI and NLP: The Blueprint for the Next-Gen Contact Center

If you rely heavily on contact centers to communicate and manage relationships with your customers, you should always be looking for ways to make this core component of your business more efficient.

This can be a difficult balancing act. Spend too much on the contact center and you could soon run into financial difficulties elsewhere in the company, but spend too little, and you run the risk of disappointing and ultimately losing your valuable customers.

Innovation is essential if you want to overcome this challenge, and there are few fields offering more exciting opportunities for business development and modernization than artificial intelligence.

The growth of AI in business

The rapid evolution of AI is impacting and providing opportunities for businesses of all types and sizes around the world. The possible applications of AI-driven tools and technologies are practically endless, from the use of machine learning and automation in your data analytics to constantly evolving cybersecurity measures.

According to recent research commissioned by IBM, in association with Morning Consult, global adoption of AI is "growing steadily". Of the 7,502 organizations surveyed, more than a third (35%) were already using AI, while 42% were exploring opportunities in this area.

Around half of the respondents were leveraging innovations in this space to automate IT, business and network processes. The most common benefits reported were:

• Cost savings and efficiencies (54%)
• Improvements in IT or network performance (53%)
• Better experiences for customers (48%)

When it comes to the challenge of optimizing your contact center operations, one of the most promising fields of AI development is natural language processing (NLP), which could make a big contribution to the speed and efficiency of your customer service.

What is NLP?

NLP is the branch of AI that deals with the understanding of text and spoken words, focusing specifically on how rule-based modeling and machine learning can enable computers to process and 'understand' human language.

It's an area of innovation that a large proportion of your customers will already be familiar with, since it powers commonly used tools such as digital assistants (Apple's Siri and Amazon's Alexa being among the most common examples) and search engine autocomplete functions.

There are many ways NLP can be put to use in business, from the development of customer service chatbots to social media sentiment analysis.

Applications of AI and NLP in the contact center

Deployed in the right way, AI and NLP can make a big difference to your contact center operations and deliver a range of benefits for your business and its customers.

Key applications of these technologies include:

• Automation of routine processes: Rather than having to wait to speak to a human customer service assistant, callers who have a relatively straightforward task to complete - such as changing basic details on their account or asking for information to be sent to them - can get the job done quickly with the help of a chatbot.
• Advanced analytics: AI and NLP can greatly increase your capacity to convert all phone conversations into text, data and statistics that can then be analyzed for deeper insights into your audience and customer service Targeted analytics can show you how frequently certain individuals have been contacting you, for what reasons and the nature of your conversations with them.
• More accurate predictive modeling: Effective predictive modeling enables you to anticipate and prepare for spikes in call volumes, proactively address issues that affect waiting times and, ultimately, deliver a better customer experience. Keeping up with developments in AI and NLP will ensure your predictive models are constantly improving and becoming more accurate.
• Quick access to solutions: The availability of cutting-edge tools can make it easier for human assistants to do their jobs quickly and efficiently. Dedicated NLP software, for example, can suggest solutions to contact center agents who are dealing with complex issues or demanding customers. The technology analyzes what the customer has said and suggests the most appropriate next steps, removing the need for employees to spend time researching and assessing different responses.
• Error identification and alerts: It goes without saying that you should be striving to keep contact center errors to a minimum, since even a small oversight could result in lost business. AI-driven software can help you achieve this goal by instantly identifying and alerting you to potentially serious issues, so you can deal with them as swiftly as possible.

Like any new tool or technology, it's important to think carefully about how you want to implement AI and NLP in the contact center, and to use data analytics to track how these innovations are affecting performance and being received by customers.

Some segments of your audience might not be comfortable with the idea of dealing with a chatbot, for example, and could be frustrated by barriers in getting through to a human assistant.

But if you can find the right balance between innovation, harnessing the power of AI and continuing to support those who have a more traditional view of customer service, you can drive your contact center operations forward without sacrificing audience satisfaction or loyalty.