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Contact Center AI – What’s out there?

Contact Center AI – What’s out there?

AI (Artificial Intelligence) is undoubtedly a buzzword that’s been around for a while. From the early days of Science Fiction and Kubrick’s groundbreaking 2001: A Space Odyssey to the more recent chess match between Deep Blue and Kasparov, AI has long captured our imaginations.

As technology continues to advance, companies are coming to realize that many benefits can be accrued from employing it. Tech industry giants like Microsoft, Google, and Amazon, as well as smaller companies of all types, are already devoting resources and time to develop AI for the future. Unsurprisingly, the enthusiasm of AI has spilled over to customer experience (CX) in the hope of improving call center efficiency. However, there are still a lot of questions about what AI can actually do, its limitations and its downsides.

This uncertainty has generated myths about AI, such as the popular thinking that AI will replace call center agents or equally popular, that AI will solve all CX problems. It’s therefore essential to analyze ‘what’s out there’ in customer service AI and adjust our expectations accordingly.

How AI can be Used in the Contact Center

AI has some viable uses in the contact center sphere that managers can employ to improve their CX and the efficiency of call centers. Out of these benefits, two concrete benefits of AI in the contact center stand out.

First, customers can receive accurate information instantly from self-service AI, and they don’t have to call the support center and wait on hold. Second, call center agents get access to a sea of information and can sort out complicated issues that cannot be solved by self-service functionality.

Here are some more ways AI can be used in the call center.

  1. Capturing Customer Data

    Chatbots and voice AI agents can capture data from customer interactions and feed it into analytics software. This doesn’t mean that human agents will be out of work, since 90% of customers affirm that there needs to be the option to talk to a live agent from the call center.

    Massive sets of captured data can, for instance, undergo analysis with AI technology to discover trends such as dissatisfaction with service. This can be accomplished much more efficiently than with the use of live human agents.

  2. Accurately Predicting Customer Behavior

    Apart from behavioral trends as discussed above, AI can also predict new market trends using the same tools that capture customer interactions. CX managers can then get ahead of new customer expectations to anticipate their needs and increase customer retention.

    Getting ahead of new trends is equally useful in strategic planning, where companies can plan best practices to deal with future issues.

  3. Advancing Customer Service

    AI has immense potential to improve CX and the efficiency of contact centers starting with the day-to-day activities. Handling routine user requests and trivial problem solving is a mainstay of AI. However, AI needs an effective knowledge management backbone and natural language processing to allow it to handle enquiries like a human call center agent.

    To achieve this, the AI system has to be fully integrated and fed enough data to allow it to be well-trained to respond appropriately to enquiries.

  4. Identifying and Switching Calls

    During customer calls, AI can be used to determine the nature of an incoming call and pass it to a different channel. This can include routing a call to a customer care agent or a chatbot.

    AI systems can be installed on the agent desktops to access the user’s background information, allowing inbound customer calls to be handled quickly. In the future, we can expect AI to be heavily relied on to manage customer interactions for more efficient customer experiences.

The Maturity of Current AI in the Contact Center Space

At this point, AI is still a young technology, and some people are not familiar with how it works.

True AI uses machine learning to analyze large sets of data, and natural language processing (NLP) to understand and interpret speech.

NLP is used in chatbots to understand customer requests and “talk back” to provide a solution or transfer the call to an agent. The rapid adoption of chatbots – their use is expected to jump by 1000% by 2020 – has caused some concern in the customer service sector, where many are worried it will replace call center agents.

The truth is that chatbots are currently only capable of resolving routine and straightforward questions and issues. Chatbots will save a lot of time by handling these routine requests, leaving call center reps free to deal with more complex issues. In fact, 72% of CX experts and professionals agree that human agents have a stronger impact when AI chatbots handle routine work. In the same group, 79% are of the opinion that taking over complex requests sharpens the agents’ skills.

Companies who want to achieve the maximum potential of their human resources can do so through realizing that using AI has multiple benefits.

It helps to elevate the skills of the call center team and simultaneously allows them to focus on more critical issues that generate income. Cost savings are another advantage, since less time is spent by humans on trivial tasks, meaning more productive hours and less telephone traffic.

Customer-Facing or Agent-Facing?

Before choosing an AI solution, you have to select the most compatible and effective option for you, having undertaken a careful analysis of where AI complements and enhances your existing customer experience strategy.

A customer-facing AI, for example a chatbot, can build your brand image by engaging customers on live chat, or even through messaging apps. Since the dawn of social media, companies have marveled at how much time is spent on messaging apps, and many companies have started tapping into this. Facebook Messenger, for instance, has more than 100,000 chatbots in operation, and more are being added by the day. Customer facing chatbots will not only engage customers, but can perform other tasks like anticipating customer needs, learning from interactions, interpreting common trends and preferences, pushing message alerts and informing customers about new offers or promotions. Using a customer-facing tool benefits the company by maximizing on data collection, interpretation and time-saving. Customers also benefit at the same time from a superior, effortless customer experience – a great example is the “TacoBot” from Taco Bell – since they expend minimal effort in transactions or queries.

On the side of contact center agents, there are multiple reasons to implement an AI. Customer expectations have been on the rise and customers now expect the agent to know who they are, their past transactions and history with the company. Agent-facing AI can kick in to supply the agent with the customer’s profile and details of their historical interactions with the company. If for instance, the customer has never called before, it can be marked as a high priority situation, and the call can be prioritized to give the customer a pleasant experience. With the customer profile readily available, the customer won’t have to repeat information since their history with the issue can be traced. For complex queries, AI systems can route or transfer calls to the relevant agents who can quickly solve the problem without consulting with other agents. Therefore, the call center can meet their key performance indicators (KPIs) and become more efficient and high performing.

The Future of AI in the Contact Center Space

Contrary to popular opinion, AI is not a silver bullet; it is only a means to an end. Managers should adjust their expectations and realize that human call center agents will still be a vital part of the customer experience. What managers can expect is for the AI to handle simple tasks quickly and efficiently while at the same time collecting data for future projects.

Regarding the future of AI in customer experience, it’s important to remember that AIs, unlike human agents, are scalable. If your contact volume increases, a chatbot can easily meet the demand, while the only solution for human agents is to hire more of them. This is important to note, since we are witnessing an upward trend in the number of calls that customer support centers are receiving.

Knowledge Management

Your AI system will be an expensive purchase if there isn’t any knowledge management system to back it. Most customers’ main complaint is that their queries aren’t well understood; knowledge management analyzes big data to piece together customer queries and produce effective solutions. Apart from this major benefit, knowledge management has more potential benefits, like achieving greater consistency in resolving queries. First call resolutions will skyrocket when knowledge management systems are introduced to back chatbots or other AI variations. A knowledge management system will also assist the company to understand the user’s needs and anticipate solutions for the future, hence dramatically improving the user experience.

For proponents of the effortless experience, knowledge management tools are a major boost. This is because as the knowledge base grows over time, questions can be answered more quickly and with higher accuracy for a positive customer experience. Finally, a knowledge management system saves the company training costs. Call centers are notorious for high employee turnover, and many companies spend thousands on training employees who simply do not pass their probation period. A knowledge management system cuts out the need for intensive training for new agents and fewer losses are incurred when employees decide to leave.

In conclusion, AI has massive potential but only as a tool to bridge the communication gap between customers and the company, and not necessarily managing the whole customer service department.

Download now: How to Create Perfect Knowledge Base

Download now: How to Create Perfect Knowledge Base

Creating a knowledge base for your business is a win-win customer service strategy. This eBook shares best practices in the planning, structuring and creation of knowledge bases, based on our experience in helping our customers set up and optimize their knowledge bases.

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Kaye Chapman

About Kaye Chapman

Kaye is an internationally-experienced writer and trainer, and an MA graduate of University College London, the world’s #1 center for Education and Social Science. Kaye has worked with Fortune 500, governmental and private firms across the world to advance customer service operations and embed leading learning and development strategy. As a specialist in Contact Centers, Kaye is passionate about using technology and training to improve experiences for customers and employees alike. Connect with her on LinkedIn.