AI has already changed the way customer service and call centers function today and is redefining the possibilities for the future. Indeed, statistics show customer experience is one of the most important factors driving the implementation of AI technology and the future.
Take the example of a small business that runs a remote call center. To streamline workflow and optimize customer service, they can implement AI-based solutions that combine the best business phone system with a contact center platform that, in turn, integrates with other software and automates basic tasks..
This guide reviews examples of AI call centers technology in action, and predicting the ways machine learning will transform the industry in the future.
Let’s dive in.
Call center challenges
Call centers have traditionally faced three fundamental problems:
The first is accurately forecasting the supply and demand of call volumes and the agents needed to meet them. Businesses with contact centers can end up scheduling too few agents to deliver excellent customer service during the busiest times, or too many, which undercuts their ability to budget resources.
The next problem, which only exacerbates scheduling, is notoriously high contact center turnover rates. The reason agents rarely hang around at contact centers for very long relative to other industries? Because repetitive, mundane work can contribute to agent burnout.
Good communication in the workplace is one of the best ways to increase employee engagement. Yet keeping agents focused and engaged is a challenge. And happy agents are the key to avoiding poor customer experience, particularly in hybrid work environments. Here’s how to measure sustainability in a remote workforce.
The benefits of AI technology and the future of call centers
Machines can perform tedious, low-value tasks, for example looking up the status of a delivery, with maximum efficiency. Automation streamlines workflows, which helps businesses run as smoothly as possible, and frees up agents to take care of more complex interactions with customers. AI tools with automation are a vital complement to having skilled contact center staff in driving customer satisfaction.
Reduce costs and scale
Suppose, for example, that you launched a startup after seizing on an original idea and weighing the merits of different international domains. As your business grows, you want to drive efficiencies and scale your customer communications accordingly. By reducing labor costs, AI can be game-changing for small businesses, enabling them to deploy call centers that scale provision to meet changing call volume patterns. Even more impressive, autonomous contact centers promise to make elastic customer service a reality.
Improved customer satisfaction
Today’s customers expect to have their issues resolved as quickly as possible. And it’s not a stretch to say they want to connect with businesses via their preferred channels. That means via phone calls, chatbots, SMS for businesses, and mobile apps. Just as user testing apps help businesses to ensure they deliver frictionless mobile and website experiences, AI technology is essential to providing customers with robust omnichannel support.
How is AI changing call centers?
Examples of how AI can help contact centers solve some of their challenges:
Smart call routing
AI technology can deliver more effective call routing in call centers. Intelligent routing can make an enormous difference in freeing agents to focus on high-value, trickier conversations. With AI tools, you can automatically route the right customer to the right agent according to criteria you set, based on your goals or capacity. AI software will rely on customer behavior profiles and match specific customers with agents most suited to handling particular questions.
For example, you can set call routing for separate teams dealing with a different promotion.
Or once you know how to optimize customer acquisition cost, you can route calls to account for that other business metric that underpins growth: lifetime value.
Better routing improves customer satisfaction since customers don’t have to wait as long to arrive at the right agent to receive the best support.
Interactive Voice Response (IVR)
Interactive voice response (IVR) is an AI-enabled system that automates call routing. It’s probably not hyperbole to say that we’ve all used them in our customer service experiences, answering recorded questions ourselves, such as giving our account number. For companies that routinely receive basic questions about hours or eligibility, automated voice systems gather this information, routing inbound calls automatically to the right person.
While our interactions with IVR have classically been a mixed bag, the technology is continually improving and becoming more popular as the cost of running these systems has dropped. Businesses are increasingly using them to save on the cost of hiring human call center agents and reduce call volume, minimizing the burden on existing agents. IVR systems also reduce wait times for customers by providing this avenue to get answers.
Also known as chatbots, conversational AI is a self-service solution that allows businesses to provide instant, virtual customer assistance. They can offload a significant portion of their customer support operations to conversational AI, allowing customers to solve their own problems on-demand, reducing call volume and the need for live agent support.
Customers can engage with website content and receive instant answers to simple questions about products on ecommerce sites. And businesses can customize workflows depending on their industry or use case.
Chatbots are the fastest-growing customer service channel, and most customers report neutral or positive experiences using them. Conversational AI is getting more advanced every year, performing lightning-fast and deeper semantic searches of all your data sources to deliver the most accurate answers for your customers. And in the future, these tools will use NLP to search the conversational text of past support calls.
AI technology and the future is transforming call centers by providing in-depth analytics on sundry real-time metrics, including call times, agent availability, first resolution, and more. These business intelligence solutions allow leaders to identify trends to schedule staffing, where agents need help, and gain an overview of team and campaign performance measured against goals and benchmarks. You can then implement changes to optimize the customer experience or your future sales campaigns.
Intelligent analytics reports break down the customer data and help you go beyond human error to discover if you’re missing calls and opportunities that could cost your business revenue (check out the benefits of financial management software). For example, you might automate answers to competitor-related questions to be ready at agents’ fingertips to deal with sales objections and boost close rate.
AI also allows you to monitor quality assurance for a much greater volume of calls than human QA teams could replicate.
AI-powered call center QA is essential to ensure your call center adheres to robust security and compliance control standards, which is critical in highly regulated industries such as healthcare.
While AI cannot handle complex problem-solving and human interactions, it can track customer sentiment during a phone call in real-time. Agents and managers then have the option to step in when needed. Sentiment analysis uses natural language processing to capture the support rep’s and caller’s mood based on signs such as tone of voice or number of interruptions, enabling managers to listen in and understand how a call is going.
They can open up real-time transcripts for more context before deciding whether they need to jump in. Perhaps to close a deal or offer a complimentary product. On a related note: Let’s say you’ve done your research into how to run an effective large-scale virtual meeting with your contact center team. Why not use AI-powered transcription to ensure everyone can focus on the conversation at hand while detailed notes get taken?
Unlike traditional call monitoring by human managers, sophisticated AI platforms can monitor the mood of customers and agents to provide real-time insights to managers and provide help that guides agents. This capability is ideal for coaching and giving tips to new agents to get them up to speed quickly. Another use case is identifying a customer risk score and recommending the best action to a rep during a call, removing guesswork and helping agents say the right things.
AI is also helping businesses with outbound call centers bolster their sales conversations. Answering machine detection tools uses machine learning to judge whether a human or voicemail is at the end of an outbound call.
That way, sales agents can stay in the rhythm conducive to successful conversations, increasing their productivity and helping them make a better living through commissions. Increased agent morale then means reduced turnover.
SMS bots can optimize lead generation efforts, freeing up agents to focus on the work of converting them. This AI software can analyze your CRM data and help you sort through hundreds of prospects to discover the most promising leads.
AI-powered virtual agents can ask qualifying questions to determine if prospects are a good fit. As technology develops, conversational IVR systems look set to get even better at sending friendly, personalized messages to your leads.
AI technology: the future of call center transformation
Automations already answer calls immediately and resolve Tier-1 customer service issues more efficiently, ensuring customers don’t need to wait on agents manually entering data. Better yet, AI tools work well with CRMS and existing software, meaning agents and managers can access the insights that help them make better decisions that level up customer outcomes without needing to toggle between multiple systems.
Information can be found and updated instantly, with summary notes generated, so customers don’t need to repeat themselves if they get transferred. All of which make for faster response times, higher call resolution rates, keeping agents happy, and empowered to perform better.
As AI technology develops, autonomous contact centers promise to enable organizations to scale customer service elastically to drive call center costs down further and push CSAT scores up. Sounds too good to be true? Watch this space.
Jenna Bunnell – Senior Manager, Content Marketing, Dialpad
Jenna Bunnell is the Senior Manager for Content Marketing at Dialpad, an AI-incorporated cloud-hosted unified communications system and a Dialpad call center solution platform that provides valuable details for business owners and sales representatives. She is driven and passionate about communicating a brand’s design sensibility and visualizing how content can be presented in creative and comprehensive ways. Jenna has also written great articles for sites such as LandingCube and SMEnews. Check out her LinkedIn profile.