To succeed, today’s contact center must be hyper-efficient; with every possible metric, output and deliverable enumerated, analyzed and optimized. With that in mind, it’s no wonder that the rise of AI and automation in contact centers has been embraced by industry leaders across America - typically by automating some simpler customer requests through chatbots and self-serve IVR - by 2020, Gartner forecasts that 85% of customer interaction will happen without a human being involved. (source: Gartner)
, a specialist business in research and experience design in 2014, and is an Australian pioneer in the field of experience design. Katja is also an International Director on the Interaction Design Association Board. She says: "in terms of 2018, we need to acknowledge the further development of robotic process automation – in other words, machines taking over our jobs, or part of them at least!
"Office work has always been a ritual, but part of the routine. Many of these tasks, like moving data from one spreadsheet to another, are boring and tedious by their nature. Completing these tasks is costly and carries the
risk of human error, and this is where robotic process automation comes into effect."
There’s a tendency to conflate automation with AI in the industry. Automation, is simple and straightforward, and has been around for years. A chat bot, after all is just a simple step forward from an IVR. True AI is a leap beyond this, with machines learning from customers, parsing and responding to requests in natural language and developing the ability to handle more complex issues and customer processes. It’s a huge area of technology and one that’s hard to navigate, requiring detailed knowledge, experience and understanding. It’s also a narrowing of view, with the end goal being a replacement of existing staff and resource, without acknowledging and exploring the way machines can support across a center’s entire business processes, including the human interaction with an agent.
, says of AI: "We see AI as valuable technology that enhances, not supplants, a Contact Centre Agent’s ability to serve and affect the customer’s experience in a variety of ways.
"As an example, Interactive Voice Response technology (both audio and visual versions) saves customer and agent time by enabling things like choosing the right queue, ordering a callback, or requesting to be
reconnected with the same agent after a call drop-out. Additionally, customer facing chatbots can be used to provide instant answers and links to further information for frequently asked questions. This significantly speeds up the service to prospects and customers, who otherwise may need to wait in a queue to speak to a live agent.
"For smartphone callers, (more than 50% of calls to a contact centre are made from a smartphone) chatbots can be integrated with Contact Centre technology to manage smartphone communications that emulate the natural, friendly speech of a human agent. Not only does this simplify and streamline operations for both customer and agent, it means that average call waiting times and call handling times are reduced, giving agents more time to handle more complex queries."
, adds: "The impact of Artificial Intelligence (AI) on call centres will be very exciting. Many of us think of AI as the little Chatbots who allow us to type in questions and get answers while on a website.
"Fasten your seatbelt, the new AI in contact centres will be video. It will be able to call up your history from your phone number or log in details so the ‘system’ will be able to direct you to where they think you want to go before you even ask a question! Gartner research indicates that ‘self serve’ will grow in popularity and the reliance upon physical call agents will diminish over the next five years. They estimate the number of transactions made by phone will reduce by 50%, however the number of transactions requiring human interaction will remain similar. "
We all know that one key benefit of machine automation is reducing the amount of time that human agents have to spend on repetitive, simple queries so that they can focus on more complex interactions, it’s been the key selling point for contact center automation almost since its inception. But what if your company could get more out of machine learning and automation? Intelligent support may be the answer.
"By deploying machine learning software and systems throughout your business, from supply chain, to marketing, to customer service and accounting; you’ll achieve concrete returns that will help to transform your business." - Kaylyn Jeffrey, HR Web & Content Manager at Service.com.au
The one key frustration that most customers complain about is having to repeat their concerns or queries - they want all the information at the agents’ fingertips as soon as they make contact. Intelligent machine support can help analyze previous customer interactions across all channels; social, email and calls, and present the agent with a likely call reason and even suggest next steps; massively boosting customer satisfaction.
, advises: "AI solutions, such as chatbots, can take care of a lot. However, they are not fail-proof. Modern
chatbot platforms have the ability to integrate with sentiment analysis tools to identify and
respond to user moods. This means that a bot can identify if a customer is becoming frustrated
or angry, and can then hand over to a human agent who will be able to provide a better level of
customer service in that situation. If the customer reaches a point where they are then ready to
continue with more common interactions, they can then be passed back to the bot."
Rather than having the agent fill out forms and navigate processes, machines can learn to complete processes automatically in the background; with the agent there solely to handle errors and exceptions, they can focus on the customer interaction and deliver quality service. This can also be applied to agent development, as in some cases machines can learn to ‘score’ parts of an agents role - leaving management to coach and develop the more intangible skills.
Machines can take up some of the burden of demand planning; monitoring call trends and adjusting forecasts for staffing requirements in real time. This could, for example, unlock the value of a gig economy approach to overflow staffing, where agents can be secured and released as demand dictates.
Analytics software can review, understand and learn customer call behavior in terms of tone of voice, psychographic profiling and likely attitude and auto-route customers to the right agents in terms of human response; e.g a natural language IVR transferring an irate customer directly to a supervisor, or matching a business-like, no-nonsense customer to an extra-efficient agent. The analytics can also work in real-time, offering automated on the spot coaching to an agent, while they’re on the call, to warn and guide them about changes in the customer’s stress levels and advising them to, for example, use more empathetic language or moderate their tone - all leading to a brilliant service experience.
All of these technologies sound wonderful, but there’s a lot to understand before you can implement intelligent service - it’s easy to get overwhelmed by what’s on offer and, as with any new technologies, there are many companies offering competing services and no real guide to best practice. There are steps you can take however, to make sure that when you do implement intelligent service, you choose the right service for your business, and your customers:
Justin Tippett from
"If you don't already have a good handle on your common enquiry types, have clear and documented processes, and Knowledge Management solutions, implementing a chat bot for example is not going to deliver good results. The "Junk in, junk out" rule applies here.
"The other challenge is that customers typically don't just deal with businesses via the one channel. So whilst you might offer a chatbot to handle some customer traffic, what happens when the chatbot is unable to assist? Ensuring your AI is integrated through the entire customer journey (think omnichannel) will lead to the best outcome for both you and your customers."
Understand your customer journey: Look at your processes and customer interaction points with a discerning eye, and make sure you understand how all the pieces fit together. By knowing the environment that your customers and agents are immersed in, and where processes or engagements aren’t perhaps as smooth as they might be, you’ll be able to see where adding a touch of intelligent service will drive value and performance in your center.
Explore the value-add: Most IT vendors will want to sell your their product based on the how; the tools and capabilities their service offers that differentiates it from their competitors offerings. To ensure that intelligent service isn’t just a vanity purchase for your business you need to understand the why; the pain point relief or improvement that implementing the service will deliver. Then build your business case accordingly.
Rather than overhaul your entire business processes and customer interactions, choose one or two areas that can most benefit from an improvement in service, understand what success looks like, implement, and then consistently and continually monitor for improvements. This will ensure a longer-term viability for the technology, allow you to understand how other areas of the business can be improved and even uncover new areas of the business that can be enhanced with intelligent service.
There’s no doubt that machine learning and automation are here to stay. We’re just beginning to explore the value and benefits that deploying them can bring. Approaching implementation in a logical, customer-centric manner will ensure that you maximise the opportunities that this new technology offers, without over-extending into a new unfamiliar technology.
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