We are now well into the 21st century – a time that has seen a shift in technology unparalleled in our lifetime. The technological and digital revolution we have experienced has brought conveniences to our lives we could only have dreamed of just a few decades ago.
From reaching out to get customer support to finding out what the weather forecast is, the digital world empowers us to do more things for ourselves, and more conveniently than ever before. Times certainly have changed. It was not that long ago that having a house robot seemed more like fodder for a science fiction movie than the near future. As we transition towards the Augmented Age - where computers help us think, robots help create and a ‘digital nervous system’ will connect us to the world – the future is here, now.
“Can I afford to go out to dinner tonight, Alexa?”
Perhaps one of the most ubiquitous examples of virtual assistance that has integrated into our lives is Amazon Alexa or Siri. From knowing our schedule to completing simple information gathering and task completion, virtual assistants are being quickly adopted by technophiles and average families alike. We might think our comfort with artificial intelligence comes in baby steps, but the reality is technology improves in leaps each and every year, personalizing to our habits and preferences, and becoming more commonplace in homes and handbags.
While robots and AI are busily integrating into our homes and lives, industry is quickly adjusting in the augmented age as well. Our transportation systems, for example, are on the precipice of massive change.
From drones, to self-driving trucks and ships, to robots capable of picking and packing in a warehouse, investments in AI can create major cost reductions and improvements to efficiency in the transportation of goods. Imagine how a chatbot can integrate into this system, potentially informing your customers with a human-like conversation, about the location of their packages with pin-point accuracy.
Considering the impact of artificial intelligence, chatbots and virtual agents across dozens of industries, we are set to witness the most significant change to how we work since the industrial revolution.
In particular, we must wonder; what will happen to service industry jobs? Wide-ranging changes are imminent here. Nothing is safe; insurance adjusters to McDonald’s employees will be impacted by AI and the virtual employee. Do humans become less necessary the more we teach our artificial intelligence tools?
The simple answer is, no. The more complex answer is, preparing for the future by investing in data now will help with a smoother transition from humans doing all the work, to humans empowering technology to help them.
To teach AI, you must have good data; about your customers, about your products, and about how your business runs efficiently. Investing in that data now sets you up to teach your AI in the future. As your customer becomes more and more accustomed to interacting with artificial intelligence, appreciating and expecting their level of accuracy and efficiency, the virtual assistant and chatbot becomes one of the most important items in your customer service toolbox. Not the only, though. Humans are still vitally important to customer service. Empowering effective chatbots will help humans be more effective in their own jobs – everybody wins!
Certain things in life are better together, like peanut butter and jelly, Simon and Garfunkel, and AI and agents.
The last one might come as a surprise to some, as many people believe AI and human agents typically work independently of one another, or even in opposition to one another - but in reality, they work best when they’re working together.
Both AI-powered chatbots and human agents have their strengths and weaknesses. By blending them effectively in appropriate journeys, organizations offer their customers the best of both worlds – and will also enjoy a number of supplementary benefits in the process:
AI-powered chatbots are great at taking on many of the menial tasks that quickly become tiresome and repetitive to humans (e.g. password resets, account balance inquiries, business hours). Assigning these kinds of low complexity journeys to chatbots is not only a faster, better experience for customers, it relieves much of the burden placed on human agents and frees them up to focus on resolving complex customer journeys, which is often much more fulfilling.
Sometimes customer journeys that start with a chatbot need to be escalated to a human agent for resolution. When this happens, chatbots are able to transfer the full context of the journey to the agent, which prevents the customer from having to start over. Additionally, when customers are talking to chat agents, the agent is able to use insights collected by machine learning technology to engage the customer with real-time offers tailored to their unique needs and interests.
Chatbots are the preferred method of communication for many, because they allow customers to self-serve and resolve problems without having to call and wait (and wait) to speak with a human agent. Whenever you can streamline your customer experience and reduce resolution times by deflecting away from the more costly call center, it’s an ideal outcome for your organization and your customers.
Chatbots are also available to work 24/7 – including weekends and holidays – making them the perfect solution for handling questions that come in during off-peak hours.
Consumers are getting more comfortable interacting with chatbots and AI-powered technology, and if they’re able to solve a problem using chatbots alone, they’ll be happy. Offering your customers an enjoyable – and fast – self-serve experience that essentially eliminates wait times, is a win for your organization. When customers do need to speak with an agent, agents will have the entire journey context and access to a wealth of on-demand information, so they can quickly identify the problem and offer an immediate resolution. All of this will go a long way to reducing your average handle time (AHT).
Though blending bots and agents is an ongoing process, when done correctly, it will offer a number of benefits to your company and your customers. Before you begin, it’s important to review your customer journeys to find out where chatbots will make the most sense. Also remember to communicate with your agents – be sure they understand that chatbots aren’t here to replace them, they’re here to help them perform better.
Many forward-thinking companies are turning to virtual agents to contain costs and offer around the clock support in their contact center. This push to automation has inadvertently pitted human agents against machines in a battle for survival – but the truth is, great CX will always require a mix of chatbots and humans.
If you’re ready to increase automation in your contact center, explore the following four human-AI blending scenarios to see how you can ensure both agent and customer satisfaction are elevated.
In this scenario, chatbots remain the first point of contact for the customer. However, if the AI gets stuck or confused, a human supervisor helps the bot get back on course. For example, the customer’s utterance may be vague and map to a number of possible intents. Or the bot may misunderstand the intent and become more confused as the customer attempts to clarify the request. In these situations, a human agent can review the transcript, disambiguate the intent, and set the conversation on the right track. The bot then continues without the customer knowing that a human was in the loop.
This form of blending deals with a frequent roadblock in many enterprises: the difficulty in accessing backend systems. When this occurs, conversational AI outstrips the capabilities of the company’s APIs – that is, the bot understands the intent but cannot access the enterprise system needed to automate that intent. In this situation, the bot can ask a human agent to fetch the information and execute the transaction, which the agent can do by logging onto the various enterprise applications and cutting and pasting data between them.
This technique can be a stop-gap measure while the company deploys RPA (robotic process automation) or APIs. The benefit is that customers learn to trust automation without being exposed to the work behind the scenes to overcome backend limitations.
Some brands may prefer a high-touch support model that focuses on human agents rather than bots as the primary interface for consumers. Under this approach, the human agent can benefit by delegating certain routine tasks to the bot, such as collecting structured input (account registration, address change, credit card details) or presenting uniform content (product details, terms and conditions, regulatory disclosures).
A benefit is that sensitive information (such as social security or credit card numbers) can be transmitted directly to backend systems without passing through the agent. Another benefit is to ensure compliance by presenting information that is curated, consistent and auditable. In all these cases, the agent invokes a bot that drives the conversation for the specified task. The agent remains in control, however, and can take over the interaction at any point.
When a customer interacts directly with a human agent, AI can be used to enhance the effectiveness and productivity of the agent. A bot listens to the conversation (which could be in text or voice) and feeds the transcript to a machine learning model that outputs a suggested response to the agent in real-time. The suggestion can come from a knowledge base, or can be generated from a deep neural network trained from other agent responses in similar situations.
To remove noise and avoid misguided training, the training set should be filtered to select conversations from the best agents, as measured by resolution rates and customer satisfaction ratings. The neural network technology is similar to that used in some experimental open-domain chatbots that can converse with users on any topic for fun and entertainment.
In customer service, neural conversational models are not ready for direct customer interactions due to the risks of uncertified answers and lack of explainability or transparency. However, the technology can be extremely effective as an agent-facing tool, providing best-practice responses that the human agent can accept as-is or edit slightly, thereby saving agent time while improving quality.
The battle between man and machine today is a combination of tug of war, a fluctuating scale, a seesaw, and a bit of a roller coaster thrown in for good measure. It is a constant battle to find the reciprocal, equally beneficial and equally enjoyable path to quality service. Neither people nor machines are going anywhere. They need to learn to work together.
Human-level artificial intelligence is necessary to understand intent. This is particularly true when it comes to customer experience. Technology, particularly artificial intelligence and chatbots, have threatened the long-established world order of solely using humans to help consumers interact with companies. What many companies have lost sight of, however, is that there is a much bigger enemy out there – bad customer experience.
The fact is, many companies aren’t living up to customer expectations. Consumers expect that companies will know who they are and what they want, and they will not forgive poor customer service that wastes their time.
Unfortunately, as companies began deploying chatbot solutions, many made the mistake of not understanding these truths and not investing in understanding their customer’s intent. They put the wrong metrics in place and didn’t focus enough on customer satisfaction.
The experimentation phase is over and companies are now taking a much harder look at chatbot technologies. So, what does a chatbot comeback look like? The answer may lie in human agents.
Investing in the right blend of AI and human intelligence (HI) can result in a “near human” experience for consumers. Chatbots cannot completely replace humans, at least not yet, and they have to work with humans to deliver the right results. AI investment is necessary because it is through the power of AI and machine learning that we can decipher huge amounts of data to truly understand what customers want. Only by understanding what they want can companies deliver the best experience to them.
The future of customer service is one in which chatbots powered by AI and human intelligence are delivering convenience and customization that consumers look for—and provide the comfort of a humanized conversation. There’s no part of the business where virtual agents and real people can work together better than in helping customers. Bots are fast and accurate. People are empathetic and have judgment. Together, they’ve got what it takes to deliver