In baseball, when an infielder throws a ball too high for the first baseman to catch, the runner heading to first base usually has enough time to keep going, and make it all the way to second or even third.
When this happens, it’s called an error. And racking up too many errors can be the undoing of the most promising pro career.
Like professional athletes, customer service professionals are not immune to making errors in the heat of action. But in the competitive, high- stakes world of customer experience there are five mistakes in particular that you never want to make.
A chatbot is a computer program designed to naturally converse with human users. It has become a must-have technology for customer care because it allows companies to automate the resolution of millions of interactions without the need for live agent support.
Chatbot technology can be deployed in self- service channels, such as Virtual Agents, to reduce wait times for customers, cut costs, and increase customer satisfaction.
Chatbots can also be used to make life easier for agents, by taking the mundane, repetitive tasks off your agents’ hands. For example, if a customer contacts your organization looking to reset their password, chatbots can manage the entire process at a fraction of the cost of a live agent.
Some chatbots can handle only very basic question-and-answer interactions. More sophisticated chatbots handle a wider breadth of interactions by integrating to enterprise systems and can even take actions on behalf of the customer.
In cases where customers need an extra level of care along the journey, chatbots can actively engage live voice or messaging agents for a seamless hand-off.
Although email and phone continue to be dominant, a broader set of channels has been deployed in the last five years. Using digital channels such as chat, messaging and social has increased interactions, reduced call volume and lowered repeat contact rates. Meanwhile, adding digital channels has improved customer service metrics.
- Gartner, Market Trends: Customer Service and Support, Worldwide - 2020
As artificial intelligence (AI) technology such as chatbots continue to elevate customer care to never-before-seen heights, it can greatly enhance the capabilities of your existing customer experience technologies.
Natural language (NL) technology is a good example of this. It helps reduce the number of paths and handle time by understanding what a customer is saying and moving him or her quickly through the most efficient path to resolution. In essence, NL excels at reducing menu trees.
It becomes even more powerful when natural language is paired with AI such as predictive technology to better understand the intent of the customer and resolve issues even faster.
For example, consider a customer calling the bank, reaching the bank’s IVR and saying, “My credit card isn’t working.” Natural language technology alone doesn’t know what to do with such a general statement because the customer’s issue may require any number of different resolution paths and to select the most likely one, more information is needed.
Here’s an example of how the journey can unfold when natural language is paired with predictive technology:
Assume that in addition to natural language technology, the company had an omnichannel customer experience platform with predictive technology that tracked and shared all customer activity across channels in real time.
The platform would know who the customer was and what she was doing online before she made her call. In this case:
By combining this data with her statement “My card’s not working,” in the IVR or messaging channel, the technology would know that the most probable cause of the card suspension is a missed payment and could instantly provide her with a link where she can pay her credit card balance owing right away.
Natural language combined with prediction technology delivers faster, better journeys with higher resolution and fewer mistakes along the way—all at a lower cost to the company.
As more and more low-complexity questions are handled via self-service, the natural impact is that live agents will be expected to handle a much larger proportion of medium to high complexity calls and messaging conversations.
While most customer care leaders understand this, many have not yet equipped agents with the tools to handle these higher complexity issues. As a result, agents are finding that their duties have expanded, but their tools have not.
More complex interactions demand more sophisticated technologies that help agents handle complex calls without getting bogged down by slow, outdated systems. Here are some technologies that are proven to be up to the task:
This kind of platform tracks customer activity in digital channels and informs contact center agents of steps customers have taken in advance. This tunes the agent to the exact point in the journey where the customer is, and provides full context of their journey.
Similar to Virtual Agents used by customers today, a Virtual Agent on your agent desktops allows agents to enter questions in natural language and get the single approved answer instantly. No more wasting valuable time navigating through multiple knowledge base systems in the hunt for answers and information.
Voice and messaging agents need technology that allows them to interact with callers in ways that take advantage of the media capabilities of smartphones. This allows agents to truly guide customers to resolution faster and more easily by sharing web pages, pictures, videos and interactive forms, and viewing the customer’s activity in real time.
As customer expectations rise and technical capabilities evolve, customer care leaders need to make sure all channels for digital self-service are still pulling their weight so to speak.
There should be no passengers left behind on the journey to better customer service, and this inevitably means culling your channels and shutting down avenues for customer support that do more harm than good. Following are the biggest offenders, and the odds are good that they’re still operational on your website:
Site search technologies that return more than one single, approved answer to a question causes problems for customers. Long gone are the days when customers will tolerate being given a list of links that are varyingly relevant to their search term, links which may contain the possible answer. Relying on site search as a customer support tool is disastrous.
FAQs offer long lists of questions that may be relevant to the customer’s question, and may contain the answer. It’s an awful experience to send the customer off on a scrolling hunt for information as they pore through your content. FAQs are a guaranteed time waster for customers today and need to be abolished.
Email is rife with problems for the customer. From no replies to delayed replies to sluggish back-and-forth conversations that can stretch out over days or weeks, it’s just not a channel that keeps pace with the customer expectation for instant answers. It’s also a very expensive to staff email support properly, making it a costly channel that provides low return on the customer experience—a lethal combination in customer care operations today.
So many of today’s online support journeys can be elegantly and seamlessly converted into sales using leading technologies designed to boost conversation. Here are two examples of conversion-boosting technologies:
Immediately after delivering the answer to a question, today’s Virtual Agents and chatbots can open the door to the purchase path by introducing offers to customers that are highly relevant to their service query. This makes the offer process feel natural, seamless, and perfectly timed to the moment when the customer is most receptive—that is, immediately after answering the customer’s question.
When one of our clients, a leading North American bank, compared generic ads on their home page to intent-driven ads delivered by a Virtual Agent, the intent-driven ads achieved click-through improvements of 15x and conversion improvements of 10x.
Today’s messaging technology can proactively engage customers in a chat conversation based on their intent by tracking specific web activity or keyword (or phrase) usage and utilizing predictive algorithms. The technology knows:
One of our clients, a major retailer, compared the use of predictive chat to non-chat supported products and achieved:
As the largest provider of chatbots in the world, and other customer care solutions deployed in 400 companies, 7.ai is the right partner to make sure you make the right moves for your company.
Contact 7.ai to learn more about AI-powered conversational IVR.