3 Responses to Using AI to Serve Customers

By Peter Lyle DeHaan, Ph.D.

Predictions about the emergence of artificial intelligence (AI) have been with us for decades. But until recently they only showed up in science fiction books and movies—usually with dire results. Such is the basis for good fiction.

Yet in recent months, advances in artificial intelligence have surged forward, reaching into every industry, including the call center and customer service sphere. With AI, just as with any technological advancement, there are three responses.

Ignore It and Maybe It Will Go Away

The first reaction, which is really a nonreaction, is to dismiss it. Maybe you’re already sick of the hype or maybe you’re not aware of it. Yet assuming a computer algorithm has no place in your call center is not a wise conclusion to make.

The risk of this approach is getting left behind. You will find—likely in short order—your call center operation and your company competing with others who have thoughtfully integrated artificial intelligence into their operation.

They will serve customers in a way you cannot and save money you’re not able to.

Gung Ho Adoption

The second response is the opposite. It’s to go full speed ahead in adopting artificial intelligence technology for the call center. Yet this is also fraught with peril.

The news is filled with artificial intelligence going awry. In recent months, companies have been publicly embarrassed and their stock has taken a hit, not because of human error (at least not directly) but because of computer error. These occurred from AI applications running unchecked and without restraint.

If you’ve ever used text chat to submit a customer service request, you’ve likely interacted with a chat bot, which is an artificial intelligence application. In my experience they’re unlikely to solve my problem, but usually they collect some preliminary information and route me to a real person who can help.

Yet just recently, a chat bot took me down the wrong path, leaving me with two unacceptable options: agree that the chatbot had solved my problem or pay to upgrade my service. End of discussion. But it wouldn’t allow me to start a new chat session until I concluded the first one by picking either of its two unsatisfactory answers.

I also think artificial intelligence was involved in a recent near-miss with an email support effort. I had submitted a service ticket, but a couple hours later I figured out the solution on my own. I sent a follow up email to cancel the ticket. The response told me how to cancel my service with the company. This may have been a human error by an agent who scanned and didn’t read my email, but I suspect it was artificial intelligence which responded wrongly to the word cancel. Fortunately, the AI bot didn’t take the initiative to close my account.

Imagine seeing these examples extended to telephone calls at your call center. Yet it’s already happening.

I recently read a report of artificial intelligence telling human agents how the solve customer problems and what to say. The AI then grades the agent on compliance, penalizing agents who use common sense to override the AI’s bad guidance.

Then the common excuse of “I was just following orders,” becomes “I was just doing what the computer told me to.” May it never be.

Cautious Implementation

The third response—the one I recommend—is a balanced perspective. Investigate the use of artificial intelligence in your call center operation. Make an informed decision as to how to best use it. The wise application is to implement artificial intelligence to better serve customers. Don’t pursue AI merely to save money, even though this should emerge as an expected outcome.

Seek ways where artificial intelligence can make your agents’ jobs easier. Look for ways where AI can help your human staff better serve your human customers. A guiding principle in this is to keep AI in an advisory capacity. Give your agents final say. They should be able to control the AI, not have the AI control them.

As you appropriately implement artificial intelligence in your call center, the goal should be to offer better customer service, improve response times, and lower payroll costs. But don’t look for AI to replace your staff anytime soon. And my advice is to resist the urge to blindly implement AI, lest you end up with a public relations nightmare, lost business, and a decrease in new customer acquisitions, all through AI run amok.

A good baseline requirement to guide your use of artificial intelligence in the call center is to empower your agents to control it, not let AI replace the common sense and empathetic problem-solving ability of real people.

Peter Lyle DeHaan, PhD, is the publisher and editor-in-chief of Connections Magazine. He’s a passionate wordsmith whose goal is to change the world one word at a time.  Read more of his articles at PeterDeHaanPublishing.com.

By Donna Fluss

Many years ago, when I was managing a credit card customer service contact center, one of our clients threatened to bomb our office. The agent who received the threat followed protocol and the issue was immediately brought to my attention, as the head of the department. I assessed the risk—per guidelines—and made the decision to keep everything going.

My evaluation of the situation was based on many factors, most importantly the risk to my employees, which I determined to be non-existent, as I knew this caller and his frequent issues very well. (To put this into perspective, when the fire alarm went off a few weeks later due to a fire drill that we had not been notified of, we immediately emptied the contact center, as the risk was perceived to be high.)

The world has changed a great deal since I ran that contact center, and so have the guidelines. Bomb threats and other types of warnings to a business/institution/government agency and its people happen too frequently. Organizations have established protocols, policies, and resources to assess risks, which include notifying a risk assessment team that makes the decision about how to handle the situation; this judgment is no longer left up to the department manager.

Contact Centers are Points of Vulnerability for Enterprises

A contact centers is fraught with risk since its purpose is to invite the outside world in to interact with a company. It’s a natural point of vulnerability; its physical site(s), employees and customer data must be protected. Companies need to have plans in place to protect all customer-facing functions, as the risks are growing with each passing year.

There are many types of risks and attacks that contact centers face, including:

• Physical threats to people and property: bombs, shootings, ramming cars/trucks into buildings, etc.
• Human-engineered phishing attacks: hackers breaking in and stealing customer information
• Ransomware attacks: hackers breaking through a company’s security and freezing access to their systems and accounts unless a ransom is paid
• Phone-based attacks: a fraudster (or a group of people working together) calling repeatedly until they get the information they need to access specific customer accounts
• Attacks through the self-service solution: a fraudster accessing a specific customer’s account via a website, interactive voice response (IVR) system, intelligent virtual agent, or other self-service solution
• Compromised employees: having an employee who is either a fraudster or is paid to collect and share customer information with a thief
• Many more

Establish a Security Framework

Contact centers need to establish a security framework that minimizes the risk of fraud, as there is no known way to eliminate it completely. This begins with the contact center’s underlying network architecture. Today, especially with the increase in work-from-anywhere staffing models (for agents and other contact center personnel), the recommended approach is based on a Zero Trust configuration. Zero Trust requires continuous authentication of all network devices and users and limits network access to the least privileged level.

Contact centers can also apply a Zero Trust approach to customer authentication, which takes 2-factor verification a step further. It means that customers who were verified in a self-service solution must be “re-verified” if they transfer to a live agent. Or if a customer is transferred from one agent who verified them, they must go through the verification process again when they speak to a second agent. (The customer will be put through a 2-factor verification during the first contact with a self-service solution or live agent and only a single-factor authentication for the second contact.)

This process reduces fraud risk and losses but will frustrate and annoy legitimate customers because of having to be verified multiple times when transferred between devices and agents. Therefore, this approach should be applied only when necessary for certain types of sensitive transactions.

Making a Contact Center Secure

I’m sorry to say that there is no perfect way to protect a contact center, its employees, or customer data. Fraudsters who are intent on getting information will keep at it until they find a weak link in the system. Companies need to put in place systems, guidelines, and policies to minimize the risks and encourage their agents to report potentially fraudulent activities, without upsetting customers.

Contact center agents need to perform their primary job—delivering a great customer experience—but must do so keeping both eyes open in today’s world.

Donna Fluss, founder and president of DMG Consulting LLC, provides a unique and unparalleled understanding of the people, processes and technology that drive the strategic direction of the dynamic and rapidly transforming contact center and back-office markets. Donna can be reached at donna.fluss@dmgconsult.com.

Tips for Improving Processes or Adopting New Technology

Submitted by SingleComm

While process-improving technology is a must for contact centers that want to stay competitive and improve customer experience, putting new technologies to use can mean growing pains, slow implementation, and frustrated employees. Patient experience ensures that your agents can connect patients to providers efficiently and securely.

In this article, we’ll discuss some common pain points contact centers experience when adopting new technologies or processes.

What Is Process Improvement?

Process improvement involves identifying, analyzing, and improving existing business processes to optimize performance, meet best practice standards, or improve user experience.

Often, the catalyst for process improvement comes in the form of a new technology solution. For example, the printing press allowed the production of books to increase drastically because the process of how books were made fundamentally changed.

How Technology Improves Business Processes

A large part of improving processes involves identifying inefficiencies and, when possible, streamlining them. These are two things that tech solutions excel at.

Tech applications can shine a light on redundant sections of processes and have the capability to automate repetitive, time-consuming tasks. This enables contact centers to reduce the cost of operation, save time, focus on other tasks, and speed up business operations.

Common Pain Points

Identifying opportunities and successfully managing through change can be painful but failing to innovate can be a death sentence for a business. With that in mind, here are some of the most common pain points organizations must work through when adopting a process change or new technology.

Cost

Cost is a significant factor in a contact center’s decision to adopt new technology. By quickly identifying deficiencies and enabling contact centers to make fast, efficient changes that optimize time-to-market, helps users to reduce their costs by about 40 percent.

Employee Buy-in

When a team member is unsure of a new technology or process, there is a good chance they will avoid embracing it fully, making the technology seem ineffective and causing the team member to become even more skeptical of the new solution. It’s a cycle that can be incredibly harmful to innovation.

Employees can have a variety of reasons for being hesitant about embracing new technologies or processes:

• Lack of awareness about the purpose and reason for the change.
• Adherence to an old methodology that they feel comfortable using.
• Belief that the new process or technology might make them redundant.
• Too busy to devote time to learning a new system.

Adoption Speed

The time between deciding on a new technology solution and having it fully implemented can be a tedious journey. Waiting for agents to become proficient with a platform can end up having the opposite of the desired effects of the new technology. Instead of happier customers and decreased call times, you end up with agents fumbling through a new interface and customers spending extra time on the phone.

Lack of Resources and Support

Even if there is complete buy-in from every agent, a lack of proper training and support can stymie the adaptation of new technology.

SingleComm is the cloud-based all-in-one call center software solution that helps contact centers train agents faster, turn data into actionable insights, and save big on operating expenses.

Increasing Customer Satisfaction with a Human-AI Team

By the SingleComm team

Today’s customers have little patience for long waits, multiple handoffs, and unresolved issues. It only takes one unpleasant experience to send them headed for the hills–or another brand.

Adequate staffing has long been the go-to method for handling call volumes. But the days of readily available employees are gone as contact centers struggle to attract and retain talent.

The solution is a future-forward strategy that maximizes their teams’ capabilities, also known as AI (artificial intelligence).

According to Gartner’s 2021 Technology Roadmap Survey, more than 65 precent of customer service and support leaders are optimistic about the value that AI can provide, and they plan to increase their adoption of AI capabilities over the next two years.

Furthermore, new research conducted by The Harris Poll revealed that improved customer experience is now the most frequently cited driver of AI implementation decisions, above cost reduction and the ability to drive top-line revenue.

Advanced technology solutions are not new to the contact center industry: call-routing and interactive voice response (IVR) systems have been in use for decades. But today’s AI-powered options are taking the customer experience to new heights.

Myth versus Reality

When people hear the term artificial intelligence, scenes from the movie The Terminator often come to mind. But AI reality is quite different from AI myth. According to Seth Earley, author, founder, and CEO of Earley Information Science, here are five common myths about artificial intelligence followed by AI truths:

• Myth 1: AI algorithms can magically make sense of all your messy data.
  Reality: AI is not “load and go,” and the quality of the data is more important than the algorithm.
  Translation: Regardless of any AI interaction, good data in means good data out.
• Myth 2: You need data scientists, machine learning experts and huge budgets to use AI for the business.
  Reality: Many tools are increasingly available to business users and don’t require huge investments.
  Translation: There are AI solutions available to fit any business and any budget.
• Myth 3: Cognitive AI technologies can understand and solve problems the way the human brain can.
  Reality: Cognitive technologies can’t solve problems they weren’t designed to solve. 
  Translation: AI technology performs according to design. 
• Myth 4: Machine learning using neural nets means that computers can learn the way humans learn.
  Reality: Neural nets are powerful, but they are a long way from achieving the complexity of the human brain or mimicking human capabilities.
  Translation: You don’t have to worry about computers taking over your contact center.
• Myth 5: AI will displace humans and make contact center jobs obsolete.
  Reality: AI is no different from other technological advances in that it helps humans become more effective and processes become more efficient.
  Translation: AI will not change the need for skilled and talented call center representatives. In fact, AI will enhance their superpowers while improving the performance of the contact center and increasing customer satisfaction.

Taking Your Contact Center to the Next Level

There are many ways that AI can strengthen your team’s performance and improve your processes.

• Personalization: Tailoring the experience based on information that the platform has learned about the caller or user.
• AI-Based Customer Routing: The ability to match customers with the best resource or agent.
• Chatbots and Conversational Assistants: Interacting with customers, either by text or voice, taking care of simple and/or repetitive issues, and freeing up contact center representatives to focus on more complex assistance needs.
• Workforce Management: Data analysis capabilities that help predict when agents and resources are needed.
• Post Call Wrap-Up: AI assists representatives in entering call-action summaries and wrap-up codes.

By using AI systems and solutions, you are not taking anything away from your human team members. Instead, you are empowering them to raise the bar to meet and exceed customer expectations by streamlining processes and tasks, which allows them to spend more time on supplying the best service possible. Talk about a win-win.

Interested in learning what a human-AI team might look like in your organization? We have the information and solutions you need. Contact us today to schedule a demo.

By Trey Norman

More complex customer queries call for knowledge management to simplify tasks. Simplifying the steps taken for answer retrieval is beneficial not only for companies and their employees but also for customers.

In addition to reducing time and cost, more benefits arise. With knowledge management technology, call center agents have it easier with access to all company data right at their fingertips every time a customer picks up the phone. The request often requires more details than someone confirming their account number or product delivery date, and complex queries send agents on an endless hunt for information.

Knowledge management turns complex queries into a simple and productive phone call between brand and customer.

Call center agents can look up relevant data in no time to help customers get the information they want. This diminishes the need to transfer them because the first person on the phone has a 360-degree view of company knowledge, allowing them to quickly find the data and keep the lines open for the next caller.

The Value of Search and a 360-Degree View

Considering a company and its data, so much comes to mind with the breadth of technology and applications used today. From emails, sales documentation, contracts, support tickets, chats on internal collaboration platforms, and marketing analytics, there is way too large of a scope for customer service agents to find what they need and keep a customer happy in a timely manner. Eventually, they may resolve the issue, but at what cost?

High-level knowledge management with the help of artificial intelligence can slash through data silos and connect prominent information from all relevant sources. All a company needs to do is make it accessible to employees on the front lines.

While search is a significant function of these systems, proactive input and graphical displays can also be essential within call centers. From a search standpoint, representatives can search for keywords related to the specific customer or the issue needing resolution. Generated are search results, like on Google or Bing, of resources and content about the topic—precisely filtered the way the agent needs it. Query results could lead to a support ticket of a past customer who called with the same problem, or it may lead to a helpful whitepaper that discusses the topic in question.

But there is more to solutions than just searching and finding. We all know this is not always how it goes, as many of us have been on page ten of google results before. Machine learning techniques like Natural Language Processing (NLP), understand written and spoken language. That said, queries will lead to the exact sentence of a whitepaper or support document because intelligent systems understand what the employee needs just as a human would.

Not All Answers Have a Single Source

Search and search only may not be what the company and customer need. With complex queries, it may be unlikely the full answer lies in a single document. Connecting data sources allows graphical overviews to be created from all relevant sources. On one display, past customer tickets can appear to agents while specific data about the customer is highlighted on another, right next to each other in one central location.

Customer service agents don’t need one source opened on their primary monitor, another open on a second monitor, and a third source hiding behind another window. They can relay information back to the customer on the other end from one place that shows every source.

Auto-Generated Responses: Answering Questions for Agents

The last part is where technology really amazes. Another popular machine learning technique used in knowledge management is NLQA, Natural Language Question Answering. Not only does NLQA understand human language the way NLP does, but it can auto-generate answers based on sources of information within the company. Many companies have turned to chatbots to reap the benefits of Natural Language Question Answering and automated assistance.

But why should a chatbot get all the cool and innovative tools when people are still picking up the phones and relying on humans to support them? Taking advantage of this could lead to support agents receiving answers in real-time based on the spoken words of the caller or typing in the query. This practice saves many hours and dollars while making a difficult job more manageable.

Taking a hard look at company data sources and what is relevant to customer service and call center agents is especially important for businesses to move forward. Quick and efficient support is key in retaining business and maintaining happy, paying customers. With these tools and innovative knowledge management, many dollars and stressful phone calls can be saved.

Trey Norman is the COO at Mindbreeze.

By Donna Fluss

The knowledge management (KM) market is experiencing the most rapid adoption cycle in its history. Driven by customer expectations for a great experience, increased demand for self-service, the need to empower employees throughout the enterprise, and the rise of artificial intelligence (AI), KM solutions are being purchased to meet a wide range of requirements.

The significantly increased demand is driving a large research and development (R&D) investment cycle, which is invigorating and greatly enhancing all aspects of these solutions, enabling vendors to convert them from searchable information repositories to highly contextual sources of intelligent content.

The KM vendors are applying AI to enhance many aspects of their solutions, including the creation, curation, and oversight of content. The “garbage in/garbage out” issue has long been one of the largest impediments to acceptance and adoption of KM solutions. Authoring and maintaining pertinent and up-to-date content will always be a critical element of these applications, and the vendors have started to introduce tools and best practices to help companies manage this essential aspect of the system (and process).

Artificial intelligence is being used to locate and prioritize the most relevant knowledge utilized by organizations, as well as to help administrators keep it current by identifying outdated, redundant, and missing information. Artificial intelligence and other enhanced features also enable companies to create one answer and automatically render it in a manner appropriate for each user and channel.

This is just the beginning of many practical and game-changing innovations that the KM vendors are delivering to the market, along with improved system usability, integrations, and much more coming during the next couple of years.

Process is as Important as the KM Solution

While technology makes a difference for any solution, including KM, how it is perceived and used are equally important. Contact centers and other enterprise departments that want to realize benefits from KM need to build a culture that prioritizes agents’ use of knowledge over productivity.

For years, contact center leaders asked their agents to use KM to standardize inquiry handling and then complained that it took them too long. The new generation of context-sensitive and highly responsive KM solutions can more rapidly serve up the information agents need to resolve customer issues, eliminating one of the biggest impediments to adoption.

However, it will still take training and encouragement to get agents on board and contact center leaders need to support these efforts by making KM usage one of the department’s core tenets for success.

Selecting the Right KM for your Contact Center

Prospects need to carefully assess the KM offerings in the market, as each one is in a different stage of its development, despite vendor claims. Adding complexity to the challenge, vendors in many IT sectors, including customer relationship management (CRM), contact-center-as-a-service (CCaaS), and even workforce management (WFM), are claiming to offer their own KM solutions.

In many cases, these are knowledge repositories designed to provide information, best practices, and tips to support the use of their own core solution and are not full-fledged KM offerings. (This doesn’t make them bad, but it limits their overall scope and contributions.)

Given the tremendous amount of innovation introduced into these solutions, it’s time to find a vendor whose product and plans align with the needs of your organization. And be sure to select one that listens and has a proven record of accomplishment of applying customer feedback to its roadmap.

Final Thoughts

The current generation of KM solutions are excellent and have proven benefits. The next generation of KM solutions that are expected to be delivered during the next two years will be even better, as significant improvements to the underlying technology should enable vendors to deliver on the benefits they have been promising for decades.

For an in-depth analysis of the knowledge management (KM) market and the solutions that are vital in supporting the needs of today’s digitally transformed and artificial intelligence (AI)-enabled enterprises, please see DMGs 2022 – 2023 Knowledge Management for the Enterprisereport.

Donna Fluss, founder and president of DMG Consulting LLC, provides a unique and unparalleled understanding of the people, processes and technology that drive the strategic direction of the dynamic and rapidly transforming contact center and back-office markets. Donna can be reached at donna.fluss@dmgconsult.com.