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Is the Future Our Friend or Foe?



Be Ready for Artificial Intelligence to Revolutionize Your Call Center

By Peter Lyle DeHaan, PhD

Peter Lyle DeHaan, Publisher and Editor of Connections Magazine

One of the spaces I inhabit is the call center industry. Another of my worlds is writing. These two areas intersect in this column. Another commonality is how technology, specifically artificial intelligence (AI), will affect both sectors.

Futurists in the writing community talk about how AI will arise as a disruptive force. Indeed, the disruption has already begun, with computer programs writing poetry, song lyrics, a screenplay, and even a novel. Much of the writing community isn’t aware of this emerging reality. Other writers deny that AI even exists and consider it a pipedream. Some see it as the end of writing as we know it and a threat to their livelihood. Last are those, like me, who see AI as a tool that will help us write more, write better, and write faster. Yes, writing as we know it today will change dramatically, but that change is something to embrace.

AI is also making inroads into the call center industry, and the reactions to AI in the call center space are much the same as in the writing world.

Blissfully Unaware

Many people in the call center industry aren’t aware of the burgeoning developments with AI and how it will dramatically change call centers and their provision of customer care. They view AI as the topic for sci-fi movies, scientific labs, and a far-off future reality—one that will occur long after they no longer care.

Instead, they focus on the day-to-day urgencies of hiring, training, and scheduling agents. They look at metrics such as first call resolution, speed of answer, and average call length. They consider the number of calls in queue, time in queue, and abandonment rate. And their world focuses on resolving customer complaints. There’s nothing wrong with these worthy pursuits, but it keeps them from considering tomorrow and embracing the future.

Deny It’s a Threat

Others acknowledge the existence of AI, but they don’t see how it could help call centers serve customers better. If anything, they assume AI will make customer service harder and therefore perpetuate the need for live agents. To them, AI is another call-center fad that will receive a lot of hype for a few years and then fade away. Their response is to maintain the status quo and pursue business as usual. 

Fearful Over the Future

Next, are the Luddites, those who oppose technology. Though some call centers embrace technology much more than others, every call center has some degree of tech in its infrastructure and operations. These people have formed a comfortable truce with the tools they use, and they don’t want any more of them. They have enough, and everything works fine, thank you very much. More tools, especially AI-powered solutions, makes them shudder. They fear that self-learning programs will take over the call center space and eliminate their jobs. 

AI will assist call center agents, helping them work more effectively and efficiently. Click To Tweet

Embrace It with Optimism

The final group looks at AI as an intriguing call-center solution. Yes, it will fundamentally change how call centers operate. And this transformation could happen much sooner than most people suspect. Yet instead of fearing uncertainty over the unknown, these forward-thinking futurists welcome AI as a smart solution to many of the challenges call centers to face.

Yes, in some cases, AI will replace jobs, just as answering machines, voicemail, automated attendants, and IVR have done in the past. In other cases, AI will assist call center agents, helping them work more effectively and efficiently. This will occur just as our existing tools have improved the results produced from our prior toolset. Then, now, and in the future, the customer benefits by realizing enhanced outcomes.

Thanks to AI, in the future you won’t need to hire as many people to staff your call center. And those you do hire will benefit by having AI to guide their work. These employees will find their call center job less dreary and more invigorating. The days of routinely shuffling through repetitive calls will end, replaced with variety in handling challenging calls that AI can’t address. This will provide the opportunity to excel in call-center work as never before.

AI isn’t coming. AI is here. What role will it play in your call center?

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.

Challenges and Opportunities: Contact Center and Artificial Intelligence



By Ross Sedgewick and Lisa Campbell

Within most contact centers, artificial intelligence (AI) adoption remains in an embryonic stage. As companies like Google compete to become AI-first, there is plenty to suggest this next leap in consumer engagement models will soon become inevitable. Yet contact center employees and the industry at large are apprehensive about the impact of AI on service levels and jobs through the deployment of new digital automation capabilities.

Current research shows that as many as one-third of all jobs could be lost to AI in the next decade, with frontline contact center work being among the most vulnerable. However, because of strong commercial gains and changes to customer engagement models, AI is poised to become far more mainstream in customer contact centers.

Current trends may see contact centers achieve at least one-third AI-based interactions by 2022. Click To Tweet

More companies are rolling out AI-driven software bots to reduce live agent costs while collapsing wait times. (In theory, there is no queueing time to reach a software bot agent). As with prior generations of automation, such as interactive voice response (IVR), automated software bots have proven to provide good results in structured, repeatable, and simple customer interactions.

The Challenges with AI in Contact Centers

AI has the power to transform consumer engagement. While there will always be a place for voice in the modern contact center, consumers are looking for a faster, more frictionless experience. AI, when deployed effectively, can deliver this.

Traditionally, a live agent’s voice is ideal in complex, escalated, or empathy-intensive scenarios, or when the customer is not embracing technology or internet tools. For example, if you are an insurer and define your brand by understanding customers and offering personalized service, any shift to AI—from a contact center perspective—needs careful management.

Similar risks apply with first-generation implementations of AI-driven customer service bots, which mollify the situation through statements of empathy and generalized responses without grasping and resolving the specific customer issues. Ultimately the customer must escape and talk to a real person. Doing a superficial job with AI dialog construction and machine learning is worse for customer relations than having a caller wait a few extra minutes to access a live agent.

The challenge here is that businesses need to ask themselves what they stand to lose if they don’t deploy new AI technologies well, or if they effectively give up the human touch in favor of AI. Contact center managers and technology providers should also consider how to spur the seamless exchange between virtual agents and live agents to manage the fallout of unsuccessful digital conversations. With this inevitability, the need to deliver an omnichannel solution that can shift between the virtual and living agent becomes apparent, and the customer experience flows smoothly as a result.

Innovation Opportunities with AI in Contact Centers 

AI and software bots have the potential to bring many interesting and innovative opportunities to the contact center. Here are some sample scenarios to envision:

  • Rather than relying on agent skills, knowledge, and experience alone, an AI-driven bot can virtually listen to the customer interaction and silently guide the agent toward a resolution—including questioning and dialog prompts. This allows less experienced agents to do a better job while consuming less off-line dedicated training time.
  • How many times have you struggled to clearly hear what a contact center agent is saying due to ambient noise? Annoying and disruptive background noises on both the customer and agent sides can be isolated and filtered out in real time by AI, allowing for a better customer and agent experience overall, as well as faster resolutions.
  • Call recording is now commonplace. AI can enable real-time transcriptions of calls that are later searchable and more easily processed by analytics and reporting engines for business insights, as well as audited for legal compliance. These transcriptions can also be used to gather intelligence for future use to feed into AI dialog coaching and machine learning in terms of issue identification, effective questioning, and prompts.
  • AI enables customer service software bots to be self-aware, such that a graceful handoff to a human agent can occur as needed for resolution—sometimes without the knowledge of the customer, as in the case of email, web, or text chat. This allows a more natural dialog leading to categorization and routing, as opposed to “press one for service” or selecting topics from preset drop-down menus.
  • The value of agent retention and reduced employee turnover correlates with effective contact center operations and customer satisfaction. By introducing AI, highly valued live human agents can be more engaged and more challenged by novel, complex, and interesting customer situations, as opposed to repeatedly processing routine and predictable customer inquiries or requests that AI and software bots can now handle. 

AI’s Future in Contact Centers

In the near-to-medium horizon, increased adoption of AI in customer interactions is inevitable. Current trends may see contact centers achieve at least one-third AI-based interactions by 2022, yet with a transformation component that will see the live agent role shift from prescriptive and transactional activities to managing deeper customer journey activities in tandem with AI.

Knowing when to use AI will remain an iterative process that must be managed by the right individuals within an organization. Given studies where AI is currently outperforming doctors and lawyers, contact centers need to determine how AI and agents can work in harmony to manage all customers’ situations across all communication media in effective and efficient ways.

Ross Sedgewick fulfills several expert marketing roles in technologies for the digital workplace, team collaboration/customer contact solutions, and virtual team engagement. He currently handles content creation, messaging, and insight development relating to the digital workplace at Atos’ unified communications and collaboration division (formerly Unify).

LisaCampbell fulfills several positioning, messaging, and value propositions functions for Atos’ customer engagement solutions and orchestrated communication services as well as global vision, strategy, and statements of direction for the full portfolio. Lisa is passionate about communication technology and its ability to amplify individual and organization outcomes.

Ignoring Lessons from the Past



By Sherry Gouel

Looking back at previous generations, we’re certain to find things that make us wonder, “What were they thinking?” Of course, the world has changed in the past hundred years, and people have learned ways to improve their lives, their well-being, and their health. Many of these lessons were learned the hard way.

The Past

We learned was that nicotine was harmful to our health and sugar had many negative consequences. We learned these lessons because people suffered from their use.

If you look through any magazines or newspapers circa 1950, you’ll find ads for cigarettes. TV commercials used to show doctors trying to sell viewers on their favorite tobacco brands. Movies of that era included characters prominently puffing on cigarettes in every second scene.

Another less advertised but just as detrimental product was sugar. The advertising may have been more discreet, but the negative effects of sugar weren’t exposed and the sugar industry made sizable profits.

It would be years before society would be enlightened to the dangers of both these items. It would be years before cigarette ads would change from promoting them to informing the public of the dangers of their use. It would also be years before the link between high sugar intake and diabetes would be made public. Although it took many years to get these messages across, we eventually realized our errors and tried to correct them.

We may have come a long way, but that doesn’t mean we’re done learning. What about cell phones and social media—have we stopped to consider the potential consequences of using them? What will the next generation say about our love of this media? Human connections are falling behind our electronic connections, and the consequences won’t be as repairable as other mistakes humanity has made. Click To Tweet

The Present

Cell phone popularity soared around the late 1990s, and it would be hard to find anyone over the age of fourteen that doesn’t have a personal cell phone. Some of the harmful effects are not so obvious, but they are definitely present. We’ve now become a society that spends more time looking at our cell phones than at each other, but instead of trying to salvage our human connections, we find ways to accommodate our world to ease our connections with our cell phones.

Every year, hundreds of thousands of people are injured and some even die due to inattention while texting and walking. The World Health Organization calls this “distracted walking.” In Shaanxi, China, there’s a special lane reserved on the sidewalk for people who walk and text. It allows the people who are distracted as they walk and text to not impede the rest of society. They can simply stare down at their phones and not worry about walking into anyone. It’s a sad reality when we make accommodations to make texting instead of human connections easier.

One of the more troubling consequences of increasing attachment to our cell phones is that for many it has increased the feeling of detachment and isolation. For those who already feel lonely, seeing the world around them staring down at their phones creates more distance than connectivity.

The increase in our ties with technology has increased our isolation. This is particularly difficult for seniors, many who already feel isolated and alone. This demographic isn’t as accustomed to using their cell phones as often as the younger generation, and they prefer human connections, eye to eye.

In the UK, Costa Coffee shops has introduced a concept to help with loneliness. “Chatty Café,” which began in 2017, consists of allocating a table in their cafés for people who just wish to talk to someone. People are encouraged to stop and chat to anyone sitting at that table. This has been very popular, especially with seniors who welcome the warmth of a face-to-face conversation. But once again, we’re attending to the consequences of the problem rather than facing the actual root of it.

The Future

History has taught us some lessons that we have rectified, but our attachment to our cell phones will be a difficult crisis to overcome. We’re spending more time in front of our screens, and this inevitably will continue to have consequences. Human connections are falling behind our electronic connections, and the consequences won’t be as repairable as other mistakes humanity has made. Why? Because repairing our increasing human disconnection will mean putting our cell phones down. And that’s unlikely to happen.

Szeto TechnologiesSherry Gouel handles sales and marketing support for Szeto Technologies.

PCI Scope Reduction Can Save Tens of Thousands of Dollars Per Year



By Art Coombs

High-profile stories of compromised credit cards and data breaches and their sobering aftereffects have dominated the headlines in recent years. As such, increasing security and reducing fraud is on the minds of many business leaders. This is particularly true of call centers, where credit card transactions are at the heart of their operations. These companies are challenged to provide a secure environment to accept credit cards while keeping the associated costs down.

The leading credit card companies set up the Payment Card Industry Data Security Standard (PCI DSS) to help businesses that take card payments reduce fraud. Built on solid security principles that apply to all sorts of data, it covers areas such as retention policies, encryption, physical security, authentication, and access control. According to the Verizon 2017 Payment Security Report, almost half of companies that accept credit cards fail to protect their payment card data on an ongoing basis.

The explanations vary widely as to why this is the case, but one of the primary reasons is the expense associated with maintaining full PCI compliance. In many cases, it’s prohibitively expensive. Fines levied by banks and credit card institutions for not being PCI compliant in the event of a breach can range from five thousand dollars to five hundred thousand dollars, highlighting the need for compliance despite the cost.Two approaches call centers can employ to reduce or even eliminate PCI scope is to use DTMF (dual-tone multi-frequency) suppression and SMS text messaging. Click To Tweet

Companies Face Mounting Costs

PCI-compliance costs add up quickly. Companies can expect to pay handsomely for items such as vulnerability scans, penetration testing, training, and policy development. Overall, there are twelve standards and more than four hundred controls outlined in the PCI DSS.

Often the largest direct expense (aside from remediation requirements resulting from a breach) is usually the PCI assessor and assessment fees, which, depending on the complexity of an organization, cost tens and even hundreds of thousands of dollars each year. These annual and biannual assessments are conducted by Qualified Security Assessor (QSA) companies, independent security organizations that have been qualified by the PCI Security Standards Council to validate a company’s adherence to PCI DSS.

The PCI Security Standards Council maintains an in-depth program for security companies seeking certification as Qualified Security Assessors and recertification each year. The requirements are stringent and comprehensive. Because of the time and energy individuals and companies invest in certification, they are justified in charging a premium for the assessments they conduct.

Reduce PCI Scope and Save Money

The litany of requirements is as costly as it is formidable, but call centers, as well as any company accepting credit cards, need to be aware that there are distinct ways to reduce the burden of applicable PCI controls. This means they can easily reduce the number of areas in the scope of PCI compliance that the company is responsible for. Reducing or eliminating areas of PCI scope can greatly reduce costs now and in the future and still provide a secure system.

Two approaches call centers can employ to reduce or even eliminate PCI scope is to use DTMF (dual-tone multi-frequency) suppression and SMS text messaging. These bypass the agents and contact center infrastructure, going instead directly to a tokenization service provided by the company’s payment processor and acquiring bank.

DTMF represents the tones the numbers on a phone make when pressed. DTMF suppression is a method that enables customers to enter their credit card information using the keypad on their phone. The agent stays on the line and never sees the numbers or hears the tones.

The second approach is to leverage SMS, or texting, so customers don’t have to give their credit card information verbally over the phone to the agent. SMS and an accompanying payment portal are a secure and smart solution for accepting payment for several reasons. Most consumers are already familiar with their mobile devices and SMS. This saves agents from having to explain a complicated web portal and payment screen. The consumer doesn’t need to download an app or go through a credit card terminal to make payments via SMS. SMS payments can be accepted around the world without any agents seeing or hearing the information.

The systems the company uses (CRMs, CMS, and payment systems) receive a confirmation or token validating that the transaction went through, but the credit card data never touches the company’s infrastructure. This greatly reduces risk: the company doesn’t have the credit card data, and it isn’t present, stored (recorded for quality assurance), or transmitted within the company’s systems. This reduces or eliminates PCI scope.

It’s important to note that regarding fraud prevention, even the most robust, 100 percent PCI-compliant environment could still be at risk when human agents, including employees, decide to commit fraud or theft. If they verbally receive numbers over the phone, they can memorize the critical information and then write it down once they leave the office or record the numbers and use them for their own nefarious purposes. In any card-not-present environment, there is risk. These approaches take that risk out of the picture.

Reduce Scope to Qualify for Self-Assessment

By using technologies that employ DTMF suppression and SMS, companies can reduce the scope of what’s required under an assessment so much that they’re no longer required to hire a consultant to conduct an assessment. Instead they can conduct a self-assessment, write a report, and submit it to the PCI council themselves, instantly saving tens of thousands of dollars or more while dramatically improving security.

Art Coombs is a published author on leadership and methodologies for BPOs, contact centers, and technical support. Art has more than twenty-five years of experience with several global firms and their call and BPO centers worldwide. He is president and CEO of KomBea, a fifteen-year-old software company that develops solutions for contact-center environments to help deal with the myriad of regulations and standards they face, including PCI compliance and HIPAA. For more information visit www.kombea.com.

Science and Technology Revolutionize the Customer Experience



Applications that Improve the Customer Journey

By Deborah Navara and Jana Benetti

Recent advancements in artificial intelligence (AI) technology, coupled with consumer preference for digital channels, are driving interest in and adoption of intelligent virtual agents (IVAs) and a related technology, robotic process automation (RPA). Voice biometrics is another high-tech solution that is going mainstream. A leading bank’s recent ad campaign publicizes that they know customers “by the sound of their voice.”

Organizations are starting to leverage these sophisticated technologies to re-engineer service experiences that combine the best of self-service with live agent support, a winning experience for enterprises, who have a fiduciary responsibility to reduce operating costs while also providing a highly effective personalized customer experience.

DMG defines IVAs as “specialized technology that utilizes artificial intelligence, machine learning, advanced speech technologies, and free dialogue understanding to simulate live cognitive assistance for voice, text, or digital interactions via a digital persona. IVAs are self-learning. Their intelligence is continually evolving based on data inputs from each new interaction. The acquired knowledge is assimilated and leveraged in future interactions.”

In essence, IVAs use science to elevate the art of self-service. IVAs are catching on in a variety of verticals, where they serve as personal shoppers, ensure compliance with healthcare protocols, book reservations, schedule appointments, assist with financial or investment decisions, and determine how to manage utility expenses more efficiently.

For agent-assisted interactions, IVAs pull information from knowledge bases, customer profiles, and other online sources that agents need to optimize each interaction. In the enterprise, they are being leveraged to assist with benefits, compensation administration, and other HR issues.

Contact centers are inherently complex environments, and agents routinely must enter the same information into two or more systems, such as a transaction processing system and a CRM solution. This is where robotic process automation comes in. Attended RPA is being used to automate cut-and-paste tasks and for populating the same data in more than one solution.

This greatly speeds up the processing time for customers and prospects, while reducing errors. Attended RPA can also be used to create a composite servicing screen to reduce the number of systems and screens agents need to access to resolve inquiries. And unattended RPA can fully automate some end-to-end contact center processes, with little or no human involvement.

Voice biometrics is another solution whose time may finally have come, as adoption of these solutions by contact centers is on the rise. (Adoption of biometrics in general is increasing.) The primary use for voice biometrics in the contact center is to automate speaker authentication. Once a voiceprint is obtained, it eliminates the need to answer security questions, which may, ironically, contain the same information they are trying to protect. IVAs, RPA, and voice biometrics enhance the customer experience, improve productivity, and reduce the cost of service. Click To Tweet

Security concerns, regulatory requirements, and the pressure to reduce operating costs and improve the customer experience, along with improvements in technology and much faster servers, are paving the way for companies to adopt voice biometrics for customer identification, verification, and e-signatures. The following chart provides a synopsis of how these solutions work and are being used to deliver customer and enterprise benefits.

Technology How it Works Contact Center Application Customer Benefit Enterprise Benefit
Intelligent virtual agents (IVAs) Utilizes AI, machine learning, advanced speech technologies, including natural language understanding, natural language processing, and natural language generation (NLU/NLP/NLG) to simulate live and unstructured cognitive conversations for voice, text, and digital interactions via a digital persona Omni-channel self-service Enhanced self-service; reduced customer effort Improved productivity;

lower cost of service; increased use of self-service solutions; enhanced CX

Robotic process automation (RPA) Leverages AI, machine learning, workflow, and other technologies to emulate the processes performed by human workers; can be trained to adapt to changing conditions, anomalies, and new situations Automating processing of repetitive tasks;

automating cut-and-paste; data propagation across multiple applications; initiating actions and communicating with other systems or employees; agent/employee assistance (attended automation)

Reduced errors; reduced processing time Improved productivity; lower cost of service; improved accuracy
Voice biometrics Compares the unique voice characteristics of a live audio stream to an enrolled voiceprint to authenticate the speaker Fraud and risk mitigation; automating verification; primary component of multifactor authentication; authorizing transactions; legally binding digital e-signature Accurate and nonintrusive authentication method; enhanced data protection; expedited digital transactions Reduced risk and exposure; decreased fraud; enhanced CX

IVAs, RPA, and voice biometrics enhance the customer experience, improve productivity, and reduce the cost of service. They simplify how customers interact with companies in many channels, including phone, interactive voice response (IVR), websites, and smartphone apps to facilitate a consistent and personalized omni-channel customer journey. When planning for the near-term, all companies should carefully evaluate these solutions, as they achieve the primary goal of helping companies deliver an outstanding customer experience cost effectively.

Deborah Navara and Jana Benetti are with DMG Consulting LLC, which helps emerging and established companies develop and deliver outstanding customer experiences.

Best Practices for Surviving a Ransomware Attack


Startel, Professional Teledata, Alston Tascom


By Jim Graham

In 1989 the first known ransomware attack occurred when twenty thousand floppy disks containing malware were distributed to researchers across more than ninety countries. In 2017 Symantec recorded an average of 1,242 ransomware complaints per day, not including the infamous WannaCry and NotPetya attacks. According to a survey conducted by Malwarebytes, one in six organizations impacted by a ransomware attack were down for twenty-five hours or more.

A recent attack on one of our clients was a painful reminder that ransomware continues to be a genuine threat to individuals and businesses worldwide. Our client received the virus upon clicking on a bad link in a “spear phishing” email. Their business was down for twenty-four hours before they were able to process calls.

The longer a business is down, the harder—and costlier—it is to recover. The financial impact can be just as staggering, with one hour of inactivity costing small businesses as much as $8,500. That doesn’t include lost business opportunities or the personnel cost associated with downtime.

Common Best Practices

There are many best practices, tips, and recommendations to mitigate a ransomware attack. The options can be overwhelming. However, you can lessen the likelihood you’ll become another statistic and decrease the impact of an attack by implementing these best practices.

1. Be Educated: Staff training is the first and best line of defense against ransomware. In most cases, systems are infected by user-initiated behavior such as clicking a malicious link in an email, opening an executable email attachment, or unknowingly giving a password to a potential hacker.

Educate staff about recognizing suspicious links and attachments. Phishing expeditions have become more sophisticated and targeted. These “spear phishing” attempts typically include client-specific information you’d assume no one else knows, making them much more believable. Never click on email links unless you’re absolutely certain of the identity of the sender.The longer a business is down, the harder—and costlier—it is to recover. Click To Tweet

2. Be Prepared: No matter how well-trained your staff is, be prepared for the possibility of a ransomware infection. This is where robust system and data backup strategies become essential. It’s critical to backup your data, software, and configuration settings frequently. Without a backup, you could permanently lose data. Create three copies, on two different media, and keep one copy stored securely off-site. Then test all backups to ensure you can successfully recover data.

A detailed incident response plan can make these instances a little less daunting. Take the time to put together an incident response plan, and test it each year. Also, consider investing in a business continuity and disaster recovery solution. These solutions minimize downtime and help ensure customer data remains secure and accessible 24/7.

Finally, in the unfortunate event you’re impacted by ransomware, consider enlisting the assistance of qualified IT professionals skilled at recovering from an attack. They’ll be able to get your company up and running and help minimize the impact on operations.

3. Stay Proactive: Once staff is well-trained and you have a strategy in place, continually monitor other areas of your business that may be vulnerable to ransomware. Implement these approaches to stay proactive:

  • Update operating system patches and antivirus software. On average, Microsoft releases several “critical or security”-related updates each month.
  • Limit administrative rights to only those that need to have them.
  • Deploy strong spam filters that block executable files.
  • Consider using a secure email gateway (SEG) in addition to your email client filter.
  • Set firewalls to block known malicious IP addresses.
  • Lock down your firewall from inside out to prevent data from being extracted.

HIPAA and Other Compliance Implications

A breach caused by a ransomware infection can have significant HIPAA and other compliance-related implications. Whether or not data has been taken, a successful attack is still considered a breach by HIPAA standards. Be sure you’re maintaining backups and log files for all systems that touch electronic protected health information (ePHI), because your company security policies will be subject to review by auditors. Proper HIPAA training is also essential in protecting ePHI.

Disclaimer

No matter how well prepared your business is, you can still be a victim of ransomware. However, following these recommendations will lessen the likelihood and impact of an attack.

StartelJim Graham co-founded Professional Teledata (PTD) in 1993 and served as vice president until the merger with Startel in September 2015. As the CTO of PTD, Jim draws upon his thirty years of computer and software development experience and twenty-three years of call center experience. Startel, Professional Teledata, and Alston Tascom provide unified communications, business process automation, and performance management solutions and services. They leverage their solutions and industry knowledge to empower organizations to improve agent productivity, reduce operating costs, and increase revenues. For more information, call 949-863-8776 or visit www.startel.com.

The Bots Are Coming!



Automated and AI-Driven Programs for Business

By Elena Langdon

Automation and artificial intelligence (AI) are all the rage these days—for good reason. The technology behind once too-good-to-be-true tools like facial recognition and 3-D printing has advanced rapidly. Many of us own or pine for smart devices and use dozens of apps a day for personal purposes. So what about business? How much can automation and AI boost productivity and profit at work? And what are the no-go zones for this exciting area of development?

First, Some Terms

“Automation” and “AI” are often used interchangeably, but there are important differences. Automation refers to processes that can be undertaken through a chain of events that trigger each other without human interference. We’ve seen it in manufacturing for decades. Simple contemporary business examples are Hootsuite or Buffer, programs that help automate a business’s social media participation.

AI refers to machines undertaking processes and making choices on their own, based on their programming and what they learn from it. There are different levels of AI, and the most powerful two—levels at which a machine can understand human thoughts, and be self-aware, respectively—have not been reached. So what can be accomplished now?

The Digital-Assistant Revolution

While C-3PO from Star Wars or Ava from Ex Machina are not in our immediate reality, AI is a driving force behind many business applications.

Personal digital assistants such as Siri and Cortana are good examples of AI-driven programs that can boost productivity, save time, and facilitate our lives. With one of these programs, you can delegate scheduling, play music, and check the stock market, all without typing, thanks to voice recognition capabilities. Pen, paper, and typing can be eliminated from the entire process.

Google Duplex is a more recent digital assistant that takes automation to a new level. It makes calls to humans to schedule appointments, request information, and order food. Instead of speaking with a typical robotic tone, Google Duplex mimics real speech patterns and uses fillers such as “um” and “hmm.” Plus, this bot interacts with human responses and can carry on a conversation. For this reason, its reception so far has included a mixture of awe and trepidation.The more complex the task, and the more it involves human reasoning,the less likely it will work for business. Click To Tweet

Proceed with Care

Caution might be needed for that type of digital assistant, especially from ethical and privacy standpoints. Should a human receptionist know that he’s talking to a machine? Is he being recorded so Google can learn from the exchange? Nevertheless, most of the tasks accomplished by Google Duplex involve little personal risk. If your haircut gets scheduled at the wrong time, it would be a nuisance but not a big loss.

However, you should approach some types of AI-driven programs with caution when it comes to business because of the risks involved. For example, in language translation, the technology can’t yet match the human capacity for communication. Automatic translation engines are great for getting the gist of a letter or website, but using them for business can result in embarrassment, misinformation, and even financial loss.

Most companies put time and money into writing compelling and clear texts; foreign-language copy requires the same attention. Despite recent advances in deep learning, machine translation is not like Google Duplex—it does not sound human, and it’s much less eloquent. More importantly, accuracy is seriously compromised with automatic translation—just think of all the menus with indecipherable items such as “The water fries the potato” and signs saying, “Beware of safety.”

Apply the same caution for verbal translation or interpreting, which has made headlines with programs that combine machine translation with voice recognition. Holding a conversation with someone in a language you don’t know by using “translator earbuds” might work for casual exchanges with inconsequential outcomes. However, if you need to speak to an employee about her performance or to an international branch manager about next quarter’s sales goals, you cannot rely on AI to accurately transmit your message. Between speech recognition flaws, cultural differences, and the incredible creativity behind any human being’s speech, it’s best to stick to a professional interpreter for bilingual business communication.

Lawyer Up or Bot Up?

If creative speech is one reason not to trust the machines, what about legal discourse? Does it make sense for a business to rely on automated contract-writing programs or document-reviewing apps? As with many machine-based applications, such programs can work, albeit in a limited context for limited purposes.

AI-driven programs will review legal documents at a fraction of the cost of a lawyer. This review process takes humans significant time, and lawyers take years to master it, yet computers have apparently learned the skill. That said, even apps’ websites make it clear that the apps will not provide legal advice and should be used only for the specific purpose of reviewing documents.

The formulaic language and boilerplate nature of legal documents lends itself well to AI and frees up time and money for actual legal strategy. In some ways, it’s like translation—you can get some entry-level tasks done, just not anything that requires tactics or nuanced meaning. And of course, nothing involving any risk to your business.

Look Both Ways Before You Leap

So the next time you see an ad for a new app that looks like a miracle cure for what’s ailing your business, by all means, don’t ignore it. There are many good applications for automated and AI-driven programs. Just be sure to research the program and consider its uses. The more complex the task, and the more it involves human reasoning, the less likely it will work for business—at least in an all-encompassing manner. Work patterns and skills are certainly changing, but the bots aren’t taking over just yet.

 

Elena Langdon is a certified Portuguese-to-English translator and interpreter and an active member of the American Translators Association (ATA). The American Translators Association represents over 10,000 translators and interpreters across 103 countries. For more information on ATA and to hire a translation or interpreting professional, please visit www.atanet.org.

Embrace the Intelligent Virtual Agent


Onvisource


The Promises, the Challenges, and the Pitfalls

By Ray Naeini

Adoption of intelligent virtual agent (IVA) or chatbots is a popular topic in today’s industry, as it can offer a broad range of benefits to both enterprises and their customers. A survey published by DMG Consulting in January 2018 showed that “increasing use of self-service” is one of the top three “enterprise servicing goals for 2018.” IVA uses artificial intelligence to automate customer service for chat or audio interactions with customers. It has the potential to operate as, or improve the performance of, live agents. Today’s customers mostly prefer self-service, especially through digital channels. IVA is a promising solution for improving customer satisfaction.

Automation Is Inevitable and Evolutionary

Automation has been a progressive, irreversible, and unstoppable trend. Automation has made drastic changes to our way of living and doing business. A few decades ago, customer service started with live switchboard agents manually connecting customer calls to the right customer service agents. In the 1980s live switchboard agents were replaced by interactive voice response (IVR) that could automatically prompt questions and route calls. IVA is the next evolutionary step in automation, going beyond the IVR functionality. It penetrates deeper into the enterprise organization and further automates various functions of customer service.Today’s customers mostly prefer self-service, especially through digital channels. Click To Tweet

Benefits of IVA

IVA offers a broad range of compelling benefits. It can assist live agents with real-time access to knowledge management systems, improving the quality and the speed of service. In certain cases, it processes customer service requests directly without the need for a live agent. In general, IVA can significantly improve the quality and the speed of the service while reducing live agents’ workload or payroll costs. It also reduces enterprise challenges related to live agent staffing, training, and retention.

IVA is available 24/7 from anywhere and can offer consistent customer service with an unlimited, real-time access to information during customer engagements. It automates repetitive tasks and can assist with or take over sophisticated customer service transactions. It supports multichannel via text-based chat or audio-based interactions. The use of IVA can go beyond customer service to benefit other departments such as sales and marketing for customer surveys or lead generation and qualifications.

Artificial Intelligence Is the Brain Behind IVA

What makes IVA smart enough to intelligently automate customer service is its use of artificial intelligence (AI) technologies. AI is a broad concept that started in the mid-1950s. It promised delivering intelligence similar to the human brain through progressive technological milestones. Advancements in mathematical modeling and natural language understanding, combined with faster and more cost-effective computers, make each technological milestone more capable of offering solutions to real-world problems.

The first two AI technological milestones that provide real solutions are called machine learning (ML) and deep machine learning (DML). The concept is to create mathematical models capable of continuously receiving, parsing, and categorizing a vast amount of relevant or training data to progressively increase the capabilities of the computers in natural language understanding, image processing or recognition, medical diagnostics, and so forth. This is similar to the basic functions of the human brain, as we were born with an inherited ability to continuously receive enormous amounts of data through our senses and then parse and categorize the information.

The use of ML and DML in IVA mainly focuses on natural language understanding (NLU) to converse with customers. In an IVA driven by ML, the data is analyzed and categorized by trying to understand the intent of the data (conversation) and extract the information associated with the intent (called entities) to prepare a response. The more intents and entities are analyzed and categorized, the more intelligent the IVA becomes. The ML approach, however, has certain limitations due to its single-layered analysis. In a DML-driven IVA, the data is analyzed by multiple layers or stages (using technologies such as neural network), and then at the end a collective scoring of the results from all layers is used for categorization.

IVA Challenges and Pitfalls

While IVA can deliver many benefits, it also creates challenges. Experiences related to the deployment of disruptive technologies tell us to avoid the hype of IVA and focus on applying it to each specific application systematically and progressively. IVA requires continuous training using a significant amount of valid and relevant data to improve its accuracy and performance.

We should also remember the pitfalls of early deployment of IVR that created significant customer dissatisfaction and try to avoid those mistakes. IVA deployed in a contact center environment should be capable of seamlessly integrating with the contact center’s overall workforce optimization (WFO).

OnviSourceRay Naeini is the chairman and CEO of OnviSource.

AnswerNet Acquires Synergy Solutions

AnswerNet acquired Synergy Solutions in an asset transaction. Synergy Solutions specializes in high-touch consultative customer service and sales support programs for many of the nation’s leading brands.

Headquartered in Phoenix, Arizona, Synergy Solutions was established in 1999 and focuses on innovative customer interaction solutions. This allows Synergy Solutions to provide superior results for its clients in fast-growth retail and e-commerce, as well as traditional verticals such as healthcare, insurance, and financial services.

Gary Pudles, president and CEO of AnswerNet stated, “Synergy Solutions furthers AnswerNet’s continued growth in high-touch customer engagement space for well-known companies and brands. AnswerNet’s customer care business has been growing exponentially over the last three years, and adding the incredible Synergy team further deepens our strength in providing solutions that help our clients continually stand out in providing support to their customers.”

Synergy’s president and co-founder Lori Fentem is staying with AnswerNet and will work closely with Pudles on building and executing AnswerNet’s growth strategy. Fentem is a well-regarded leader in the contact center industry. “We are thrilled by the opportunity to become part of the AnswerNet family,” says Fentem. “This acquisition allows Synergy the ability to continue to offer high-touch customer experience solutions. I believe that integrating with AnswerNet will present the ideal environment for Synergy employees and clients.”

Automation Success Requires Human Involvement



By Dan Somers

Automation and artificial intelligence (AI) can help save contact center costs, but primarily it increases customer satisfaction by speeding up responses and reducing customer efforts. Contact center automation falls broadly into three categories:

  1. Speeding up or automating the helpdesk agent (staff who capture and triage queries)
  2. Speeding up or automating the case handler (staff who resolve queries)
  3. Increasing self-service automation (chatbots, searchable FAQs, and self-help tools)

AI Challenges

Certain limitations of AI cannot guarantee the accuracy expected by customers, however. Some of these limitations are temporary, such as the comprehension capabilities of speech recognition, which will continue to improve. But other limitations relate to how machine-learning robots work.

All machine learning relies on studying real-life training data to predict or classify current data. The training data needs to be “labeled”—that is, it must have an outcome or class (tag) assigned to it, as judged by a person. For example, if a query comes in that says, “My server has crashed and is showing a blank screen,” then the chatbot will assign the best label it has in its training set, which might be “server crashed.”

However, in this example, a label of “faulty screen” might be assigned instead. The customer would be annoyed if the bot attempted to address a faulty screen issue instead of a server crash. This is an example of potential ambiguity. Furthermore, new issues will appear from new product launches, changes in quality, and evolution in the market. Lastly, the way people describe or view the same problem is more variable for certain issues than others.

Human-in-the-Loop

The only safe way of deploying bots within a contact center is to have a human-in-the-loop. This person will validate what the bots are doing, preferably with minimal impact to the customer.

So, who and where is the human-in-the-loop? It turns out that there are four general ways for humans to validate some or all of the process:

  1. A helpdesk agent can validate suggested responses before sending.
  2. The customer can validate that the response—or the question they asked—was comprehended.
  3. A third-party solution provider can check the performance of the bots and curate the process; this might be an internal or external data science team.
  4. The knowledge base manager can check the bots for satisfactory performance.Automation of contact centers yields promise, although not without humans-in-the-loop to maintain its performance. Click To Tweet

Considerations of Humans-in-the-Loop

There are pros and cons of different human-in-the-loop approaches. Some of these points are technical in nature but have substantial implications.

Agent: Some solutions on the market have AI recommend the next “best response” for the agent. The agents validate the response, not the categorization. For example, if two queries—“The strawberries I bought were tasteless” and “The strawberries I bought made me sick”—both lead to the same recommended response, “We’re sorry; please accept our voucher,” then the categorization models will degrade as they are not being updated with the accurate root cause.

Also, the insight generated by the models won’t allow executives to monitor product quality, design, and usability to then generate the self-service tools that can reduce contact center traffic. With this solution, other humans-in-the-loop will still be required elsewhere.

Customer Validation: If customers provide the required validation, it is scalable, but customers may not like having to correct their original query or the responses. If the query produces a new category, then there must be a process to deal with it. Fundamentally, the system cannot be relied upon with just these humans-in-the-loop.

Solution Provider: This is the status quo for most machine-learning deployments in real-world environments: a data science team, either internally or a third-party, sets up, curates, and retrains the models on a regular basis to maintain their performance. The pros are that these are the only humans-in-the-loop required. The cons are that these professionals are in short supply.

Knowledge Base Manager: This role has the most hidden potential benefit for having a human-in-the-loop. In a nontechnical environment, they will provide business rules on how to handle queries, as well as the training, trouble-shooting guides, and fault tree analysis to resolve issues.

In terms of their day-to-day role, they will be aware of product launches and modifications, but they also can use the rich insight of the labels coming from the contact center (both triage and resolution) to make improvements to both the knowledge base and the process. This includes updating the FAQs so customers can better use self-service. Also, this insight can inform other functions, such as product quality, product design, and customer experience, to help guide improvements.

Optimized Learning

A new approach that only requires a few humans-in-the-loop can exist because of a new technology called optimized learning. This is a form of machine learning that builds models but invites training from a human in such a way to minimize human input and still provide maximum performance. It is ideal for spotting new signals and improving existing ones.

Optimized learning doesn’t need to be in-line and suffers from none of the downsides of other approaches. Instead, it requires a fraction of the labeling otherwise required, even in a changing environment. The implications of this are profound. It means that a call center would only need to retain a few agents after the automation implementation, and they would handle the training that the optimized learning invited them to do in an offline capacity. This would maintain the models for labeling queries to generate both automation and insight, thus speeding up and reducing issues.

The rest of the automation would come from the rules originating from the knowledge base manager, as informed by the bots. This paves the way for improving chatbots and self-serve, searchable FAQs to free up contact center staff.

Conclusion

Automation of contact centers yields promise, although not without humans-in-the-loop to maintain its performance. There are many different flavors for human-in-the-loop AI automation. With new technology appearing, an optimized system is possible with a minimum number of humans who don’t need any data science skills. There is now no reason why the contact center of the future needs to look like those of the present. The same applies for the customer experience too.

Dan Somers is the CEO of Warwick Analytics, which provides call center automation solutions to address voice of customer (VoC) data, chatbots, service desks, and complaint handling.