Contact Management Magazine Issue 4 2017

THE CUSTOMER EXPERIENCE MAGAZINE ISSUE 4 • 2017

The Technology Issue ❯❯Call centres 2.0 ❯❯GTACC Awards 2017 ❯❯Machine learning gets approachable

The Technology Issue

Call centres 2.0 AI and real-time analytics represent next-gen tools for success

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Issue 4 • 2017

The Technology Issue

By Rajesh Nambiar

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n the 1957 movie, The Desk Set, Katherine Hepburn’s character, a reference librarian, fears that a new fangled computer will replace her and her colleagues. Well, 60 years later, replace The Desk Set’s mainframe computer with today’s artificial intelligence and the same unfounded fears abound.

Artificial intelligence (AI) is being applied in a range of applications and industries—just about everywhere data-supported decisions need to be made. Considering the amount of data most companies collect on their customers, it should not come as a surprise that call centres are one of the latest applications. And why not? Companies see AI as a way to enhance the functionality of their call centres from “customer service” to “customer engagement” via the newest technology.

It’s not just semantics. The difference between “service” and engagement” is huge when vying for loyalty and revenue against an onslaught of competitors. Marketers are realizing that no amount of advertising can effectively compete with the ability of a well-informed customer engagement representative to guide a customer through a product issue or purchase decision.

Recognizing they need to refine their strategy, enterprises are turning to data science to transform their businesses into real-time predictive enterprises. Customer service call centres, those all-important nerve centres where thousands of customer interactions happen daily, should be a priority for implementing AI and machine learning systems to allow customer service representatives to respond to customers and prospects in near real-time, powered by analytics from both historic data as well as current data as it flows in. Any enterprise that does not have the ability to sense customer intent, nor the tools to influence and engage in near real-time, will lose customers and prospects as short windows of opportunities close.

The technology is not entirely new. Most consumerfacing enterprises have long collected data on customers and even prospects. Predictive analytics and business intelligence have been around for two decades, but these systems have become more affordable now and the element of real-time prediction and contextual intelligence has made it even more valuable for enterprises. AI, machine learning and real-time voice-to-text technologies are the relatively new technologies on the scene—at least in a format that is now accessible for commercial use.

At Xavient Information Systems, we offer AMPLIFY, a real-time, AI-powered, speech-to-text transcription and omnichannel customer interaction engine—to enable businesses to achieve positive business outcomes: • For customer service reps, the technology increases productivity, job satisfaction, first time resolution; • For those tasked with client satisfaction and retention, it allows for proactive outreach to dissatisfied customers, reducing churn; • For marketers and sales pros, the technology allows for identifying personalized upsell opportunities; • For the help desk department, it allows for better diagnoses of problems and issues, and more efficiency; and • For smart digital assistants and robots at homes, it provides for real-time updates, chores and assisted living.

The best Big Data solutions begin with an ability to capture and aggregate data, including countless threads of Issue 4 • 2017

customer interactions—whether it is chat, tweet, email, voicemails, voice transcripts, payment habits or logs and social feeds—into a single, allencompassing data stream on which companies can mine information to better serve customers.

One of the foundations of such systems is real-time, voice-totext transcription and analytics and dynamically driven business processes fine-tuned to drive next best action. Relying on notes is not enough. These systems record customer calls, transcribe them and analyze keyword content in order to determine customer disposition, concerns and sentiment. Consider that typically 60 million hours of conversations are recorded every day in call centres worldwide. Buried beneath these myriad calls lie their customer needs, wants, concerns and issues. But this wealth of information largely remains untapped due to technology constraints and the high cost of infrastructure and software licensing.

Obviously, collecting the data isn’t enough. What companies do with it will determine winners and losers in the marketplace. AI and machine learning algorithms are the key. In systems such as Xavient’s AMPLIFY, the more CSR-customer interactions, the smarter the system becomes, improving suggested troubleshooting techniques and even offering alternative or additional products and services where appropriate. We have worked with clients to develop a system in which the machine deep learning analytics algorithms feed recommendation engines capable of delivering real-time coaching to achieve the optimal customer interaction.

Some of Xavient’s major clients have successfully deployed AMPLIFY to automate the process of collecting and mining large volumes of digital data from multiple channels/ customer touch points and gaining contextual intelligence to improve operating efficiencies, reduce customer churn and drive up their Net Promoter Scores—a direct indicator of customer experience.

One such client is bringing down both CAPEX/OPEX in their call centres, which typically receive more than a million calls per month, while improving customer experience by being predictive and solving

customer issues over the phone, thus reducing the need to send technicians into the field.

Call centres usually record about 10-15% of all their customer calls and perform quality assurance on one per cent of those calls due to high cost of voice processing infrastructure.

Historically, such systems were prohibitively expensive due to complex infrastructure required for real-time systems, computing, analysis and storage. New technology solves that problem by capturing the full voice of all their customers and acting contextually with “next best” action. These services are available via an on-demand subscription or usage-based utility payment model which costs a fraction of traditional in-house voice infrastructures.

We believe companies can differentiate themselves by elevating the experience they offer customers and enhance their profitability through automation and reducing the cost to serve. Just about everything else—even the products sold to consumers—has been commoditized. AI and machine learning platforms can deliver a new level of actionable insights into customer interaction and experience, enabling businesses to not just react to a problem or opportunity, but to seize opportunities and avert threats as the situation is developing in real-time. This solution not only provides the ability to attain precise insight into what is actually happening with a business at any moment, but goes one step further by generating and delivering contextual intelligence to employees on the frontlines, including actionable recommendations while they are interacting with the customer to steer the transaction to a successful outcome, which results in a happier customer, reduced cost to serve and higher customer life-time value and share of wallet.

Rajesh Nambiar is senior vice president of North American Sales for Xavient Information Systems (www.xavient.com), a leading IT digital solutions integrator headquartered in Simi Valley, Calif.

Rajesh can be contacted at rajeshn@xavient.com and on twitter @rajeshnambiar

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GTACC Awards

From left to right: Carolyn Beatty, VP, direct operations at Sonnet Insurance; Neal Dlin, chief customer obsessed guy at Sonnet Insurance; Elizabeth Sedlacek, director, operations at ContactPoint360; and Asad Mirza, CEO of ContactPoint360.

Sonnet Insurance wins the Service Sustainability and the Customer Centricity Awards

By Sarah O’Connor

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s Canada’s first fully online home and auto insurance experience, Sonnet Insurance’s mission is to provide Canadians with an easy, transparent and customized way to buy home and auto insurance online. Using sophisticated analytics, modern technology and deep consumer insights, Sonnet offers a simplified quoting and buying process for home and auto insurance that literally takes five minutes or less. After answering a few simple questions, Sonnet customers receive a personalized quote and can purchase their policy online anytime, on any device.

While Sonnet offers Canadians the ability to select, manage and change their insurance without having to speak with anyone, when customers do need help Sonnet’s 360-degree view and universal agents allow for a seamless omnichannel experience. With two locations in Toronto and Montreal, their team of licensed insurance Customer Service Heroes offer coast-to-coast support. The teams consist of customer-facing teams (Customer Service Heroes, Team Leaders, Team Managers) and support functions (Workforce Management, Reporting, Training, Quality and Communications) offering full self-serve as well as phone, email, chat and social support with more to come in 2018. All of this flows through a single CRM and all Heroes work in each channel enabling a true seamless omnichannel experience.

Sonnet Insurance has earned the 2017 Service Sustainability Award for demonstrating a culture of service counts and strategies to ensure the highest level of

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service is delivered at every interaction. Sonnet has also won the 2017 Customer Centricity Award for delivering an integrated and proactive customer experience strategy backed with demonstrated results of measuring and improving the overall experience regardless of channel in near real time.

“You can create some level of consistent service without being customer centric, I suppose, but for us, we built the entire organization around the customer—all of our processes, the technology, all of our hiring, our culture is all based on people who are fundamentally focused on our customers,” explains Neal Dlin.

“Our purpose as a company is to change how Canadians feel about insurance. That means we have to change how Canadians feel about customer service, about contact centres. How do we do that? We focused very simply on what were our customers telling us, that’s one of our two key metrics, and we focus on what we call our H.E.R.O.meter.” The H.E.R.O.meter is a proprietary metric of which Dlin can’t share all the details, but essentially it is designed to measure not what an agent said to a customer but how they said it.

“It’s nice to be recognized by a group like GTACC,” says Dlin. “It’s recognition from our peers that we’re doing something right and that means a lot to us. We look at what our customers are telling us all the time, we already have that information, but its nice to see that our peers feel like we’re heading in the right direction. The truth is we’re far from ones to rest on our laurels. There’s so much more we haven’t yet done and want to do.”

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GTACC Awards

GTACC annual conference and awards hosts Heather Arthur and Mike Aoki.

ContactPoint360 wins the Giving Back Award

By Sarah O’Connor

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ontactPoint360 (CP360) is a growing organization with over 400 employees in four state-of-the-art contact centres—two in Ontario, one in Quebec and one in South America. CP360 delivers customized solutions that fit their clients’ business model while improving efficiency, customer satisfaction and retention.

Their solutions include retention programs, customer service, back office processing, telemarketing and sales, sales support, collection management, fundraising, customer surveys and analytical support.

The Giving Back Award recognizes contact centres that put their time, energy and heart into giving back to their communities. It can be as small as a bake sale in the cafeteria to organizing a centre-wide CN Tower climb.

CP360 was selected as this year’s winner for enabling employee-driven giving back campaigns across a wide spectrum anchored by a corporate culture of giving back.

CP360 dedicates a portion of all revenue to their AQLA Foundation, which supports community involvement and donations which are at the heart and soul of CP360.

This is a private foundation named after the mother of the founders, Aqla Mirza. This foundation operates with a global outreach supporting people and families in crisis to help them through difficult circumstances.

CP360 CEO Asad Mirza credits his mother, who passed away due to breast cancer 15 years ago, with settling a strong example of giving back. “She was very involved in her community, helping the neighbours out,” recalls Asad fondly. “She never said no to anybody.” Because of her

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example Asad and his brother decided that a portion of all revenue would go back to their community.

Over the past several years, CP360 has contributed above and beyond to annual food drives in their communities, including volunteering employees’ time.

The company is also proud to participate and donate gifts to Holland Bloorview Kids Rehab Hospital, volunteer time and gifts for St. Marcellinus Secondary School in Mississauga in order to help 10 underprivileged families and time and money to Cathedral Church in St. Catharines, assisting in serving food to the less fortunate.

“Our employees are proud to serve our community and are willing to spend time outside of their work commitment to help those in need,” says Elizabeth Sedlacek, director, operations at CP360. “In 2015, we sent a team with equipment and medical supplies to Asia providing a free eye exam and medical treatment to thousands of underprivileged people and children. We feel so blessed to be fortunate enough to help those in our world who are less fortunate.”

“Thank you, thank you so much, this means a lot to us,” said Asad in response to this recognition from GTACC. “I’m committing more than ever before to give back to our community.”

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The Technology Issue

Machine learning gets approachable

By Holly Simmons

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rganizations are finally cutting through the hype and adopting artificial intelligence, machine learning in particular. According to The Global CIO Point of View, nearly nine out of 10 CIOs already use machine-learning technology or have plans to adopt it.

Investments will double in the next three years as leading organizations turn to advancements in machine learning to drive faster, more accurate decisions that fuel digital transformation.

A shortage of talent has hindered adoption. Building practical applications of machine learning has required highly skilled data scientists. Recent analysis shows that the demand for data scientists outweighs the supply. In fact, 47% of CIOs reported that they lack the budget to hire or train employees with new skill sets.

How can organizations realize the benefits without incurring the high costs?

The customer service case for machine learning One area of the business that is ideal for employing machine learning to boost efficiency is customer service where, according to Accenture, agents spend as much as 12% of their time manually categorizing customer service requests. Manual categorization, prioritization and assignment leads to human error as well as long customer wait times. Machine learning also benefits customers directly by simplifying categorizing when they make service requests. By routing cases automatically via a system employing machine learning, each request can be analyzed more quickly and sent to the correct area for resolution.

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Additionally, machine learning helps to reduce escalations that occur as a result of improper case classification. The beauty of this approach is that agents can spend less time on tedious repetitive functions freeing up their time to focus on delivering greater value to their customers. The results are faster resolution times, lower costs, more satisfied agents and happier customers.

At ServiceNow we have deployed machine learning in our own customer service centre, which handles 13,000 incidents per month.

In two months, we saved more than 315 hours.

Reducing the adoption hurdles Why is machine learning now a more approachable reality? In the past, use of machine learning required an army of data scientists, deep familiarity with your customer data and great expense to make it successful. Now new solutions exist that incorporate machine learning into a platform off the shelf ready for simple implementation. With the machine learning models baked

into the product itself, you can take advantage of a system that adapts to your needs without the costly use of hiring or training an in-house data scientist.

Such a system can help categorize requests in near real time, refining its accuracy as it is exposed to more examples. It can eliminate the bottleneck of support agents having to manually deal with each request or forcing the customer to choose an option from a long list to classify their need. The end result is more efficient use of time for customer service agents and increased customer satisfaction.

Machine learning is paving the way for more efficient business operations but it doesn’t require an expensive investment in talent to reap the benefits. The results can also pave the way for other machine learning initiatives throughout the organization to further improve processes and the bottom line.

Holly Simmons is senior director of product marketing at ServiceNow.

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The Consultant’s Corner

Head in the Cloud?

Here’s some dating advice for you

By Emily Nielsen

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ometimes a woman may lie about her age to initially attract a man. And sometimes a man may inflate his job title to initially attract a woman. And similarly, a salesman pitching Cloud services may sometimes say things just to initially attract you. He may say things about what his Cloud service can do while skirting around what it cannot do.

Being able to expose these shortcomings sooner rather then later is like the difference between finding your soulmate or getting married to a stranger in Las Vegas.

And marrying a stranger—someone who isn’t your ideal match—would be disastrous.

So then, if you’re serious about finding the right match for your organization, then consider me your Cloud-service match-maker. Here are three simple things you can do to see through the seduction:

1. Uncovering reality: Kraft Dinner and bingewatching Netflix Perhaps you’ve dated someone who claimed they love to cook; however, upon getting to know them better, you discovered all that they could cook was Kraft Dinner. Or perhaps you’ve dated someone who described themselves as “active”; however, soon after you realized that the only thing they actively did was binge-watch Netflix.

This annoying phenomenon isn’t exclusive to dating.

It’s alive and well in the world of choosing the right Cloud provider. So, to get to the bottom of what your Cloud service does and does not do, request a trial!

After all, in the Age of Cloud, when all the hardware is in the Cloud, it should be relatively easy to trial their services. Right? So, if you propose this idea to a potential Cloud provider, they should take you up on the offer. If they advise you that a trial isn’t necessary, I’d consider that a warning sign.

Ask for a trial. Start playing with their product. Try the features. View their training material. Test their support.

Discover for yourself, firsthand, if there are any drastic discrepancies between what they say they can do and what they actually do.

2. How to avoid a major marriage mismatch Okay, you’re looking for a spouse to spend the rest of your life with. If you’re doing that, you would (I hope) carefully consider not only who that person is, but what their plans for the future are.

Where do they see themselves in two, five or 10 years’ time? Do they want to live in the city or the country?

Do they want to buy a house or rent an apartment? Do they want a career or to stay at home? Kids or no kids?

In short, much like in marriage, you should figure out if you and your Cloud-provider are heading in the same Issue 4 • 2017

direction (regarding their features, functionality and support).

To do that, the first thing you’ve got to do is begin dialing in your vision because you can’t make sound decisions without a clear sense of direction. What’s your organization’s long-term vision? And what’s your contact centre’s plan to make this a reality?

Second, get your vendor to share their vision. They should be able to paint a clear picture of where they are going with their service. If they can’t articulate this and have no documentation to substantiate their claims then consider this is another warning sign!

Third, if they have a vision, begin comparing it to yours. Ask yourself: How does it align with your organization’s vision? How does it compare to your contact centre’s plan? Ultimately, are the things that are important to you on their list?

If not, now is the time to run for the hills!

3. Do this if you’re serious about marriage If you’re serious about “marrying” (partnering with) a vendor then you must call on and talk to their reference accounts. And I mean REALLY talk to their references. I’m not talking about calling references for the sake of calling references just to get a glowing recommendation.

Here I’m talking about asking meaningful questions. Well thoughtout questions that serve a practical purpose. After all, their references may indicate that they’re a great “date”—a wonderful company and product. But, is the vendor’s solution the one that’s right for you? Before you call a vendor’s references, I recommend developing a list of questions.

This list should be composed of questions and concerns coming from two sides of your organization.

From one side, gather questions

coming from your business units.

These questions should be aimed at uncovering and developing your business use cases. For example, these units may have questions like, “How easy is it to pull reports from the software?” and “Was X, Y, Z wizbang feature worth the investment?” etc. The point here is to ask questions that uncover the things which are meaningful to your business.

The next line of questions should be developed by your IT department.

They may be questions such as, “How much time and effort did it take to get the solution up and running?” and “What technical difficulties did you have?” and “In what ways does the vendor help you support the system?” and so on.

Seeing through a seduction in three steps In summary, if you’re serious about finding the right match for your organization and contact centre, then carefully consider and closely follow through on my match-making advice.

In a nutshell, here’s my three-step summary: 1. Confirm their features and functionality by requesting a trial.

2. Validate their vision and then compare it against yours.

3. REALLY talk to their references.

By doing these three things you’ll discover who you’re really going to partner with and whether that partnership will stand the test of time or not.

Emily Nielsen launched Nielsen IT Consulting in 1999, a consulting firm focused on helping organizations achieve breakthrough results using contact centre and unified communication technologies. If you’d like such rewarding results you’re encouraged to contact Emily at enielsen@nielsenitconsulting.com or by calling 519-473-5373.

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