Contact Management Magazine Issue 4 2018

THE CUSTOMER EXPERIENCE MAGAZINE ISSUE 4 • 2018

The

Technology Issue

❯❯Specialized service: the future of contact centres ❯❯How to deliver an impactful omnichannel experience ❯❯Filling the CX gap ❯❯Chat before you bot

Technology

Specialized service: the future of contact centres

By Matthew Clare

I

n our data-driven world the need for more effective automation and personalized customer experiences is greater than ever. In some cases, a company’s customer experience journey may be even more important than the actual product or service.

Today, contact centres are crucial with Millennial buyers who expect companies to have context on their customer experience journeys. The last thing consumers want to do is pick up the phones and talk to someone— especially after waiting on hold for at least 15 minutes or more—to explain their issues.

The right contact centre model, with the necessary tools to understand customer interactions and provide the best ways to respond, is therefore critical for positive consumer experiences and the retention of customers.

Offer a cohesive experience People today expect the omnichannel experience, even if they aren’t familiar with the term. Customers may interact with companies on their web sites, via social media or in-store. In turn, companies need to deploy the right mix of tools that integrate these touchpoints and can move seamlessly between them in order to meet customer expectations.

It’s no longer enough to look at these as individual interactions; instead, they must be viewed with a more holistic view. This is imperative for the success of the integrated omnichannel experience.

Some omnichannel contact centre tools now leverage artificial intelligence (AI) and machine learning, and for good reason. People now expect agents to be technologically savvy specialists who can resolve problems when they get on the phones to talk or interact over chat tools, as opposed to being connected to generalists who can only speak to company solutions. If the agents are equipped with AI and machine learning solutions that support customer service efforts, they will have more time to provide a deeper and more personalized and ultimately more satisfying experience for the customers.

Accuracy: AI versus agents Accuracy is a key consideration—but also a challenge— when it comes to integrating technology into the customer experience. Automated customer experience technology with an accuracy of at least 95% is essentially delivering the same level of accuracy as a human contact centre agent.

Given many customer support questions are relatively standard, basic interaction ownership can shift to an AI or machine learning-powered solution that handles the response. This lowers overall customer interaction costs, while allowing the human agents to spend more time handling complex support inquiries. The budget allotted for building a contact centre support team can then be better spent on hiring and compensating technologically 2 | Contact management

savvy specialists who are deep customer experience experts, and who will provide more valuable troubleshooting and interaction for complex customer issues.

This is the main reason Mitel’s partnership with Google Cloud works for today’s evolving contact centres.

Mitel can now provide smarter and more accurate virtual agent solutions through the power of Google Cloud’s Contact Center AI, including natural language processing and machine learning technologies.

As more companies implement virtual agent capabilities over time they will reposition their centres to focus on more specialized support, rather than generalized service.

Companies will then experience reduced costly agent churn as the work becomes more satisfying, while the size of contact centres can be lowered; both factors will net cost savings and productivity gains that outweigh the increased wages for the higher-skilled staff.

Consistency is critical Another major contact centre innovation being developed by Mitel, with the support of Google Contact Center AI, is Agent Assist. Agent Assist uses AI to feed information to support agents—think of it as traditional whisper coach functionality being done by AI rather than a live supervisor—which is particularly valuable considering contact centres have some of the highest turnover rates. With average handle time remaining a top contact centre metric, Agent Assist allows new agents to onboard faster and deliver more consistent and effective information to customers.

There’s nothing more frustrating than finally getting through to someone: only to realize they just started the job two weeks ago, have limited knowledge and are unable to resolve your issue. Agent Assist helps reduce these incidents by providing a more seamless and consistent contact centre experience, regardless of how experienced the agent is. It

also allows companies to improve their knowledge bases for all workers, so agents can consistently provide the most accurate interaction data for a specific customer problem or situation. Agent Assist is a valuable training tool and also provides consistent quality assurance for experienced agents as well.

In addition, more and more contact centres are integrating analytics and real-time reporting into their systems, enabling companies to make data-powered decisions to satisfy the needs of their customers.

Using data companies have already collected on their customers they can provide more intelligent customer experiences that remain consistent across every product or service level.

This is a key feature of Mitel’s MiCloud Engage Contact Center, which was released in late August 2018 for the U.S. market and is planned to be available globally in 2019.

Deliver a proactive experience The last challenge—and opportunity —for contact centres is delivering proactive customer experiences.

Contact centres are historically reactive. A customer buys a product, they have an issue with it and they call the customer service line for assistance. By harnessing the Internet of Things (IoT), companies can leverage data on customer usage and behaviour patterns to deliver proactive support. This means getting ahead of the customer to deliver solutions before they even know they want or need them. In other words, companies should be delivering the information customers need before they ask for it.

A company’s greatest strength today is their understanding of the customer journey. This entails having specialized contact centre agents complemented by technology that can deliver an exceptional omnichannel customer experience.

Matthew Clare is director of contact centre solutions, Mitel (www.mitel.com).

Issue 4 • 2018

Technology

How to deliver an impactful omnichannel experience

By Rebecca Martin

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rand loyalty is cultivated when companies continually adapt to changing customer preferences.

Today, those preferences rest largely on the availability of digital self-service options. Grocery stores now allow consumers to order items and pay directly from mobile apps, while ride-sharing services make it easier than ever to get refunded for poor experiences.

Customers are increasingly communicating via digital channels and these interactions are expected to overtake voice interactions. As this trend continues into 2019, brand loyalty will be defined by a company’s ability to deliver such options seamlessly.

To meet increasing digital expectations, companies are scrambling to set up new self-service channels: but without ensuring that a strong internal infrastructure is in place. This neglect leads to chaos. A recent report from Calabrio, The Danger of Digital, found that 93% of business leaders think it’s important to provide a seamless, quality experience across all channels; however, less than half think their companies are very effective at doing so.

To keep up with rapidly changing customer demands, companies must slow down and take a step back to optimize the entire process.

First, they must understand what channels their customers are on and audit their existing strategies to ensure these align to customer preferences. Second, they should establish strong internal frameworks and align data sources and people to ensure support for the omnichannel strategy.

Here are three ways companies can deliver an impactful omnichannel experience: 1. Rethink staffing and training. Not all channels should be treated the same. As companies rush to add new self-service options, they are failing to deliver a superior customer experience across those channels. While more than half of business leaders say adding a new channel is easy and they have a set process in place to follow, if those processes don’t involve channel-specific training and onboarding agents won’t be set up for success.

A strong omnichannel customer journey requires seamless and positive interactions across all touchpoints, from start to finish. With the contact centre operating as the nucleus for the customer experience, contact centre agents should have specialized skill sets to support these individual channels. While some agents are strong at engaging with customers via phone their skills may not transfer to chat-based interactions.

Through channel-specific training, companies can equip agents with the tools they need to deliver the best possible experience. And, by applying quality assurance (QA) methods across all channels, they can identify agents’ areas of strength and assign Issue 4 • 2018

them to the channels where they’ll see the most success.

2. Analyze the data. Adding a new channel should be justified by showing how it will benefit the overall health of the company.

Simply deploying digital self-service options because competitors are doing so, or a company executive wants to be there isn’t reason enough.

While just under half of leaders say direct feedback from customers is why they added channels, numerous other influential factors come into play. These include input from senior decision-makers, data and analytics, industry and media discussions and pressure from internal stakeholders.

And there’s another issue: 43% believe customer forums and surveys give them a good understanding of how people view their ability to provide a consistent quality experience.

However, such measures of success are often biased and offer incomplete views of the full customer story.

Instead of looking at individual metrics from disparate sources, companies should take a comprehensive look at the customer journey.

The contact centre is the one part of the company that touches every customer channel and can act as a centralized hub for such data and insights. Contact centre data allows them to understand how customers communicate and the channels they’re interacting with the most. With the help of analytics, companies gain insights that can be used to improve service and enhance sales and marketing across channels.

3. The right technology. An omnichannel strategy is only successful if the right technology is in place. Utilizing analytics solutions that

integrate new data sources allows companies to quickly and easily establish new channels without disrupting existing processes and monitor each channel’s activity.

By incorporating insights from across all touchpoints, companies can ensure all departments have a consistent view of the customer journey to drive business direction.

Digital self-service options are popping up left and right as companies try to get ahead of the changing customer experience: and the competition. However, omnichannel success depends on a company’s ability to incorporate channels and insights across the organization. By taking a step back, companies can create a seamless channel experience that delights customers and moves the business forward.

Rebecca Martin is chief marketing officer, Calabrio (www.calabrio.com).

Calabrio recently released a new version of its Calabrio ONE enterprise workforce optimization (WFO) and engagement suite. Here are the highlights: • Improved workforce management (WFM) features, including advanced forecasting improvements, sophisticated prioritization rules to ensure proper scheduling and improved schedule creation options; • Easier and improved administration including simplified user administration, improved network capacity management for on-premises deployments, system monitoring coupled with proactive server maintenance processes and closed loop performance management notifications; and • The latest evolution of speech analytics, significantly improving transcriptionbased speech recognition and analysis.

Calabrio customers can transcribe audio at up to 150X speeds and benefit from a significant boost in speech recognition accuracy while seeing a reduced overall hardware footprint and total cost of ownership.

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Technology

Filling the CX gap

By Jonathan Eisenzopf

E

nterprises are finding themselves in a constant state of digital transformation. They’re looking for the best ways to meet the needs of their customers in the channels that are most meaningful to them at any given time. Many executives will say that, as a result of these efforts, they feel their companies are doing a pretty good job in the area of customer experience.

But when you talk to their customers, you’re likely to get a completely different story. A recent study by PwC revealed that only 49% of U.S. consumers say companies provide a good customer experience today1. It’s clear that companies are consistently failing to keep pace with the expectations of customers, resulting in a widening gap between them when it comes to delivering a truly effortless experience across channels.

Knowing that they must compete on the basis of the customer experience (CX), companies have embraced customer analytics, launched new channels, such as chatbots and they are beginning to enjoy the business applications available to them with applied artificial intelligence (AI). But still they fall short.

The tangled infrastructure

bot developers: and fails to deliver truly natural interactions with the customers that actually solves their problems.

Another side effect (and a potential opportunity) of this “piece part” approach to CX is that a business’s customer conversation data—a leading indicator of where and why a brand is succeeding or failing—isn’t integrated into core customer-facing solutions, especially as they cross functional lines. That’s because there has simply been no systematic way to do so.

There are upwards of millions of valuable historical and ongoing

Companies are consistently failing to keep pace with the expectations of customers.

Courtesy Discourse.ai

One factor making customer success elusive is that the typical enterprise CX infrastructure connecting customers to automated and live agent applications has become a

tangle of third-party software and hardware components. As technology innovations like chatbots become available they are grafted onto the CX “systems” like CRM, IVR, and other contact centre voice and customer analytics applications, but often with unintended and less than optimal results.

Much like working on a car as you simultaneously drive it down the Autobahn, the outcome is not likely to be the desired one. Highly anticipated “add on” chatbot development platforms are typically immature and require (costly) time-consuming and tedious manual tasks of the

4 | Contact management

Issue 4 • 2018

Courtesy Discourse.ai

Technology

multichannel conversations that are recorded and archived in databases with no connection to operations or CRM or enterprise resource planning (ERP) applications. They’re just waiting to be taken advantage of, but the task of consolidating that data into holistic conversation data repositories that can be leveraged for analysis, decisionmaking, and real-time and proactive communications has been elusive. That is because companies are faced with the massive challenge of organizing, classifying and managing so much unstructured data.

Conversation data democratization The problem waiting to be solved is to provide true conversation data “democratization”, whereby all of those valuable conversations, are available universally and immediately for analysis and insights across the business.

They hold rich information about a business’s customers, products and the actions of customers and the business that drive revenue, retention and churn.

Here’s an example. A large payments company has committed resources and budget for an eight-month project just to establish a customized ontology (database schema) and to transcribe and annotate a portion of their conversation data. However, this means they won’t be seeing and applying the value of that data for nearly a year.

Can they really afford to wait this long?

We believe conversation data is an increasingly critical enterprise asset with value that is on par with intelligently integrated ERP and CRM platforms. But how best to take advantage of this unstructured data? What can be done to speed the time to value of the very words customers have shared?

We recommend a fresh approach to address these challenges so businesses can finally benefit from the value of customer conversations across any business systems: • Leverage conversation- and domain-specific ontologies as contextual schemas to inform the structure of a Conversation Data Hub (or Hub). The Hub is a graphical database that serves as the system of record for all customer conversations, regardless of source and structure; • Ingest the company’s historical conversations into Issue 4 • 2018

the Hub and enrich them using a semi-supervised annotation process to create a semantic conversation graph; and • With all of the conversations now available in a structured format, data scientists, business analysts and bot developers can query the Hub to see the patterns, dominant paths and dialogue flows aggregated across millions of conversations (e.g. live chats, voice calls, bots). This functionality will aid them in their analysis and development efforts.

Applying new approaches The Conversation Data Hub is the core of our overall Cognition Platform, which permits conversation democratization. The platform also has a Cognition Dashboard that includes an Annotator tool, which simplifies and speeds the annotation process for training the conversation model and a Conversation Insights tool for use by data scientists and business analysts.

The initial focus of the product is on the analysis, design and development of chatbots. For example, Conversation Insights provides the ability to visualize millions of conversations, see the dominant paths and even drill down on a conversation type to explore the flow in more detail, providing great insights for bot application design.

Once a business has identified and prioritized opportunities for automation with the help of

these new conversation insights, integrations of Cognition with leading bot development tools (e.g. IBM Watson, Google Dialog, Salesforce Einstein) help to simplify and speed the bot development process.

Finally, Cognition’s Runtime API can be used to help guide bot responses in real-time conversations with customers, providing next best intents or responses that are based on a statistical analysis of the millions of conversations in the Hub. Our vision is to fill the CX gap with the Conversation Data Hub, a single system of record for customer conversations. With the Cognition platform, businesses are finally able to leverage all of those customer conversations to inform the delivery of a proactive and personalized experiences for the end customers.

And the rich insights that are typically inaccessible to businesses are available for use in the strategy, design, development and execution of intelligent self-service. The Conversation Data Hub creates the foundation for a true data-driven approach to the customer experience and business insights.

Jonathan Eisenzopf is CEO and founder, Discourse.ai (www.discourse.ai).

Jonathan is an expert in the semantic web, structured and unstructured knowledge extraction, speech recognition and natural language conversational systems.

1 David Clarke and Ron Kinghorn, “Future of Customer Experience Survey 2017/18”, PwC, survey.

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Technology

Chat before you bot

By Marie-Louise St-Jacques and Eric Dauphinais

T

echnology has never evolved at such a rapid pace. Newly implemented solutions can become obsolete or dated in an instant. The panic of being left behind has many companies adopting new technologies for the sake of newness, with little thought as to why these solutions are needed, how they can be best used or how they should interact with other critical applications.

In 2018, artificial intelligence (AI) reached critical mass attention with just about every tech company announcing 6 | Contact management

the launch of AI enabled solutions and partnerships with AI institutes.

Working in Montreal, a world-leading AI hub, it’s impossible to ignore the enormous potential benefits of the technology.

One of the AI solutions gaining in popularity are chatbots. Chatbots instantly handle routine and repeatable customer contacts, freeing contact centre agents to manage more complex sales or service inquiries. As a consumer,

you have likely interacted with an AI chatbot without even realizing it.

Google Home, Siri, Alexa and within the contact centre space, Genesys’s recently-launched Kate and Nuance’s Nina, are examples of integrating AI to customer experiences. The futuristic world promised by the 1960s animated series, The Jetsons, finally seems to be a reality. It’s no wonder that contact centre organizations are eagerly looking to these solutions with wide eyes.

Issue 4 • 2018

Technology Properly implementing digital channels As front-line administrators of the relationship between the company and their customers, contact centres hold tremendous power in orchestrating the customer experience. Contact centre agents have a bevy of tools that deliver customer insights, improved response and ultimately, customer satisfaction.

For many companies, the advent of AI chatbots is a natural and necessary progression from more established digital channels, notably chat and SMS/text messaging, to help them achieve their goals.

But companies that invest straight into AI chatbot technology with zero previous experience with these other tools will likely lead to failure. The old adage, walk before you run, rings true for a reason.

Let’s take a deeper look at chat and SMS/text messaging.

When part of a strategic response plan,these technologies can be important tools in your toolbox. More than a customer convenience, chat provides instant and on-thespot interaction with follow-up questions taking place in real-time, leading to faster issue resolution. When integrated within your contact centre solution strategy, the potential for increased sales and, improved customer service and loyalty are boundless.

But too often chat or SMS channels have failed to deliver on their customer service promise. The lure of new technology is so strong, that unfortunately contact centres often move too quickly and without a structured strategy, or they choose separate technologies for digital versus voice channels.

The lure of new technology is so strong, that unfortunately contact centres often move too quickly.

Choosing a tool that is separate from your overall contact centre technology will leave your agents in a silo and force supervisors to manage multiple tools, creating an imbalance of work that leads to long call wait times for voice agents while chat/SMS agents sit with empty queues. The last thing you want is to have the new chat queue generating additional calls due to a poor customer experience. Do end users really prefer voice over chat/SMS? Or is the design and administration of the tool the real issue?

When contemplating a digital channel, companies must consider the design and operational impacts of the solution.

Interfaces that cause redundancies and errors will not be utilized. These dynamic, evolving and live channels touch many aspects of contact centre operations and must be part of an integrated contact centre strategy with a clear understanding of how the solutions will be used. When, and why, does someone choose to chat or SMS? Is the end-user on a mobile or desktop device?

By understanding existing channel analytics, you can create a response strategy based on common requests and can start to predict new inputs and address them before an Issue 4 • 2018

interaction is initiated. Ultimately, this proactivity will increase contact centre efficiencies and end user satisfaction. Your digital messaging should support this response strategy and not dictate it.

they wanted to achieve before there was any talk of technology. Once the desired outcome was clear, its strategy was to use chat as a main component in their plan to reduce live call support volumes. With an integrated plan

So, the question is not whether chat or SMS/text messaging are valuable tools, but how to properly implement digital channels within your contact centre organization.

So, the question is not whether chat or SMS/text messaging are valuable tools, but how to properly implement digital channels within your contact centre organization to maximize benefits. The goal is to understand how they will be used within your ecosystem and to define what you want accomplished with a clear vision of the end-result. Only then can you select the right digital messaging technology and have an implementation methodology that will serve your end goals. Otherwise, all you will have is an isolated tool that delivers zero internal or external value.

Build digital right and achieve success To understand the greater value of digital when built right, let’s take a real-world example of a company’s help desk that was dealing with a high volume of service requests with no chat support. Its front-line agents were faced with a significantly large number of live support calls and a low first call resolution rate. Self-help was non-existent with the burden placed completely on the agents to manage an overwhelming amount of contacts per month.

The challenge was immense with implications affecting many stakeholders beyond the agent level. The company took a step back and gathered the necessary metrics to build a clear and accurate understanding of its current situation.

Using baseline best practices, it developed a focused strategic plan with clearly defined targets and objectives.

The company determined what

that directed clients away from live agent support and towards chat, it altered the voice-path to make it less attractive as a first path resolution and implemented knowledge-based, self-help web pages.

Post-strategy metrics are impressive, to say the least. The company generated 50% fewer contacts per month, 80% of which are now chat-based. It saw a 40% reduction in service request volume and its first contact resolution rate increased by 17%. Not only did the company leverage use of its web site and increase the agent and customer experience, it was able to repurpose its agents towards more proactive activities that better utilize their expertise, allowing them to become more engaged. Mapping out and then driving customers towards the appropriate channel eliminated the heavy burden placed on the agents, ensuring that the right calls went to the right agents at the right time.

Now that the help desk can clearly identify common tasks completed by their agents, and the input/outputs have been tested with chat/SMS, when ready, an AI chatbot can be implemented in an effective way.

Without a plan or clear direction, you may lose sight of your objectives.

Don’t let technology, current or new, dictate your path. Remember, as smart as Alexa, Kate, Nina and Siri are, if you don’t properly phrase your question, you’ll never get the right answer.

Marie-Louise St-Jacques is channel manager and Eric Dauphinais is senior consultant, contact centre solutions at Quovim C3 (www.QuovimC3.com).

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