Meaningful Agent Training For Meaningful Customer Experiences

How important is agent experience when delivering exceptional customer experience? Eighty-six percent of CX executives believe it is the #1 factor. When it comes to customer satisfaction, agent satisfaction is the key. In the live Virtual Conference webcast, Lauren Comer from NICE InContact walks us through a comprehensive worksheet to help us better understand how to conduct meaningful agent training for more meaningful customer experiences.

It’s simple: satisfied and engaged agents are more likely to stay in their jobs and to have a positive impact on the overall customer experience. But how do we make sure we keep our employees satisfied and engaged? After all, the types of problems agents are handling are increasingly complex, and they need to solve these problems in a way that is efficient and satisfactory for the customer. The answer lies in training: creating more time for it and adding in higher-value skills.

We know what you’re thinking: creating time is easier said than done. After all, you cannot simply add time to your day. When we think about how we can gain more time for training, it is not about adding time, it’s about being more efficient with our time. We can do this by focusing on three things: accelerating new agent onboarding, training smarter with analytics, and pushing miniature bite-sized learning packages.

When accelerating new agent onboarding, it’s not about cutting onboarding time shorter. You’ll want to keep that duration the same while focusing on the activities and skills that really matter to the customer experience. Today, the majority of onboarding time is spent on contact center processes, technology used to service customers, and learning to use the knowledge base. The solution is an all-in-one intuitive agent interface. It’s simple: less complicated technology leads to less training required on systems. Instead, your agents can spend more time on service and use freed onboarding time on value-added training.

Many businesses have a one-size-fits-all approach to ongoing training. This is too manual to identify agent-specific skill sets, and too time consuming to be prescriptive in training. By using analytics to pinpoint agent-specific skill gaps, businesses may evaluate agent interactions based on experience through customer sentiment, customer complaints, specific words and phrases, as well as feedback from customer surveys.

In general, businesses do not prioritize setting aside time for ongoing training and development. The perception is that there is not enough time because of the typical contact center training mold. These training sessions tend to be formal, classroom style training that last at least one hour and require the presence of every employee. Instead, push “just-in-time” bite sized training. These are short, custom learning packages that are accessible from contact handling surfaces. Pushing bite-sized training packages can transform idle time into training time.

Creating time for training will transform how your agents develop and adapt overtime, becoming better equipped to handle the increasingly complex problems being thrown at them. Meanwhile, focusing that training to include higher-value skills such as problem solving, multi-tasking, and emotional intelligence will hand them the toolkit to success.

In the last 12 months, forty-three percent of contact centers experienced an increase in contact complexity. Prepare your agents by modeling what effective problem-solving looks like, identifying common problems in your contact center, ensuring all agents understand all of the problem-solving resources available to them, and allowing room for hands-on role play.

In fifty percent of contact centers, contact volume has increased in the past twelve months. Meanwhile, sixty-seven percent of agents indicated a number of channels as a factor contributing to stress. Today’s digital omnichannel world requires new juggling skills from agents. Get ahead of potential stress by providing your agents with hands on exercises for multitasking practice, sharing best practices across peers, and incorporating screen recordings into QM practices.

Just as well, emotional intelligence is key to successful customer interactions. When your agents have superior emotional intelligence, they are better at managing their emotions as well as the emotions of others. Teaching emotional intelligence is tricky. You cannot just teach the agent the empathy piece, but you also have to teach them to cultivate that emotion into effective problem solving. Do this by creating a list of recommended words and phrases by incoming sentiment /scenarios and provide hands-on exercises with your agents using active role play.

To reiterate, the keys to meaningful agent training is time and value. Creating more time for training, maximizing time with the right tools, and rethinking the training model will set you up for success. Focusing on higher-value skills like problem solving, multitasking, and emotional Intelligence will better prepare your agents for the evolving and increasingly complex contact center. You can listen to the full webcast here: https://bit.ly/3dOPln9

 

Infusing Digital CX With Human Intelligence

In today’s contact centers, there are plenty of avenues for using technology to provide a great customer experience. How can we make sure to maintain a personal touch? In the live Virtual Conference webcast, Dave Hoekstra from Calabrio demonstrated how to infuse digital CX with human intelligence to create a meaningful customer experience for not only your customers, but for your agents as well.

In today’s contact centers, we are constantly hearing the terms “AI” and “machine learning”. What does all of that mean? Really, we are talking about the ability for machines to display human-like intelligence; a concept that CX has fully embraced in recent years. Years ago, customer service was strictly face-to-face. Over time, the customer experience has evolved into omnichannel experiences for the customer such as e-mail, chat boxes, and SMS messaging. In 2020, IoT data will grow at 50 times the rate of other data. CX must keep up with this trend, however, it is vital to maintain humanity in these exchanges.

Customer expectations for CX are increasingly rising, demanding instant responses, personalized services, and omnichannel experience. With these rising expectations, maintaining customer loyalty is more complicated than ever.

The problem is that most businesses don’t know what their customers want. Why? Because they are simply not listening. Only one in four companies actively use their customer feedback, while only one in three actively use their customer interaction analytics. Ninety-eight percent of invaluable customer intelligence is sitting on the shelf. Businesses must turn this information into actionable intelligence to push them toward their goals.

Here is what we know: customers prefer human contact. Eighty-six percent of customers claim they prefer human contact to chat bots. Seventy-one percent of customers said they would be less likely to use a brand if it didn’t have customer service representatives available. While many believe phone contact is dying, calls to businesses are expected to exceed 169 billion per year by 2020. In response, businesses must humanize their customer relationship.

As previously mentioned, businesses are sitting on a goldmine of information. Using sentiment analysis, businesses can take information such as recordings from phone calls to identify human emotion in order to really understand what is going on in the day-to-day processing of our customers.

Another focus area is employee and agent empowerment. By empowering human intelligence in the contact center, businesses can drive an agent-centric approach while giving their employees the flexibility and balance they need. The integration of AI in this equation provides a personal assistant to your employees rather than taking their place. Thus, improving work-life balance, allowing for flexible planning and scheduling, and happier agents. That’s the key: happy agents lead to happy customers.

AI Assistance may also improve training and development. This can include VoC (Voice of the Customer) training, automated quality monitoring, a more intelligent way to schedule training opportunities, and cross-functional job training. Businesses are still living in an environment where operations are siloed because agents’ skills are very specific. Enter: training across job functions. Here, businesses can get ahead of the curve by recognizing where their employees’ strengths and weaknesses are before they are out in the field.

All of this leads to more empowered employees. Employees that are more engaged are:

  • 8.5x more likely to stay than leave within the year.
  • 4x more likely to stay than dissatisfied colleagues
  • 3.3x more likely to feel empowered to resolve customer issues

It’s time to hear your customers out. First. audit your technology stack. Take a look at all of the different ways your customers can get in touch with you and figure out what works best. Second, tap into the conversation to gain a comprehensive view of the customer. Finally, focus on your people. Customers matter but so do your agents. It’s time for companies to focus on the people who are engaging customers on a day to day basis. CLICK HERE TO WATCH THE WEBCAST

 

AI-Driven Modeling to Improve the Agent and Customer Experience

Are traditional analytics and contact center practices enough to drive customer satisfaction? During this live Virtual Conference webcast, Larry Skowronek and Michelle Carlson from NICE Nexidia lead a conversation about how AI-driven data modeling can be the key to achieving greater success. To further explain, Larry and Michelle walk through the state of analytics today, an overview of sentiment analytics, an overview of predictive behavioral routing, and how to combine sentiment and predictive behavioral routing to maximize customer satisfaction and drive progress.

Today, we generally see a large disconnect between business and how they evaluate customer interactions. Eighty percent of companies claim they deliver “superior” customer service, while in reality, only eight percent of their customers actually agree. This is partially because the state of measuring customer satisfaction is deeply flawed. Manual reviews of calls that require a human to evaluate transactions lead to highly subjective, interpretive, and inconsistent feedback, which not only requires higher costs, but also fails to move the needle forward.

Customer contact centers are a dynamic and evolving animal. The only way to respond to change is with change. Enter: Sentiment Analytics. Sentiment Analytics is a way to use machine learning to train a model that measures whether our customer interaction was positive, negative, or neutral on a granular scale. The machine can take our otherwise subjective behaviors and turn them into subjective data that is highly valuable and actionable. This data is consistent, accurate, and without bias. Most importantly, because it is a machine, it can do as much work as we throw at it, so we can receive and analyze data for every single customer interaction.

This AI-based model has proven to be statistically accurate, according to several CX centers that use it. But how exactly does this model measure customer satisfaction. The model reliably measures every interaction, including:

  • Spoken words, like “Awesome”, “I’m annoyed”, and “This is ridiculous”.
  • Laughter detection.
  • Pitch and tone.
  • Cross talk: customer and agent interrupting one another.

These models may also differentiate calls that start positively and end negatively, indicating worst practices, as well as calls that start negatively and end positively, indicating best practices. The reliability and accuracy of these models have allowed businesses to gain deep insights on the overall customer experience and quickly translate those insights into action. Finally, these models create a hyper-personalized customer experience. This is a monumental advantage, as eighty-four percent of customers say that personalized customer experiences are key to winning their business.

For a perfectly personalized customer experience, sentiment models can aid in Predictive Behavioral Routing (PBR), which uses sentiment analytics to match the customer to the appropriate agent and therefore improves the overall customer experience. By bringing Sentiment Analytics and PBR together, businesses can seamlessly operationale their sentiment data by:

  • Calculating customer sentiment on 100% of interactions
  • Using this sentiment combined with personality, make the best connection for the customer.
  • Immediately improve customer experience with AI-powered routing.

So, what does this process look like in real time? In one example, a Fortune 500 company’s customers were initially being transferred all over the contact center. They then optimized their customer calls based on sentiment dada. Here’s what happened:

  • They saw a 15% decrease in negative sentiment on PBR (predictive behavioral routing) routed calls.
  • They saw a 13% increase in positive sentiment on PBR routed calls
  • They saw a 6.4% decrease in average handle time in PBR routed calls
  • This required 0 hours of coaching, training and employee change management.

The combination of sentiment and behavioral routing will improve customer satisfaction metrics, reduce costs for manual listening and surveys, improve customer satisfaction via targeted coaching and performance management, and increase employee satisfaction. Your analytics practices are valuable, but should be evolving to keep up with dynamic consumer expectations. Your employees and customers alike will thank you for it.

To listen to the full webcast click here: https://bit.ly/2ULJgPB

Can we build machines that understand us?

Tobias Goebel,  Mar 2020

The question of whether we can build machines that truly think is a fascinating one. It has both practical and philosophical implications, and both perspectives answer a key question very differently: how close to the real thing (human thinking) do we need to get?” In fact – does rebuilding the exact human ways even matter? And are we too easily impressed with anyone claiming they have accomplished this Franksteinian feat?

From a purely practical perspective, any machine that improves a human task on some level (speed, quality, effort) is a good machine. When it comes to cognitive” tasks, such as reasoning, or predicting what comes next based on previous data points, we appreciate the help of computer systems that produce the right outcome either faster, better, or more easily than we can. We do not really care how they do it. It is perfectly acceptable if they simulate” how we think, as long as they produce a result. They do not actually have to think like we do.

The question of whether machines can truly think has become more relevant again in recent years, thanks to the rise of voice assistants on our phones and in our homes, as well as chatbots on company websites and elsewhere. Now, we want machines to understand — arguably a different, more comprehensive form of thinking. More specifically, we want machines to understand human language. Again we can consider this question from two different angles: the practical, and the philosophical one.

John Searle, an American professor of philosophy and language, introduced a widely discussed thought experiment in 1980, called The Chinese Room. It made the argument that no program can be written that, merely by virtue of being run on a computer, creates something that truly is thinking, or understanding. Computer programs are merely manipulating symbols, which means operating on a syntactical level. Understanding, however, is a semantical process.

Searle concedes that computers are powerful tools that can help us study certain aspects of human thought processes. He calls that weak AI”. In his 1980 paper, he contrasts that with “strong AI”: But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states.

Cognitive states are states of mind such as hoping, wanting, believing, hating. Think (sic!) about it: proponents of strong AI, and they do exist, claim that as soon as you run an appropriately written computer program (and only while it is running), these computers literally are hoping, are wanting, etc. That surely must be a stretch?

Searles thought experiment is summarized by him as follows:

Imagine a native English speaker who knows no Chinese locked in a room full of boxes of Chinese symbols (a data base) together with a book of instructions for manipulating the symbols (the program). Imagine that people outside the room send in other Chinese symbols which, unknown to the person in the room, are questions in Chinese (the input). And imagine that by following the instructions in the program the man in the room is able to pass out Chinese symbols which are correct answers to the questions (the output). The program enables the person in the room to pass the Turing Test for understanding Chinese but he does not understand a word of Chinese.

Goebel Cartoon

This is a simple but powerful thought experiment. For decades now, other philosophers have attempted to shoot holes into the argument, e.g. claiming that while the operator him- or herself might not understand Chinese, the room as a whole actually does. Yet all of these replies are eventually refutable, at least according to Searle, so the argument is being discussed and studied to this day.

Strong AI is of course not necessary for practical systems. As an excellent example of that, consider the social chatbot Mitsuku. (A “social bot” has no purpose other than to chat with you, as opposed to what you could call functional or transactional chatbots, such as customer service bots.) Mitsuku is a five-time winner (and now a Guinness World Record holder) of the Loebner Prize, an annual competition for social bots. She is entirely built on fairly simple “IF-THEN” rules. No machine learning, no neural networks, no fancy mathematics or programming whatsoever. Just a myriad of pre-written answers and some basic contextual memory. Her creator is Steven Worswick, who has been adding answers to Mitsuku since 2005. The chatbot, who you can chat with yourself, easily beats Alexa, Siri, Google, Cortana, and any other computer system that claims it can have conversations with us. (Granted: none of the commercially available systems do claim that social banter is their main feature.)

Certainly, Mitsuku by no means aims to be an example of strong AI. It produces something that on the surface looks like a human-to-human conversation, but a computer running the IF-THEN rules is of course nowhere near a thinking machine. This example, however, shows that it neither requires a machine that “truly thinks”, nor a corporation with the purchasing power of an Amazon, Apple, or Google, to build something that serves a meaningful purpose: a single individual with a nighttime and weekend passion can accomplish just that. And Mitsuku, with its impressive ability to chitchat for long stretches of time, is meaningful to many, according to the creator.

Goebel Mitsuku Graphic

 

It is easy to get distracted by technological advancements and accomplishments, and the continuous hype cycles we find ourselves in will never cease to inspire us. But let’s make an attempt to not let them distract us from what fundamentally matters: that the tools we build actually work, and perform a given task. For chatbots, that means that they first and foremost need to be able to have a meaningful conversation in a given context. Whether they are built on simple rules or the latest generation of neural network algorithms shouldn’t matter. Despite that concession, it will probably remain forever human to marvel at advances towards solving what might be the biggest philosophical question of all: can we ever build a machine that can truly understand?

Finding an Easy Formula to Do the Math is a Challenge for Contact Centers

When you google “contact center metrics,” there’s no shortage of suggestions to peruse. Lists of varying numbers of suggested metrics to be monitored pop up on the screen: 7, 13, 20, 27.  But which are the right ones for a company’s specific environment? The across-the-board metric cited is First Contact Resolution (FCR), which is a standard that just about every contact center views as critical to maintain and improve.  Similarly, Customer Satisfaction ratings, while not always quite as simple to define, are also a universal target to be monitored.

But it gets murkier from there. Many other commonly cited metrics, such as service level or average handle time, are not always directly comparable across channels; and evaluating teams that share some — but not all — queues is not always a precise process.  An ICMI study revealed that 39% of contact center leaders struggle to identify and measure key performance indicators.

A deeper understanding of metrics and how to calculate them helps a business set the right targets and reach goals to support its mission and vision. Each measure used to help determine how teams are performing needs to be understandable and actionable to individual agents, supervisors and management alike.  When all parties agree on what is important, a company can consistently track performance and see where to improve processes and training to help its agents do better.

Having this level of clarity on goals and metrics and knowing how they’re tracking towards those goals, creates employees who are more engaged with their work and empowered in their roles. A Dale Carnegie infographic shows that companies with more engaged employees outperform companies without engaged employees by 202%, and have customer retention rates that are 18% higher, according to loyalty strategy research by Colloquy.

Setting goals to measure performance can be somewhat tricky. Targets should not be so difficult to attain as to make them daunting for agents. There must be flexibility and compromise in determining how to balance between goals that appear to compete with one another, such as average handle time – where saving and time and reducing cost is paramount – and customer satisfaction, especially in cases that involve more complex interactions. When creating scoreboards to measure agent performance, businesses need to ensure that goals are instantly comprehensible and ready to act upon. They also need to make sense mathematically in tracking drivers across all contact channels including traditional, social, and mobile.  It’s helpful to use the same classification system across all interactions and equip agents to use it consistently.

Of course, simply knowing which metrics to use and how to score them is not the be-all, end-all for optimizing agent happiness. Going back to Google, one would find an astounding 147,000+ results for “benefits of a happy contact center agent”. The major areas of focus in these listings range from the obvious: “why agent satisfaction is important,” to the ubiquitous “fun things to do to keep agents happy” and the more specific evaluations of software and services to promote agent satisfaction.

Companies must be proactive in their approach to building models that are consistently accurate in predicting probabilities and outcomes in their contact centers. Models that are less than precise lead to failure to maintain desired service levels and result in cost overages. Businesses need to find innovative but proven methods to calculate the proper variables and the right things to look for in developing analyses that result in accurate forecasts.

Data abundance and complex operations make it challenging to develop, implement, and present clean, clear reports and on-target analyses. Over the next several months, agent-first solution provider Sharpen Technologies, developers of an always-on contact center platform built for the enterprise, will present a comprehensive series of complimentary webcasts on CrmXchange.

The four sessions are designed to demystify the process of determining the right metrics, show businesses how to measure and accurately analyzing contact center performance, and to implement those analyses across the operation so the entire organization stays focused on excellence. It will culminate in a discussion of how to put together the most efficacious math models for contact center executives and managers to glean actionable insights.

The first webcast in the series, “Attributes of Solid Contact Center Performance Metrics – and Attributes of Poor Ones”  will take place on Thursday, March 5.

The second,” Learn How to be Great: Helping Agents, Supervisors, and Execs Perform,” will be presented on Tuesday April 21.

The third session, “Setting Performance Goals and Scorecards,” comes up on Thursday, August 13.

The final presentation “Building Great “What-If” Models and the Resulting Analyses for the CEO” will be delivered on Tuesday, October 20.

All webcasts will be jointly presented by Ric Kosiba, Chief Data Scientist and Adam Settle. Chief Product Officer, Sharpen Technologies. Ric’s vast background of expertise goes back two decades to Bay Bridge Decisions Technologies which he co-founded in 2000. In that role, he developed the contact center industry’s first “what if” decision engine, a complex set of algorithms designed to forecast proper staffing levels. Adam is an experienced education professional skilled in Sales, Coaching, Team Building, and Training. He combines his extensive knowledge with hands-on experience as a trainer at Apple and Angie’s List.

Register now at no cost for the individual presentations or the complete series. Each webcast is at 1:00PM ET. If you cannot attend the live presentation, a link to the recorded session will be available within 24 hours.

How Analytics Enable You to Bring Your Company Closer to the Customer than Ever Before

There are divergent opinions in what technologies are most effective in creating a better customer experience, but one thing that just about every expert agrees upon is analytics can be  a real game-changer.

According to a recent Harvard Business Review Analytics Services study, published in Forbes magazine;

  • 70% of enterprises have increased their spending on customer analytics solutions over the past year.
  • 58% of enterprises are seeing a significant increase in customer retention and loyalty as a result of using customer analytics.
  • 60% use real-time customer analytics to improve customer experience across touch points and devices as extremely important today.
  • 44% of enterprises are gaining new customers and increasing revenue as a result of adopting and integrating customer analytics into their operations.

The move toward greater use of analytics has been swelled by a wave of converging technologies including artificial intelligence, the internet of things (IoT), and cloud computing. The exceptional speed and precision advanced customer data analytics continue to improve at an exponential rate, making them a must-have for businesses seeking to forge stronger connections with their audience.

As further noted in the Harvard Business Review Analytics Services study, the number of corporate executives who responded to the study indicated that the importance of having the capability to use customer analytics to improve customer experience across all touch points rose from 60% in 2018 to a projected 79% for 2020.

But it’s an oversimplification to just state that analytics can be beneficial to businesses. Analytics tools encompass a broad spectrum of categories and technologies that needs to be understood and evaluated before being implemented and integrated into a company’s CX strategy.

Can text and speech be analyzed in the same way? Why or why not and how should companies be thinking about text analysis vs. speech analysis? Both text and speech analytics enable organizations to optimize customer engagement by looking deeper into interactions its agents have with customers, regardless of channel –phone, email, chat, social media, or surveys as well.

Speech analytics uses speech recognition software to convert spoken words of recorded calls into text where analyses can be performed. When used effectively, it can help identify the reason behind a call, the products mentioned and the caller’s mood. Sophisticated speech analytics software can analyze phrases used by customers to quickly identify their needs, wants and expectations and indicate areas that need improvement for front-line personnel.

Text analytics is the process of transforming unstructured text documents into usable, structured data. It works by deconstructing sentences and phrases into their components, and then examining each part’s role and meaning using complex software rules and machine learning algorithms. One can analogize it to slicing and dicing piles of diverse documents into easy-to- interpret data pieces. By more closely examining communications written by–or about– customers, business can identify patterns and topics of interest, and follow up with practical action based on what has been learned

Desktop analytics offers contact center managers a method of capturing and analyzing user activity at the desktop level. The data gathered about individual application usage and across applications can not only impact the customer experience but ultimately affect the IT resource budget as well. It resides on each individual agent’s desktop, compiling a list of every application, URL, and more the agent accesses during the day. This empowers companies to determine if contact center personnel are adhering to standards and see how well they are relating to customers.

Leading analytics provider Calabrio will take a deeper dive into the constantly growing use of analytics—and examine its specific role in enabling companies to become more customer-centric—in two complementary…and complimentary…webcasts on CrmXchange.

The first of the two presentations –“The Beginner’s Guide to Analytics” –will take place on Thursday, February 20. Presented by Contact Center Analytics Consultant Mark Fagus of Calabrio, it will explore such key topics as:

  • The differences between speech, text and desktop analytics
  • Analytics technologies, such as LVCSR (Large-Vocabulary Conversational Speech Recognition), Phonetics and STT (speech-to-text)
  • The top 10 analytics business use cases

The second webcast –Unlock Customer-Centric Intelligence on Thursday, March 12 will expand on how companies can make the most out of using analytics by empowering themselves to reach higher levels of comprehension by developing new insights to deal with their customers. Brad Snedeker, Director Product Marketing, Calabrio, will delve into features that companies can use to their advantage, including:

  • Embedded analytics – learn how analytics have been surfaced throughout the application to provide easy access to key insights without having to go outside everyday workflows
  • Unified, self-service dashboards – compelling and personalized insights within dashboards that can double as homepages
  • Enterprise KPIs – out-of-the box performance management tools
  • Speech-to-text enhancements – find out how to achieve increased accuracy and speed of transcription

Register now for the first or second of these informative Calabrio webcasts….even better, sign up for both! Each will take place at 1:00 pm ET: if you cannot attend the live presentations, you can download each one 24 hours after it is completed.

2020 Customer Support Predictions

2020 Customer Support Predictions from UJET’s Anand Janefalkar, Founder and CEO, UJET

  1. Messaging Will Surpass Voice – “While voice will always remain an important channel for support, especially for urgent issues, in 2020, we will see messaging (SMS and chat) overtake voice as the most critical support channel. Woe to customer service organizations that cannot provide an omnichannel support experience that includes messaging, as this will most surely equal the success or demise of the overall customer experience (CX).”
  2. Multichannel Will Expand to Multimedia – “In 2020, expect to see customer service organizations turn their attention to optimizing each support pathway to meet the tech-savvy needs of many of their customers. Chief among enhanced capabilities will be multimedia. The ability to share screenshots, photos and even video between the customer and support professional will become commonplace during support interactions.”
  3. Data Will Break Down Silos Between Customer Support and Other Teams – “In 2020, the ‘digital transformation’ conversation that has become commonplace across IT, will extend into the customer service center. We will begin to see the impact and value of support data being shared across the enterprise. Customer feedback, sentiment, profile data and more will be securely shared across organizations helping teams such as marketing, sales and product development to make more strategic decisions. And as a result, the importance and value of customer support will be elevated as a whole.”
  4. Agent Specialization Will Be A Key Focus  – “In 2020, as the presence of technologies such as AI and Machine Learning within the contact center continue to grow, and more customers are directed towards bots and self-service options, support agents will become hyper-specialized. Agent specialization will not only be geared towards channels, but also centered around specific issues, situations and the urgency of incoming support interactions.”
  5. AI Will Improve the Customer Support Employee Experience (EX), as well as the Customer Experience (CX) – “In 2020, AI will dramatically improve the employee experience (EX). The ability to automatically and instantly collect data from across multiple channels, analyze it and provide actionable insight will enable support agents to more quickly, easily and accurately address customer inquiries and come to highly satisfactory issue resolution.”

Biometric Authentication and AI Technology: How Companies are Keeping Customers Satisfied and Safe from Fraud

With the constantly increasing need for customer service and sales support, contact center operations continue to expand, generating over $300 billion in revenue each year according to JLL Research. Given the vast amount of sensitive data that flows through contact center environments, security -including insidious insider threats – has become a serious concern. According to a recent report by UK-based Contact-Centres, the rate of contact center fraud has gone up dramatically over the past four years, increasing by 350 percent. This has created what Gartner calls “an epicenter of vulnerability.”

In the US, as many as 1,300 breaches were tracked last year by the Identity Theft Resource Centre1. Fraud perpetrators are becoming more sophisticated, leveraging today’s omnichannel shopping techniques. For example, a fraudster can employ social engineering to reset a password on a victim’s account, using information now easily found via social networks and Google searches to obtain usernames, passwords, and other personal data. Criminals then employ that newly reset password to hoodwink a live agent into giving away additional information and sometimes even performing fraudulent financial transactions.

For contact centers, finding effective methods of tackling this daunting challenge calls for a multi-faceted approach, including ways to prevent attacks emanating from both outside and inside the company. That means identifying dishonest individuals who call in masquerading as legitimate customers, or try to hack into contact center data, as well as keeping dishonest agents from stealing customer information. The caveat is that contact centers need to implement such security measures without creating barriers to a positive customer experience for honest consumers.

One method now coming into widespread use is biometric authentication to verify customer identity. Some solution providers offer tools that support self-service interactive voice response (IVR) via voice and face recognition and when the customer is using a smartphone, can even support fingerprint authentication. Others offer voice biometric identity verification which relies on more than simply the physical characteristics of a voiceprint when authenticating end users. An advanced voice biometrics engine can also account for how a user speaks and what is said. taking note of variations in the pitch and tone of a customer’s voice.

So, how can forward-thinking organizations take the right measures to adapt to this new reality and protect their customers from fraud without negatively impacting satisfaction ratings? On Tuesday, December 10 at 2:00 pm ET, CrmXchange is offering an complimentary, in-depth webcast entitled “The Biometrics Win-Win – How Leading Brands Are Beating Fraud While Improving CX.”

The session is sponsored by Nuance, named a leader in Conversational AI for Customer Service, including voice and speech engines, human/AI blending, omni‑channel delivery and security and authentication in the in Q2 2019 Forrester New Wave. The presenters are established authorities on improving contact center security: Simon Marchand, Nuance’s Chief Fraud Prevention Officer, and Dima Cichi, Senior Principal Product Manager, Security and Biometrics for Nuance. Among the topics addressed will be:

  • How the fraud battle lines are shifting and why AI tech can help win the fight in the contact center and beyond
  • Enabling stronger authentication to co-exist happily with exceptional customer experience
  • A first-hand look at how combining voice, behavioral and other biometric modalities deliver a powerful cross-channel defense
  • An examination of the latest Nuance innovations for authentication and fraud detection
  • The benefits both large and small organizations are realizing from faster, stronger authentication and real-time fraud detection

Register now for this eye-opening session: if you can’t attend the live presentation on December 10, it will be available for download 24 hours after it is completed.

 

What New Paths Will Companies Take to Shape the Customer Journey in the Years to Come?

As the time-honored adage puts it, ‘a journey of 1000 miles begins with a single step.’ These days, the journey a customer takes when engaging with a company may be far more geographically limited but usually starts with a lot more steps. The ever-evolving customer journey incorporates varying interactions and experiences that take place on different touchpoints: a website visit for research, a call with a sales rep or chat with an agent, a conversation on social media or online review site, an inbound call, and even an in-store retail encounter.

It has become more important than ever for a business to take advantage of every possible resource to understand its customers: their wants, needs, and expectations, their thoughts and opinions and feedback and expectations. Building this knowledge will enable companies to deliver the highly personalized customer experiences that are becoming more crucial all the time in an increasingly competitive marketplace where consumers are offered a constantly growing array of options.

Given access to vast resources of data and technology, the customer journey today has morphed dramatically from where it was even five or ten years ago. And every company’s success depends upon combining the right technologies with the agility needed to effectively manage all the interactions that take place on every channel along the way.

Gazing into the future, which often-predicted developments will come to pass? Will the migration to the cloud finally encompass all businesses and make service more responsive? Will messaging ultimately surpass voice as the communication channel that is most compelling for businesses and consumers alike? Will digital transformation extend its reach deeper into the contact center environment to better leverage profile data, more closely examine customer feedback, and measure sentiment? Will customers expect greater availability of agent support that involves the use of screenshots, photos and video? And how will the growing use of AI-powered solutions progress, both in terms of those that provide more effective self-service options and those that support the development of more highly specialized agents?

Of course, no one can foresee every possible path the customer journey will take in the coming years, but CX and contact center executives and managers have an opportunity to get a cogent vision of many of the most important changes in an upcoming complimentary roundtable webcast on CrmXchange. On Thursday, December 5, at 1:00PM ET, NICE Nexidia and RingCentral will team up to explore “Smooth Customer Journey- Predictions for 2020 and Beyond.

Ken Brisco, Senior Product Marketing Manager, NICE Nexidia, who is responsible for establishing the scope and message as well as the competitive advantages of NICE’s Customer Journey Optimization Solutions within the CX space will be joined by RingCentral’s John Finch, AVP PMM, Customer Engagement, an executive with an extensive background in developing strategy for global customer engagement. Among the topics they will cover are:

  • How AI-driven analytics can boost customer loyalty and retention
  • The importance of measuring quality across all channels
  • In what ways bots are best able to collaborate with humans
  • How macro to micro-level journey analysis drives deeper insights into customer engagement

Register now for this insightful look into which near-future developments may change the way your organization helps to orchestrate the customer experience. If you are unable to attend on December 5, you can access the recorded version approximately 24 hours after the live presentation.

 

Predictive Behavioral Routing: Advancing the Capabilities of the ACD to Meet the Needs of 21st Century Customers

We’ve all had the frustrating experience of trying to extract information we need from a random agent who is not attuned to the specific issue with which we need assistance. We explain and try to provide context, but the conversation goes around and around in circles as we grow increasingly exasperated and the agent reaches new levels of confusion. In worst-case scenarios where there is a clash of personalities, the agent becomes defensive and the caller outright angry, often resulting in customer churn.

Call routing is a technology that has been around for as long as there have been call centers: the automatic call distributor (ACD) has been in place for more than 45 years since the Rockwell Galaxy appeared on the scene in 1973. But throughout that time, it has mostly been an application that supported faster pickup as opposed to more empathetic and effective customer service. It wasn’t until the early 90s that algorithms were developed that enabled skills-based routing. This called for the organization of groups of agents with specific skills that related to the needs of incoming callers based on their responses to a series of questions asked by a menu-driven IVR type of application.  Calls could theoretically be routed to people speaking the caller’s language with the right product knowledge.

While better than simply routing a call to the next available agent, skills-based routing still left a lot to be desired. It lacked the capability to take advantage of quantum advances in big data, analytics, and personalization strategies. But over the past five years, an emerging technology has been changing the equation. Predictive Behavioral Routing (PBR), first introduced by Mattersight in 2014, takes the customer interaction process from a chance encounter to a personalized connection. The company’s foundation in analytics along with its proprietary behavioral model allowed for the application of data to enhance calls right from the moment they were connected. Mattersight was acquired by NICE Nexidia in August of 2018 and the combination of NICE Nexidia’s advanced Interaction Analytics provide organizations a more comprehensive understanding of the customer journey along with a clearer view of the customer persona.

AI-powered smart routing communicates with the ACD to intelligently pair customers with agents best equipped to handle their personality style, resulting in more productive and positive call outcomes. Now being used by Fortune 500 customers in areas such as financial services, retail, healthcare, communications, and Telecom, Predictive Behavioral Routing is proven to provide improved business outcomes.

According to Paul Stockford, Research Director, NACC and Chief Analyst, Saddletree Research “Predictive Behavioral Routing is paving the way for a new era in customer care – combining the best of data analytics, artificial intelligence, and the customer experience.”

Although many contact centers executives and managers may have heard of PBR, they might not be aware of all the powerful benefits it can bring to their operation.  See first-hand how elevating the ACD from a simple call delivery tool into a strategic method for taking the customer experience to unprecedented new levels in a  complimentary “Predictive Behavioral Routing Demonstration – How Does it Work? What Can it Do?” on CrmXchange on November 19 at 1:00 PM ET.

Michele Carlson, Senior Product Marketing Manager, NICE Nexidia, will share the expertise she developed in over a decade at Mattersight in analytics technologies that provide businesses the opportunity to understand data and customer interactions. Among the topics covered will be:

  • Insight into how PBR captures a customer’s personality style and behavioral data, and the ways the data is used to identify the best agent to address their concern
  • How a call is routed to the optimal agent for the customer
  • In what ways KPIs improve with personalized connections
  • Results and best practices from enterprises that have elevated connections with Predictive Behavioral Routing

Register now for this exciting demonstration of a truly game-changing technology. If you cannot attend the live presentation, you can download it 24 hours after it is completed.