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Customer Contact Week 2018 Onsite Review

CRMXchange

Presented By: CRMXchange



One of the biggest challenges of talking about the 19th annual CCW in Las Vegas, which was held from June 18- 22 at the Mirage in Las Vegas, was getting used to the updated definition of the acronym. The event had been known since its inception in 1999 as “Call Center Week.” And while the change to “Customer Contact Week” had officially been made for the earlier winter version of CCW in New Orleans, it still took presence of mind not to refer to it by its original name. CCW is produced by the Customer Management Practice - the Analyst, Advisor, and Industry Network for all things Customer Management, under the multinational conference organizer IQPC.

Highlights included site tours of BPOs Alorica and TELUS, the Las Vegas Valley Water District and the perennial customer service paragon Zappos …an array of master classes and solution provider workshops covering everything from personalized omnichannel service to intelligent use of artificial intelligence and employee engagement to using voice of the customer data…journey mapping and messaging…book signings… the annual  awards gala… Executive Club sessions for high-level attendees …keynotes that included an address by  Barbara Corcoran, “lead shark” of ABC-TVs Shark Tank and pioneering Chief Customer Officer Jeanne Bliss, President of CustomerBliss as well as executives from Comcast  Uber, UPS, and others, conference tracks on People, Process and, networking and special events in the exhibit hall. 

An audience of approximately 2,500 attendees had the opportunity to meet with more than 200 technology solution providers and hear from a roster of over 250 speakers. Amidst all the excitement, CRMXchange was active both on the exhibit floor and in the CCW new press room to gain insight about a variety of the most innovative solutions and services becoming available to CX and contact center professionals. Suppliers of AI and machine learning solutions, chatbots, predictive analytics solutions, training, and messaging for the contact center were in abundance.

 

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[24]7.ai
                    CallCriteria                     RapportBoost                      Solvvy
             
BehaviorSignals
  
i2x
    SitelGroup    Veritone
             
BrightlinkIP         IMIMobile
                  Smooch    
             

 

[24]7.ai  considers itself to be the largest chat provider. The company offers one AI platform for speech and digital. Clients can build once, then deploy on any channel to create a personalized, predictive, and effortless customer experience. [24]7.ai evolved into AI machine learning, leveraging the technologies along with the predictive capabilities. It started with [24]7AIVA which use multiple layers of machine learning and deep learning to understand customer intent along with context. In a matter of weeks, with a simple change in the UX, AIVA can have the same applications running on multiple channels.  One set of code. When someone lands on the web, the bot is launched.  If the bot can’t resolve the issue, the next step is assisted service.  The bot will go to the agent, the agent responds, and then sends the response back to the bot for the customer interaction. If the bot has nearly resolved the issue, the individual can then leave the website and call into the IVR.  [24]7.ai can tag the call and route it to the right place. The agent can see everything that has occurred before the call. This in-time context results not only in reduced average handle time, but is also less frustrating for customers as they do not have to repeat themselves.  Dan Reed, Chief Customer Officer, provided an overview.    

Why is it critical for businesses to know customer intent and be able to act on it almost instantaneously?

The world we live in is a connected one where customers interact with personal and business services all day long. And in this connected world, customer journeys take place across devices, channels, and over time with customers expecting the steps along these journeys to be connected, seamless, and productive. The only way to successfully interact with customers across channels, devices as well as over time is by connecting the journeys to understand their intent which is knowing what each customer is trying to do, not just what he or she says or types.  Artificial Intelligence (AI) makes it possible for companies to decipher data to understand intent which allows them to connect customers to the right channel for problem solving along with context so that customers never have to repeat themselves.

How does your customer engagement platform provide predictive capabilities that anticipate what consumers want to accomplish, no matter what communication channel they prefer to use?

In this connected world of customer experience the first step is to ensure companies are moving beyond channel-centric approach to conversation centric approach. [24]7.ai has redefined customer engagement by offering intent driven customer engagement solutions, meaning use of AI and machine learning to connect customer journeys across channels, devices and over time to understand what they want and not just what they say or type. Our platform’s predictive capabilities track and share all customer activity across channels in real time to deliver faster resolutions that result in superior experiences for customers. The solution can anticipate customer requests and follow the principle to “never ask the user something you should already now”. Predictive intelligence enables the higher-level conversation skill of active guidance resulting in happy customers. 

In what ways do your AIVA solutions enable organizations to offer customers better self-service options and improved conversation levels in IVR interactions?

[24]7 AIVA, our flagship product, uses multiple layers of machine learning and deep learning to understand customer intent along with context to offer effortless interactions no matter how or when consumers choose to engage with a company.  A key differentiator of [24]7AIVA is the Vivid Speech feature that augments IVR interactions by providing customers more control through multimodal speech, touch, and visual experience that dramatically improves self-service automation. 

What differentiates [24]7. ai from other providers in the marketplace?

In todays’ digital world customer expectations are higher than ever, and the only way for businesses to meet those expectations is to understand consumer intent to offer faster and relevant customer engagement. [24]7.ai understands that using artificial intelligence, it is now possible to make sense of the tremendous amount of big data that businesses possess. In the Age of Intent, businesses who can understand, anticipate and act on consumer intent will thrive and those who don’t will be disrupted and the [24]7.ai solutions offer companies the ability to leverage AI and machine learning to know and act on consumer intent in milliseconds, reducing the risk of customer frustration. [24]7.ai also offers predictive models tuned by more than one billion annual interactions and 18 years of customer service experience. Addressing the final leg of customer interaction, our design teams work closely with clients to create a superior user interface that is easy to use, interactive and efficient thereby increasing our customers' competitive advantage.

Behavioral Signals enables businesses to measure emotions and behaviors in voice, by employing intelligence via the use of AI technology. They've pioneered the field of Behavioral Signal Processing which employs leading-edge techniques to measure, analyze, and model human behavior directly from signals, with the goal of providing valuable decision-making information. These computational techniques are now capable of understanding human expression and behavior and have widespread applications in contact centers. The solution transcribes calls and does analytics, looking at the entire conversation to see how the customer reacts with the agent, including elements such as how the agent’s tone impacts the interaction. First, it examines how a conversation starts and then, over the first 45 seconds, notes the change in tone.  They find the moments of change and determine what the agent brought to the table. This enables companies to set up business rules and get managers involved when needed. Implementation starts off with models that have been pretrained on data sets. The solution can then be fine-tuned to train on the specific KPIs of interest to each individual client organization.  Jason Ferrell, Strategic Advisor and VP Products & Partnerships and Maria-Anna Niforos, Business Development Analyst, offered additional background.

Why is it critical for organizations to recognize and measure the emotions, behavioral and interaction patterns in the conversations that have impact on the bottom line? 

Although communication is at the heart of a business, business-to-customer and employee-to-employee interactions are full of missed opportunities. It is critical for organizations to recognize and measure the emotions, behavioral and interaction patterns in their conversations because they add significant new dimensions to leaderships’ business strategy process. Whether it’s hiring the right people to fit the emotional intelligence character they want for the company, getting 10x more accurate forecasting of deals in the pipeline, managing channel and supplier relationships better, or reducing risk for negative behaviors that otherwise could lead to significant legal expenses. 

How does your solution enable businesses to monitor and take action on not only what is being said in calls but how it is being said?

When we speak to each other, how we say something matters as much as what we say. Our award-winning emotion recognition and behavioral prediction analytics technology utilizes cognitive modeling and advanced machine learning algorithms. This enables us to provide enriched measurable insights by monitoring talk-time of agent/customer calls, tone positivity or negativity of participants and emotions, such as anger, frustration, joy, or behaviors, like politeness, satisfaction, engagement or propensity to buy. These are a few of the emotions and behaviors we capture, contributing to KPIs that can help the organization with agent coaching, agent scoring or improvement of contact center goals. We understand not only what is being said but how it is being said, the emotions, intentions, state-of-mind and behaviors of each person.

In what ways do your AI and deep learning capabilities provide behavioral intelligence and real-time predictive insights by analyzing conversational data?

Our solution enables businesses to monitor and take action by utilizing our experienced team’s scientific dexterity in language, speech processing and psychology. We unlock the potential in voice-data by analyzing acoustic cues, intonation, and other speech signals and interpreting them into specific emotions and behaviors. We accomplish this with our advanced AI engine that continuously evolves through rigorous deep learning processes and vast amounts of conversational data. We enable organizations to analyze the cognitive and affective aspects of all their voice data giving back real-time predictive behavioral modeling insights.

With our real-time prediction technology, we help organizations monitor their agents and understand their customers intent, giving them the tools to take immediate action like coaching their agents to alter their behavior live, helping them perform better, or preventing mistakes that could affect their business reputation.

We add emotional and behavioral intelligence to conversations ranging from contact centers, virtual AI assistants, robots, financial processes, to healthcare services. By understanding the behavioral patterns of their customers and employees, organizations can maximize revenue by matching talent to market, predicting outcomes and focusing on ROI.

What differentiates your solution from other offerings available on the market?

Traditional analytics and business performance have little insight into the motivations and behaviors of people. They provide information about the individual’s actions but not the behaviors that cause these actions. That hinders companies from planning ahead, raising effectiveness, efficiency and quality of services, growing their reputation, avoiding lawsuits or simply training their personnel successfully to model their behavior to the desired outcome.

In the complex communication process, by capturing acoustic cues, intonation and other speech signals, we differentiate ourselves from other offerings by discovering emotions and behaviors, empowering our customers with real-time predictive behavioral modeling and business insights. The future of business takes conversational AI into account with enterprise software. We consider ourselves to be ‘category creators’ pioneering the first emotionally intelligent conversational AI solution on the market.

Brightlink IP delivers easy-to-deploy voice solutions for UC&C, contact center and cloud PBX technologies, all with superior quality. It also offers an advanced messaging platform that enables businesses to economically grow their messaging capabilities. Since Brightlink’s network was built to service the world’s largest telcos and providers, they do not resell any other products and services. Brightlink IP protects customer transactions with constant global monitoring. Its end-to-end security solutions -- from private line, encryption, MPLS and VPN connections-- are capable of handling over 10,000 messages per second per customer. Joe White, Chief Technology Officer, elaborated further.

How does having a customizable, cloud-based UC PBX platform enable companies of all sizes to better manage support /customer service call flows, recordings, queues and more?

Firstly, it empowers Brightlink partners to service their customers and end users.  It grants their business customers the freedom to use the product the way their business dictates and not the “predefined” way that a service provider typically sells.  Secondly, whether they have five seats or five thousand seats, companies will be able to continue expanding globally without committing to any extensive, and expensive, hardware investments. 

In what ways does your messaging platform enable businesses to communicate more effectively and securely with their customers?

Brightlink has a unique messaging platform in a few ways.  First, every single number that we provide to our customers is messaging-enabled by default. So, if a potential customer is already using messaging they don't have to worry about “SMS Enabling;” a number in the Brightlink network, they are all natively SMS capable.  Second, we have tremendous scale, security, and routing capabilities as well as geo-redundant networks which provide our customers with on-demand capacity, encryption solutions and reliability that isn’t available from traditional carriers.

How does network traffic transparency help companies measure the right call and messaging metrics to improve the customer experience?

Transparency enables companies to monitor traffic shifts, trends and common network issues, choppy audio, jitter etc. and bring them to the business’s attention in real time. Instead of waiting hours, sometimes days, for insight, companies can interact with data in the carrier network almost instantaneously and with visibility unmatched by any other provider. In addition, Brightlink's Liveview platform also allows companies to compare current statistics against historical data, giving them the power to identify trends, improvements and changes.

What differentiates your solutions from other offerings available on the market?

Brightlink delivers services throughout the world on its fully redundant, capacity-rich voice and data network which drives not only carrier services but also software and voice applications.  Brightlink solutions encompass more than just transport and network services. We offer our customers a full suite of UCC and hosted platforms that can interact with customer solutions through IP-based communications, web portals and robust API’s. 

Call Criteria believes that while speech analytics technology can help people perform many everyday tasks, using voice analytics software alone to monitor, measure and report contact center performance will only ever tell you a portion of the story between agent and customer interactions. The company uses advanced voice-to-text technologies in collaboration with the skills of reliable, precise human analysts to provide businesses with what they see as a highly accurate and dependable assessment of contact center performance at an affordable price. Call Criteria employs analytics tools for a more blended approach, realizing one without the other (automated software and human analysts) won’t deliver the dependability a contact center must rely on. This in turn allows contact centers to give more immediate feedback, deliver meaningful coaching and manage their teams and centers more effectively. Their technology provides comprehensive scorecards with highly dynamic development tools allowing for customized and efficient evaluations. Their teams of analysts work closely with companies’ QA management teams to ensure calibration and accuracy is constantly maintained and monitored. Helping eliminate bias often encountered with internal contact centers QA programs, Call Criteria prides themselves on being cost-effective, while offering an outstanding quality of service for their clients. Ryan Stomel, founder and CEO, answered our questions.

While technology solutions have the capability to monitor, measure and report on contact center performance, why is adding human analysis skills critical to getting a more accurate picture?

While there are certainly benefits to be gained from technologies such as voice-to-text transcription software, there are limitations that still clearly exist. The ability for human analysts to gauge, monitor and evaluate soft skills such as tone and courtesy, for example, still far exceeds that of the automated technology available today. Human analysts can uniquely discern between intended meaning and perceived meaning, while computer modeling and monitoring can merely present the facts. Moreover, when it comes to judgement calls, subjective analysis, and customized feedback, there is no replacement for human experience and our decision-making ability.

How does Call Criteria provide a hybrid of human hearing and voice recognition software to deliver scalable third-party QA?

Blending voice recognition software with human analysis brings together the best of both worlds. Through voice analytics and keyword-flagging algorithms, we’re able to pinpoint the interactions most in need of a more in-depth analysis and evaluation. This allows for maximum coverage over your agent to customer interactions, while enabling our human analysts to do the difficult work of breaking down in finer detail, the pain points and weak links within a contact center. This proves to be extremely cost effective, allowing businesses to allocate those precious resources elsewhere.

How can companies identify key agent behaviors and patterns that result in improved sales and service results?

Whether a company is focused on compliance or conversion, or very likely both, we leverage our decades of combined experience in the contact center industry to formulate and implement monitoring strategies used to develop evaluation criteria most suitable to a specific business’s unique needs. Internal comparative analysis, industry benchmarking, and aggregated data modeling are just a few ways companies today can maximize conversion opportunities and capitalize on the strengths of its processes and personnel.

In what way does your solution help businesses keep their contact compliant with regulations?

Through a multi-layered “checks and balances” system which relies heavily on quality assurance measures like repetitive calibration techniques and peer-to-peer accountability, Call Criteria helps businesses eliminate the detrimental agent behavior most associated with expensive compliance violations. While there is no perfect solution to human imperfections, our tenacious team of experts utilize a variety of communication channels to relay instantaneous notifications and feedback to provide an organization with quick and actionable data, ensuring it stays one step ahead of regulators, and of the competition.

I2x provides real-time conversation analytics and coaching to elevate customer interactions. Its AI-powered speech recognition platform enables businesses to leverage their data to understand what makes their team successful and customers happy. The solution guides the agent --via an aid appearing in the corner of his or her desktop --to direct them on what they should and should not say to conduct a smarter conversation that can increase conversion rates. In addition, i2x records and transcribes conversations in real-time. The record that is created from voice is then added into the CRM system and available via dashboard to the agent and manager.  

Beyond delivering learnings for the agent, the solution gives managers a window into the world of customer interactions by utilizing real-time analytics that can improve crucial KPIs, and ultimately decrease agent churn. Michael Brehm, founder and CEO and Mike Allen, a global B-to-B enterprise sales leader who was just appointed VP of North America to spearhead i2x’s expansion into the US market, told us more.

How did you derive the name of your company and how does this identity reflect your commitment to building expertise in verbal communications?

The name i2x originates from Malcolm Gladwell’s “10,000 Rule”. Malcolm Gladwell is an author, researcher and work-psychologist who stated that it takes 10,000 hours of practice for anyone to become an expert in any field. i2x challenges his rule and thrives to bring its users to an expert level in verbal communication in less time. i2x takes its individual (“i”) toward (“2”) the effect of 10,000 (“x=ancient roman sign for ten thousand”) hours of practice.

In what ways does your solution enable businesses to listen to, analyze and provide immediate feedback to agents after each call?

With i2x, the black box of phone calls is decrypted for the first time. Traditionally, call center success measurement was based on a limited set of data, including call attempts and duration. i2x opens the doors to deeper, more meaningful measurement. The platform evaluates complex speech parameters in real-time to determine the dynamics of a customer conversation. This includes customizable words and phrases, pauses, rate of speech, and speech-to-listen ratio. i2x analyzes sales and service team calls and identifies which approach works best for a specific customer or prospect group. Data-driven best practices are automatically identified and can be shared with all team members. As a result, managers gain deeper insights into customer interactions, as the skills of existing employees evolve, and brand experiences improve.

Can you briefly explain the concepts behind your “Do Say” list and how it helps agents conduct better conversations?

Having the ability to get real-time feedback and advice during a call, and then adjusting helps agents quickly improve their conversion rates. Our “Do Say” list allows managers and agents to easily create and adjust lists of specific phrases and words they do want to mention during the call, helping assure compliance with scripts, quality standards, and ensuring all important points are touched on during a call. If a “silver bullet word” is mentioned during a customer call, it’s highlighted in the dashboard as a positive reinforcer. Ultimately, this leads to higher conversion and upsell, as agents never have to wait for a lost sale to assess, learn and improve. 

What are some of the technological elements that i2x employs to help improve agent performance?

i2x is simple and user-friendly. It can be installed in less than two minutes on a user’s computer without the hassle of admin permissions, specific hardware, or the use of on-premise resources. i2x’s built-for-purpose ASR (automatic speech recognition) platform uses a high-volume data set from nearly 1 million transcribed phrases and is designed specifically for the teleworker use case. With the mission to improve agent performance, i2x’s machine learning elements empower agents to better identify, adjust, and improve their calls in real-time. This includes:  

  • Best Practice Identification - provides data-backed training tips for improvement, and the ability to give cross-team coaching 
  • Seamless Speech - uses AI to identify filler-words and reduce speech-disfluencies
  • Accelerated Conversation Wrap-Up -  using i2x’s fit-for-purpose ASR, each call is transcribed and stored to facilitate documentation and support manager’s performance tracking

i2x announced the launch of its speech technology research lab to address current challenges in data science. The lab will focus on advances in natural speech recognition and speech technologies. Findings will be applied to the platform and used by sales and service professionals to improve conversion rates, increase customer satisfaction, and reduce onboarding time.   

IMIMobile  is a global provider of cloud-based software and services that enables organizations to use two-way mobile and digital communication channels to improve customer experience and engagement. It allows for channels such as Facebook Messenger, SMS and Twitter DM to act as a new gateway into the contact center. AI-assistants and NLP-powered chatbots work together to enable self-service. By automating support tasks such as FAQs or parcel delivery inquiries, it proactively reduces inbound calls by up to 15 percent. It’s a communication platform as a service (CPaaS).  IMIconnect gives companies the capability to connect different business systems and design, manage and orchestrate new customer journeys across business processes within days, not months. For instance, banks can easily deploy fraud alerts, such as when a customer puts his card into an ATM in a foreign country. Through IMIconnect, banks can perform a location look up of the customers location to assess if both card and customer are in the same location. The company’s cloud software platform manages over 42 billion messages and 44 billion commerce transactions a year across the world. Alex Klose, VP of Marketing, expanded on IMImobile’s capabilities. 

In what ways can businesses better use the mobile channel to drive better employee productivity, customer engagement and customer experience?

Today, organizations need to utilize mobile and digital communication channels to respond to rising digital customer service expectations. Our research found that 67% of customers now expect help within 5 minutes (or less) of making initial contact with an organization.

By enabling customer service agents to use mobile and digital channels to engage with customers, they will be able to increase productivity by being able to handle more customer inquiries simultaneously. For example, an agent can handle up to 6 mobile live chats in the time it takes to answer one traditional voice call. 

By enabling two-way mobile communications via SMS or Facebook Messenger for services like appointment bookings, parcel delivery notification, payment reminders or complaint handling, a business can significantly improve the customer experience by allowing customers to respond quicker and in situation when traditional contact methods would be impractical or intrusive.

How does your solution help organizations to diminish inbound traffic by enabling instant communication between agents and customers via SMS and Facebook Messenger?

Over recent years we have seen a significant shift in consumer behavior - 68% of consumers now prefer messaging channels such as SMS, Skype or Facebook Messenger to contact an organization.

We specialize in integrating mobile and digital messaging channels into an existing contact center infrastructure, such as an existing agent desktop. This allows organizations to roll out new customer service channels quicker than was previously possible.

Our intelligent AI-assisted chatbot approach for lower-value inbound inquiries helps to deflect calls to less expensive communication channels. A seamless handover between chatbots and agents with intelligent inquiry routing can also help to solve customer inquiries faster. 

With our approach, we have helped clients reduce operational costs by 25%, lower inbound call volumes by more than 15% and improve the first contact response rate for outbound by 60%... key improvements in contact center KPI's.

Can you briefly explain how companies can get valuable customer feedback to identify possible areas of improvement by creating and deploying mobile surveys?

Mobile surveys are a great way to get direct customer feedback in the moment that impacts customer experience and informs Voice of the Customer initiatives. Automated surveys use mobile text messages or recorded voice to garner feedback and can be personalized with CRM data. On average, a messaging-based survey is responded to within 10 minutes of distribution and has a 10 times higher open rate than email. 

What differentiates your solution from other mobile messaging offerings available on the market?

With our IMIconnect platform we provide organizations with an end-to-end solution to create, build and manage communication flows across more than 10 communication channels, such as SMS, Voice, Push, In-App, Email, Facebook Messenger and more. We solve for the key issues of channel management, switching and routing, a key to Omni-channel enabler, which hampers organizations progress in the digital arena.

IMIconnect offers pre-built integrations with CRM, marketing, and contact center systems, such as NICE inContact, Salesforce, ServiceNow, Oracle, Genesys, Zendesk to align customer communication across all business systems and processes. This allows for an intelligent, two-way and context-aware customer journey automation, e.g. tailor communication in line with contact policies, consent, and rule-based cross-channel routing.

RapportBoost offers Maci (Machine Augmented Conversational Intelligence) to optimize the conversations live chat agents have with customers. They started out by addressing the premise that emotion had been the missing element in chat and worked to introduce emotional intelligence. Their products help chat agent supervisors and trainers manage their teams, allowing professionals to provide consistent, objective feedback and train their live chat agents without manual transcript review. One agent can handle up to 3-4 chats at a time while maintaining the same level of engagement They also believe in human-assisted chatbots and can work with any chat platform to analyze the conversation. 

The founders were Harvard-educated, one a professor who helped create a series of algorithms designed to produce successful outcomes, creating a funnel for chat and SMS communication.  One of their highlight case studies is with weight loss specialist Jenny Craig, which wanted to revamp their chat strategy. They had 2 teams of 20 people, with a conversion rate running at about 30%.  RapportBoost obtained their chat data and ran it through Maci which produced conversational insights that were used to determine which words helped to close sales.  This knowledge enabled supervisors to give recommendations to the chat team. The agents choose the right path to close the sale.  The supervisors could then give recommendations to coach agents on the chat team.  Each agent has a colored dot on their screen to indicate if they are doing the right thing. Within two weeks of delivering the insight, Jenny Craig’s conversion rate shot up to about 60%.  Co-founder and CEO Tony Medrano delved deeper into the concept of developing chat intelligence.

What is “Maci” and how can it be used to improve the quality of live chat?

Maci is RapportBoost.AI’s Conversational-Platform-as-a-Service that classifies, models and analyzes every word, message and conversation in a given data set across hundreds of dimensions. The cPaaS then performs hundreds of thousands of simulations to derive and test the actions taken in live chat conversations that matter most to the KPI’s brands choose, such as conversion rate, order size, retention, renewal, cost per interaction, first contact resolution rate and customer satisfaction.

It is mission-critical for retailers to engage potential visitors in channels they prefer and by building true rapport. Conversational Commerce is becoming more mainstream by the day and is the next generation of retail. Millennials preferred method of purchase is now short-form communication (i.e. chat, SMS), and brands that implement it will grow market share. Chat lacks the vocal cues of phone and the opportunity for lengthy exchanges of email. Live chat optimization recovers the emotion, nuances and context that get left out of digital, text-based communication.

Why is it important for a solution to have the capability to analyze an infinite number of variables as well as larger data sets than had previously been possible?

Maci augments the intelligence of human agents, which means making statistically viable recommendations requires evaluating as much relevant data in a myriad of ways as possible.  

To give your readers an idea, we recently worked with a medium-sized customer doing e-commerce with about $25 million in annual revenue in a highly competitive market. They gave us chat data consisting of about 200,000 visits. That equals a medium size data set — 3 million messages —  enough to draw some insights. Anything less would mean some situations were not included in the analysis. That can affect the conversational insights that Maci recommends and impact the company’s ability to provide top-tier service. 

How can companies ensure that there is a “human-in-the-loop” to maintain brand equity and build enduring customer relationships in chat interactions?

Bots struggle to engage with consumers authentically. They’re not good at selling; they often don’t reflect the brand identity. For brands that want to convey a fun, fresh personality, bots feel robotic, and people pick up on that. Brands that care about having authentic conversations with high value clients do not use bots as brand ambassadors.

One reason bots fail so frequently is that many use simple decision trees. You can think of them as a programmed menu that includes possible questions and answers. The problem arises when a customer deviates from the script (as humans often do), at which point the bot reverts to the main menu or provides a canned answer. Potential customers feel devalued, not engaged.

What differentiates your solution from other similar offerings available on the market?

While Maci does fall under the umbrella of being classified as an Artificial Intelligence technology, we employ it to augment human intelligence. More specifically, we use AI to improve chat agent performance. We’re confident in this approach for two reasons:

It’s the best application of the technology now. In its current implementation, AI is capable of two things: (1) automating repetitive tasks by predicting outcomes on data that has been labeled by human beings, and (2) enhancing human decision-making by feeding problems to algorithms developed by humans. Our Conversational-Platform-as-a-Service helps the humans behind successful sales and customer support interactions perform better at their jobs. We do this by employing predictive outcomes based on unique data and customers. Maci helps chat coaches develop unbiased, effective training strategies to empower live chat agent performance and achieve significant operational gains.

The emotional intelligence (EQ) of humans is what drives engagement and lifetime value. EQ is a human competence that’s difficult to teach machines because it involves intuition, empathy and moral judgment. These traits make up the qualitative aspects of human interaction that are difficult to quantify and draw insights from using data. By testing variables in conversations across hundreds of dimensions, we’re able to architect a conversation that will most often result in success for the brand. Better conversations are enjoyed more by both the agent and the potential customer and most often result in success.

Sitel Group tsc After Groupe Acticall acquired SITEL Worldwide Corporation, they created Sitel Group, which successfully combined the DNA of both companies and brings together comprehensive customer care capabilities with unparalleled digital, training and technology expertise to help build brand loyalty and improve customer satisfaction. TSC is a company of Sitel Group, offering start-to-finish solutions for digital customer experience management needs including brand community development, social media research and insights, strategic social media business plans and omnichannel UX design and development

Sitel integrates AI provider Rul.ai as their underlying technology. Beyond having the platform, Sitel also does consulting work and professional services as well.  They work with IT groups from the client side.

Presently, they are using their digital technology for Sitel BPO clients. They consult with the client on where bots will make the most sense and plot out a strategy for them. They can, however, work with companies that are not using Sitel services. Sitel is responsible for the results of the bot.  They charge clients based on performance; a resolution-based model. Upon communicating with a customer, organizations first use a bot.  If necessary, the conversation can escalate to hand off to agent.  Gordon White, General Manager, Americas for tsc: - a Sitel Group company –offered his perspective.

Why do you believe that delivering a superior customer experience will require a symbiotic relationship between bots and human agents?

A bot, at the end of the day, is still a machine built by someone who makes choices on its behalf. Will machine learning and natural language understanding mature to the point where bots carry on conversations at the same level of sophistication as a human? No doubt, but today we are still in the infancy to toddler stage where they are first learning how to walk.

The bot needs constant attention by someone who knows how to take over if it stumbles. If the job of the bot is to answer customers’ inquiries, then it stands to reason that the people who assist customers every day are the best resources to train the bot and help it learn. 

Most conversational (versus scripted) chatbots are built using open source natural language platforms - like Stanford NLU. They have access to immense data sets and should be able to handle most common words and phrases without too much difficulty. Words like “invoice” are part of that data and a bot shouldn’t have trouble recognizing them.

Brands, however, often have their own proprietary language – they might call their invoices “eBills” or “FastPay Statements”. No NLU engine will understand those words. And, while you can program those things in before you launch, there are always items that are inadvertently left out or overlooked.

Human intervention is important when the bot gets confused, first to resolve customers’ issues and after, to do the work to correct any confused intents. Customer service agents, who train on brand-specific products, and who are charged to speak to customers on behalf of the brand are the right choice to do this work. It’s a daily, constant job and needs to be incorporated into the everyday workflow of a brand. 

In this way, brands can improve the efficacy and precision of their bots to help them get past the awkward stage and stand up on their own as a true complement to customer service teams.

How will companies be able to determine the optimal balance between human and bot involvement?

The best way to understand the optimal balance - like any customer-facing technology - is to test and refine and test and refine and…

The line between human and bot interaction will change and evolve as the technology improves and as humans become more accepting of bots as valuable interlocutors in the overall brand customer relationship. Data on resolution, frustration, satisfaction and efficiency are key indicators as to whether the human-digital mix is successful.

One approach is to A/B test a bot that hands off (to a live agent) at different levels. Can a bot handle a little bit more? Is it causing more frustration or resolving issues more efficiently than a human can? In an industry where we measure interaction metrics so closely, we should be able to determine the right mix for today, understand where the gaps are and how to improve or change the mix for tomorrow.

In what ways does TSC enable organizations to better manage the digital customer experience?

TSC’s main role is to provide clarity and focus to brands who are transforming digitally. We serve as consultants and translators of best practices, we build new experiences, and we help run and optimize the digital priorities brands striving to achieve today - from digital solutions like chatbots, to social communities. It’s been our experience that while brands fully understand the imperative for change, they don’t always have the internal expertise or validation to start. We help bring both and are thus moving them forward and building happier relationships between their business and their customers.

Can you provide a few brief examples of how you have used digital solutions to help shape better business outcomes?

Cox is an important Sitel Group client and we manage 100 percent of their chat queues today. As volumes increase, and as more of their customers are choosing chat versus voice as their channel of choice, Cox needs to find a way to manage costs, while simultaneously driving better resolution in the channel. Currently we’re working with Cox to build a bot that handles some of the more transactional use cases around billing. The resultant bot should decrease overall chat volume, while at the same time, resolve customers’ issues more quickly and efficiently.

Earlier this year we helped Whirlpool launch a new Visual IVR solution for their Brazilian customers. The solution digitizes interaction at the point of call and helps route to self-care and more effective resolution channels. The solution was ROI-positive in the first two months of launch and has helped deflect over seven percent of overall volume for the brand.

Smooch connects business software to worldwide messaging channels to deliver a more human customer experience. They provide the underlying platform that companies such as Oracle, Genesys, Lithium, and Zendesk use to connect all the messaging channels. It’s a true omnichannel conversation platform: with a single API, Smooch connects a client’s software to any messaging channel, unifying all customer interactions into an omnichannel conversation. They offer a single ID for each individual. In a demo, they showed an individual starting with SMS, on the app: the person can then select Facebook Messenger or any other social platform.  From mobile, they are then taken to Facebook Messenger and can continue with the message.  The entire conversation is recorded and the person can move from channel to channel.  

Smooch connects quickly to channels and standardizes them. They charge monthly or annual support and license fees, as well as usage-based messaging fees. In addition to customer service platforms, some end-user brands choose to integrate directly with Smooch and then connect Smooch to their existing customer engagement platform Some end-user brands are on the platform and offer a direct messaging service through Smooch.  Many software providers are rolling out new omnichannel messaging solutions built on Smooch. They are moving toward becoming the broker of messaging across the world’s unique and siloed messaging platforms. Warren Levitan, CEO, provided additional details.

In what ways can businesses reduce the complexity of omnichannel messaging?

Brands focused on customer experience have long been committed to being where their customers are, but with the rise of messaging and proliferation of non-standard channels we have passed the tipping point of being able to manage all the channels through siloed platforms.

To make the complexity of omnichannel communications manageable, businesses require a helpdesk or contact center platform that unifies all their communications into one agent interface. Email, SMS, RCS, web chat, mobile in-app chat, Facebook Messenger, Apple Business Chat, WhatsApp —the list goes on —  all need to be viewed simply as "messages" to the business, requiring no change in agent behavior or bots to handle.

Why is it critical for organizations to maintain a unified view of customers across touch points?

The channels consumers choose to engage on today are highly context-driven. When on a business' website, a web messenger is the logical place to engage. But if a business needs to follow-up with me after a chat on their website, I want them to message me on a mobile channel, such as WhatsApp. Two channels, one conversation.  

Now imagine a month later I see an ad on Facebook from the business for a new product that addresses the need I previously inquired about on the web site, and then learned via WhatsApp was not yet available. I click on the Messenger ad (a click-to-message ad!), end up in Messenger and ask: "So is this product now in stock?" Same conversation, three channels. And if the product is complex in nature, and I want to quickly connect by phone to ask a technical question that is easier to address live, we are now up to four channels within one conversation. 

This is what modern communications look like. Without a unified view of customer conversations across channels, the business would be missing the necessary context to serve me properly and frankly some of these very natural and expected experiences wouldn't even be possible.

How does your solution enable companies to simplify messaging development and support emerging messaging channels?

Smooch has integrated and aggregated all the world's leading messaging channels into a single unified conversation pipeline. Within that pipeline, we normalize all conversation data into a standard format that can be ingested by any customer engagement software that a business uses — contact center, helpdesk, CRM, live chat and social support platforms.

Whatever channels a customer chooses to use, Smooch will associate with that user and unify into one conversation stream inside the business’s software. When the business responds, Smooch not only routes the message to the customer's preferred channel (or multiple channels), but Smooch also translates the formatting and presentation of the message to optimize it for wherever the user reads it. Smooch is pre-integrated with and counts leading customer engagement platforms as customers, from Zendesk and Lithium to Genesys and Oracle.

What differentiates your solution from other omnichannel messaging solutions available on the market?

It’s easy to confuse a multichannel solution with omnichannel solutions. Multichannel is simply being where most customers already are; that’s table stakes. Omnichannel allows context to follow users across any channel they choose to use. The reality is there are few truly omnichannel platforms available, and to the best of our knowledge, none in the world other than Smooch has unified 18 independent communication channels in this way.

Solvvy is reimagining customer support through intelligent automation. Powered by artificial intelligence at its core, Solvvy learns from a company’s existing enterprise knowledge and history of customer interactions to answer incoming customer questions. It enables companies to understand customer intent using natural language processing as opposed to the keyword search often employed by other solutions.  Solvvy makes use of machine learning (ML), deep learning and transfer learning to build an AnswerGraph from a client’s knowledge base, ticket history and other internal data sources. It pulls “snippets” from the knowledge base or from official sanctioned documentation to help resolve customer questions. It also sets up categorization of incoming tickets: for example, a food delivery business might have categories such as food spoilage, missing ingredients and delivery slowdowns. The business can then take action based on insights gained from categorizing tickets in these areas. Solvvy works on various channels such as web, mobile and chat. Over the next several months, the company plans to add end-to-end automated workflow to its already impressive capabilities. Kaan Ersun, SVP of Marketing, expounded on the benefits of the solution.

How do you use intelligent automation to enable companies to provide “always-on’-channel service?

Intelligent automation is the key to delivering great customer service in a cost-efficient manner. Solvvy leverages the power of AI to support customers 24/7 without live agents. Using natural language processing (NLP), Solvvy interprets customer questions written in conversational language to accurately resolve customer issues by serving up precise solutions from a knowledge base. Solvvy provides an “always-on” channel of service while enabling customer support teams scale cost-efficiently by reducing ticket volume. 

In what way does minimizing the amount of customer effort needed to achieve issue resolution improve satisfaction ratings?

According to Forrester, 73% of consumers say that valuing their time is the most important thing companies can do to provide them with good customer service. Solvvy’s under-a-minute resolution time helps reduce customer effort by eliminating the need to spend time searching through lengthy help center articles or to wait on the phone to speak to an agent. Additionally, support agents do not have to spend time answering repetitive questions and can focus on resolving complex issues, which also helps increase overall customer satisfaction ratings. 

How does the use of natural language processing (NLP) along with machine learning, deep learning and transfer learning allow companies to create a reliable mechanism to answer inquiries?

Natural language processing is a key component of an intelligent system that’s customer facing. Our co-founders’ NLP research at Carnegie-Mellon is at the core of our customer-facing solution that allows us to understand everyday human language. Instead of relying on keywords, Solvvy intelligently understands a user’s intent and accurately resolves issues. 

We also leverage the power of machine learning (with some deep learning components) to improve accuracy over time, learning from successful and unsuccessful resolutions in the past history of tickets. Our system gets smarter with every interaction and transfer learning allows each new customer to start using Solvvy from a higher baseline since the core system continues to improve and learn.

What differentiates your CX automation solution from other offerings available on the market?

Solvvy is the only customer-facing solution in the market that can boast of a 25% self-service ticket resolution rate across our customer base. In addition to the technology advantages already discussed, Solvvy has two key differentiators compared to other offerings. Our first unfair advantage comes from data. One of the biggest determinants of success in machine learning is the amount of good training data. We have been able to achieve this level of self-service by serving over 250 million users and learning from every single customer interaction. The second advantage is our fast time-to-value metric. Thanks to our effortless SaaS deployment and transfer learning, Solvvy can go live into production in a week with almost no engineering and training effort from our customers. We plan to stay 100% focused on our mission of enabling easy and effortless conversations between businesses and customers, and we are investing our resources in continuously improving the customer experience for our clients.

Veritone unlocks the power of cognitive computing to automatically generate actionable insights, previously inaccessible to organizations in their audio, video and other data sources. It is particularly valuable in legal environments, harnessing the power of artificial intelligence for eDiscovery and compliance professionals, enabling them to cost-effectively manage and analyze large volumes of unstructured evidentiary media and case material in near real-time and at significantly lower costs. Legal and compliance teams are using AI today to transcribe, translate, redact and find objects - all with structured and conceptual analytics - with higher accuracy results by blending and orchestrating multiple cognitive AI engines, pulling in the strongest AI engine to address specific areas. Michael Swarz, J.D., Product Marketing Manager, Legal, provided more details.

Why do you consider so many businesses to be data-rich yet intelligence-poor?

The amount of data in the world today is mind-boggling.  According to a recent IDC survey, there are 7,910 exabytes of data in the world (a single exabyte is a 1 followed by 18 zeroes).  Furthermore, the same survey found that the same amount of data in the world that existed from the year 0 to the year 2014 is the same amount of data that is created every 15 minutes today.  With all this data – which, according to Gartner, is 80% unstructured data such as audio & video files – it’s no wonder organizations are seeking solutions to gain actionable insights into the quality of their data to meet electronic discovery, regulatory compliance and business intelligence requirements.

In what ways does your aiWARE operating system enable organizations to unlock and use the full power of cognitive computing to derive actionable information from a variety of sources?

aiWARE by Veritone enables organizations to unlock and use the full power of cognitive computing to derive actionable intelligence from a variety of sources by resolving critical and often systemic issues facing industries, institutions, and individuals by leveraging advanced AI systems, large hyper-scale databases, and proprietary data feeds.

AI systems span many functions, some replicating capabilities of the human brain, such as natural language processing, face and object recognition, sentiment analysis, anomaly detection and prediction, while others analyze and learn the patterns that surround us.  aiWARE unlocks the full power of cognitive computing to derive actionable intelligence from these sources.

Our platform of top-notch cognitive engines is processing information at volumes and speeds designed to mimic and exceed the processes of the human brain. These engines, working together, acquire knowledge and understanding through thought, experience, and the senses. Veritone believes that for AI to truly come to life and reach its full potential, the cognitive cloud must be open to all businesses, institutions, and individuals.

How can your platform be deployed to increase efficiency and improve customer interactions in the contact center environment?

To increase efficiency and improve customer interactions in contact center environments, our aiWARE solution provides automated near real-time surveillance capabilities for call center audio calls.  We can help find spoken words and detect when specific words are spoken in call centers.  What's more we can also find faces and determine speaker sentiment and objects from video calls if a call center has that capability.  We automate and improve call center workflow processes and efficiencies.

aiWARE can transcribe, translate, redact, analyze call center conversations and can also plug into existing phone recording systems and review platforms to provide call center clients a near real-time experience. Our accuracy, ability to deploy custom workflows and open ecosystem allow us to understand call center data and configure the best workflow for optimum results.  We do so by orchestrating multiple cognitive artificial intelligence engines to translate and transcribe call center recordings, which in turn provides call centers: workforce optimization and flexibility along with enhanced accuracy and convenience. 

 In what verticals does your solution enable companies to meet regulatory compliance requirements?

Verticals currently enabled by Veritone’s aiWARE solution include: Legal & Compliance, Media & Entertainment and Government.  At the same time, aiWARE is designed to deliver insights for any industry to realize the full potential of artificial intelligence.  Veritone offers multiple deployment models, applications and integrations addressing a broad range of business and organizational challenges, while identifying new opportunities for growth.