Nuance - ContactCenterWorld.com Blog
As the old adage goes: When life gives you lemons, make lemonade.
I was given my lemon not too long ago when I experienced a shoulder injury that basically halted my ability to type on a keyboard. As a presentation director, bid consultant and frequent blogger, the inability to type was jarring. How was I supposed to get my work done and serve my clients while waiting for my shoulder to heal? When I mentioned this issue to my web support tech team, they immediately pointed me in the direction of Dragon for my MacBook Pro.
Although I had originally learned about Dragon several years ago, at the time I didn’t feel that it was a product I needed for my professional or everyday life. But with my shoulder injury taking center stage and disrupting my livelihood, I decided to give Dragon a go.
I started the training and was pleasantly surprised with its speed and accuracy. I have a unique accent –part English, part Canadian with a hint of Australian – and Dragon has been able to accurately transcribe the lion’s share of what I have dictated. And while it has taken me a little while to get used to dictating as opposed to typing, I have come to love it for a number of reasons. The first being that, current shoulder injury aside, I am dyslexic and as a result writing can be a major obstacle. For instance, I sometimes mix up words when typing – from misspelling common words and homophones such as “their” and “there” to occasionally typing text that does not flow or is out of order. Because of my dyslexia, I spend nearly 20% of my time correcting the text after I have typed it. Given that Dragon can decipher language and context, the issues around homophone confusion and flow are mitigated, and I am able to publish one to two articles per week, which was unheard of for me.
The second reason that I have come to love Dragon is that it has enabled my blog to become my “lemonade”. Shortly after I started using Dragon to dictate my blog, a friend of mine who also happens to be a former producer with the Canadian Broadcasting Corporation (CBC), contacted me. He asked me what I was doing differently – was I working with a writing coach, for example – because the style of my blog had changed. It was more conversational and free flowing. He could hear my voice and personality when he read it; and he loved what he read. And he wasn’t the only one. Others have commented about my newly found style.
I have since introduced Dragon to other parts of my life. I am using it to dictate and reply to emails, as well as write my client newsletters and write another book. Using a high-quality performance mic, I am also able to capture my discussion notes quite well. Dragon has also alleviated a great deal of physical stress on my body. As a 70-year-old, sitting in front of a computer to type isn’t in my best interest. Using my voice allows me to move around the room and dictate my thoughts for presentations and proposals, my blog and more.
Although I’m not happy about my shoulder injury, I am happy to have found a solution that has helped me realize a new level of writing.
Publish Date: June 23, 2016 5:00 AM
Just like technological advances before it, mobility has become a mainstay across a wide range of industries. While millennials are a driving force behind this shift, given that this younger population will account for 75% of the U.S. workforce by 2025 and the majority of these millennials (80%) are already armed with smart devices; mobility is becoming the new driving force behind today’s work culture and will continue to impact the bottom line.
Enterprises of all shapes and sizes are realizing the achievable ROI with mobility. In fact, 70% of organizations see mobile solutions as essential to supporting the changing workforce (Ranstad Technologies/IDG). We’ve finally moved beyond debating ‘if’ and ‘when’ enterprises are going to mobilize their workforces, to what types of applications or services are going to bring the most value to businesses and their employees – whether they are Millennials, Gen Xers or members of Generation Z, who soon will be joining the workforce ranks.
Apps that foster productivity reign
With the ability to improve business processes, particularly productivity, cited as the number one benefit of mobility (according to the 2015 Enterprise Mobility study conducted by Apperian), it’s no wonder that productivity apps, such as note-taking solutions, earned the top ranking for having the greatest impact on productivity and ROI.
This is extremely applicable to professionals whose jobs require endless necessary documentation of client or case interactions such as legal, public safety or social services. This aspect of the job is neither fun nor career enhancing, and often requires them to be tethered to the office. With mobility in mind, professionals want to be able to capture their thoughts while on the go and access this content from anywhere.
It’s no wonder then that Evernote, with its multi-platform and cloud-management support, is used by millions of mobile professionals as a note-management tool. The wide range of Evernote’s tools free users from the confines of an office and enhance collaboration and productivity from wherever their work takes them.
Access, but also creation of content leads more and more professionals looking to their mobile devices as a note-taking tool, but mobile devices small touchscreens don’t lend themselves to long-form writing and detailed note taking, as noted in a recent survey. Voice driven solutions such as Dragon Anywhere, Nuance’s cloud-based, professional-grade mobile dictation solution give mobile professionals the ability to think and document accurately and quickly – in the moment on their mobile device. In fact, Evernote is now integrated as part of Dragon Anywhere to synchronize notes and documents of any length between your Dragon Anywhere and Evernote accounts.
Marry the ability for real-time, long-form note taking with immediate access to content, and this is what mobility is all about.
Solutions that allow both creation and access to content in the cloud and across any platform will greatly benefit professionals who seek the freedom and flexibility that mobility brings, and can only benefit the businesses that embrace this new work culture.
Publish Date: June 21, 2016 5:00 AM
When you think about bank robbery do you think about Bonnie and Clyde? Or some bad guy with a facemask holding a gun and forcing a teller to put all their money in a bag? If so, then you probably grew up watching the same shows I did, but more seriously, you may have a skewed view of today’s highly successful bank robbers: fraudsters.
Today’s fraudsters are growing more sophisticated and technologically savvy. And fraudsters have found a new way to steal information: impersonating company executives to authorize wire transfers to untraceable locations. Data from the World Bank shows that the remittance market is currently $527.8 billion and is growing fast; it is expected to reach $610 billion by the end of this year. That’s a lot of money which is susceptible to attack. But how do these fraudsters do it and how can you protect yourself and your customers?
How fraudsters steal money
These fraudsters gather information to make wire transfer requests as believable as possible. They identify when an executive is traveling, craft an email to the victim with a request for an immediate wire transfer, and then “poof” the money is gone!
Sounds implausible doesn’t it? Unfortunately, all too many have found it to be a very real scenario. A woman in Ohio almost lost her company $315,000, a company in Omaha lost $17.2 million, and another company in San Jose lost $46.7 million, all due to fraudulent impersonations and wire transfers.
According to AFP research, wire transfers are the second most popular vehicle for payments fraud, only behind checks. We are not talking small amounts; data from the U.S. Secret Service says wire transfer fraud has cost victims more than $1 billion in just 18 months.
But the good news is that there is a way to mitigate these attacks.
How voice biometrics protects companies from fraud
Multi-factor authentication, the practice of using more than one method of identity verification, using voice biometrics is a fool proof way to ensure a wire transfer request is being made by the right person. Voice biometrics leverages more than 100 unique speech characteristics to create a unique voiceprint (just as individual as a fingerprint) for each customer, making it a highly secure method for authentication.
Voice biometrics is currently being used by millions of people and being adopted by organizations around the globe, including financial institutions, telecommunication services providers, and other enterprises that require validating the identity of users within customer care channels.
Voice Biometrics are gaining ground with these enterprises because not only does it make accounts more secure from the threats posed by identify theft, social engineering, and data breaches, but it also allows for faster authentication. Unlike trying to remember PINs or passwords or even worse, those unusual security questions (your favorite pet, like you can pick just one), voice biometrics can be used with a prompted passphrase like “My voice is my password” or it can work in the background to verify identity without interrupting the normal dialog between a customer and a company representative.
So it’s no wonder 90 percent of users prefer voice biometrics as an alternative to PINs and passwords.
OK, so how would it work?
In the case of a bank, the officers who are responsible for authorizing wire transfers would all enroll their voiceprint into the system by recording their pass phrase three times. Once the voiceprint is created, any time an authorization is needed they merely call in and validate the transfer. This way the poor phone attendant is not the one making the decision as to whether the person on the other end of the line is actually the CEO.
Publish Date: June 13, 2016 5:00 AM
If you’ve been reading my series, you know that AI and machine learning (ML) can have a powerful impact on delivering the best possible customer care experience. Specifically, we’re applying “big knowledge” for customer service tasks. What does this mean?
The first task we want to look at is “passage retrieval,” or finding relevant text parts that contain the answer to a question. It helps to solve the “simple” intents in the customer service application we mentioned above, where customers ask for something that is (hopefully) contained in the document data base. And instead of searching for words only, and hoping that customer question and target document use the same language, we will apply what we learned in the last part of this post.
As the diagram shows, the trick is that we run both the database of documents and the question through the Natural Language (NL) pipeline and generate enhanced dependency trees. The former is done offline to compile an index of such trees and the question is processed at run time. The best matching trees are selected as the answer candidates and the text passages are then ranked, and the best candidate reads back to the customer. When we tested this at a customer we found that it worked much better than their legacy search tool, which was based on traditional word-level search. That worked reasonably well when customers used an appropriate keyword (it would find the right answer in 84% of the cases) but it degraded a lot when people were using full natural language queries (54% success). Our new solution scored 96% and 81% respectively.
Similarly, we are now using this for another typical ML task, “clustering.” As I mentioned above, when customers contact the agents they may have one of several different “intents” or buckets of tasks in mind. How do we know which “buckets” exist? Of course you can do a manual analysis, which may be very time consuming. Instead, you can also use ML with methods that try to find “clusters” of things that look similar compared to the rest of the data. In our case, imagine you look at 100,000 requests that came in, can you find 100 or 200 or 500 “buckets” that can be mapped to request types or intents? If you do this automatically the additional benefit is that you can monitor how requests change over time, as what your customers want from you may also change over time. The naive approach is to apply standard machine learning clustering approaches on the initial requests that customers have, at world level. But given what we learned in this blog series we can improve over this in two ways: First, we will not only use the initial user utterance. Instead as we can observe the entire interaction, like what the human (and automatic) agents actually do with the request, we should take that entire interaction into account when clustering. And secondly, again we will use our NLU pipeline to transform mere words into semantically enriched trees and runs the clustering algorithms in these.
Both of these approaches again allow us to reduce annotation time before a technology is put in use, and allow us to take advantage of the unstructured data that so many enterprises have readily available. The virtual assistant is in essence not only doing something useful for the end user, but also helping to translate a company’s unstructured data into exactly the kind of labeled big data that will allow the virtual agent to move towards state-of-the-art AI learning.
So, big knowledge means big changes coming to customer care through human assisted virtual agents (HAVAs). With the right methods in place, they can drive a more collaborative engagement between humans and machines to create an effective and efficient customer experience for people around the world.
Publish Date: June 7, 2016 5:00 AM
Virtually any article on customer service or customer experience these days contains one or several of the following key words: multi-channel, cross-channel, and omni-channel. Though these words are often used interchangeably, each has a different definition and application. To demystify the jargon, here’s a quick guide to what these terms actually mean and how they can be applied to your business’ customer interactions.
A multi-channel approach simply means that you are using more than one channel to reach customers. This concept isn’t necessarily new, right? Whether it was telephone, mail, or in-person, there’s almost always been more than one way to reach a company. However, with the rapid proliferation of channels in recent years – from text messaging to social media – the notion of multi-channel is more important than ever. It’s expected there will be an average of nine customer experience channels for more organizations by 2017. As customers now have more channels at their fingertips, businesses must follow suit to keep up with customer preferences.
An example of a multi-channel approach is when a company offers customers multiple mediums to choose from to reach the business – whether email, phone, text, or website – and customers are given the ability to select whichever option they’d prefer to communicate through.
Cross-channel refers to the idea that a customer uses a combination of channels to perform a task. A cross-channel approach builds off the multi-channel strategy. Since customers now have access to more channels, it’s natural for them to use more than one to accomplish their goals. This approach allows customers to use multiple channels in tandem.
For example, a customer who has a question regarding a product may start by looking at the company website’s FAQ, then call a customer service representative to gather further specifics.
Just as cross-channel builds on multi-channel, the omni-channel approach builds upon both of the previously stated strategies. Omni-channel recognizes that customers are actively using multiple channels (often simultaneously) and aims to streamline those interactions. By saving customer preferences and information, and referencing that data in all subsequent interactions, an omni-channel approach creates a seamless and consistent customer experience across channels. Essentially, it means that all the channels a business employs work together.
For example, let’s say a customer makes a payment online. But the next time around, the customer calls a representative to make the payment. In this scenario, under an omni-channel approach, the customer service rep will be able to immediately reference the information from the past payment interaction. The customer doesn’t have to repeat all of their account information and preferences, because the representative already has it.
But why does this all matter? Simply put, customers don’t live in a single-channel world. From mobile phones to smart watches, the way customers communicate is different than it used to be. People expect and demand to be able to use which channel they want, when they want it, where they want it. And if businesses don’t comply, they’ll fall behind to competitors who are more than willing to meet customers where they want to be. Furthermore, businesses who integrate these strategies will not only boost customer satisfaction, but they can save time and money while doing so by streamlining their customer interactions.
So with these definitions in mind, revitalize your customer service and put these terms to work!
Publish Date: June 6, 2016 5:00 AM
The future is upon us. Companies are now starting to adopt technologies that can verify identity which were once thought overly futuristic (HAL had no problem identifying Dave in 2001: A Space Odyssey). Fingerprints are no longer the only unique body identifier: irises and even ears are now on the list of biometric authentication tools. But the identification opportunity that’s the least understood is voice biometrics, mostly due to misconceptions about what voice biometrics actually is and whether it is secure.
Let’s take a couple minutes to dispel some of these misunderstandings, so you can determine if voice biometrics is the best way for you to provide a seamless authentication experience for customers.
Myth #1: People can overhear me and will be able to steal or use my password.
For more than 20 years the internet has been telling people to “Never give out your username and password or very bad things will happen.” Even my own son was leery of typing his password with me looking over his shoulder (granted, that may have been due to good reasoning). Keeping one’s password safe is just good sense. Why would I speak my password somewhere where fraudsters could hear me?
The important distinction with this misconception is your voice is your password. Voice biometrics leverages more than 100 unique speech characteristics to create a unique voiceprint (just as individual as a fingerprint) for each customer. The words you speak do not grant you access to your account – the unique characteristics of your speech pattern are your password. There are both physical and behavioral characteristics of a person’s voice. Physical characteristics such as the shape of your vocal tract, how your mouth moves when you speak, and the size and shape of your nasal passages are unique to a given individual. In addition, voice biometrics recognizes unique behavioral traits such as pronunciation, speed of speech, pitch, and accents. No one can steal your account information simply by hearing you speak a passphrase.
Myth #2: Everyone says I sound just like my Dad; wouldn’t he be able to log into my account?
You may sound just like your Dad to everyone around you, but to the voice biometrics system you are two distinct individuals. As a matter of fact, WIRED Magazine recently put Nuance’s voice biometrics to the test by comparing famous people to master mimics – including Kevin Spacey. While the mimics sound just like the originals, voice biometrics was not fooled.
Myth #3: My voices changes all the time. I’m worried I won’t be able to get into my account if I have a cold.
This misconception is one of the most common ones, and many CIOs, contact center managers and other people consider it a show-stopper. But numbers prove otherwise.
For example, Nuance’s VocalPassword solution has delivered successful authentication rates within customer-facing IVRs 97 percent of the time. On average, a person with a cold tends to experience an error rate that is about double the average. As such, a person with a cold has a 94 percent chance of getting successfully authenticated, which is still significantly higher than the 40 to 60 percent success rate customers typically experience with a PIN or password. The high success rate for people that have a cold is made possible by Nuance’s approach of analyzing more than 100 aspects of each caller’s voice, and a cold affects only a handful of those.
Myth #4: If someone hacks the company’s database they will have access to my voiceprint.
After the Target security breach of 2014, everyone has been talking about what happens when a hacker gets your credentials. Unlike with a username and password, the hacker cannot use what they have stolen because it requires the back-end to process the voiceprint. Even if they were able to steal the recorded voice, Nuance provides playback detection to protect from spoofing. This feature tests incoming audio to see if it represents live speech or if it fraudulently uses a recording of an authorized speaker, mitigating the risk of fraudsters using voice recordings of legitimate speakers.
Infiniti Research estimates that voice biometrics can address 90 percent of fraud in a voice channel, as well as address 80 percent of fraud in a mobile channel. So even with hackers on the prowl, your data is safer with voice biometrics.
Myth #5: I don’t like biometrics because it is based on something that cannot change (Fingerprint, iris, voice) and if I need to change my password it cannot be done!
Unlike fingerprints or iris’, which are static biometric credentials, voice biometrics is a dynamic biometric credential. A static biometric, like a fingerprint, is unchangeable, while a dynamic biometric is constantly evolving.
Most of us have ten fingers, so there is a small amount of variability that is possible: if you enroll your right index finger to authenticate into a system, and a hacker compromised your fingerprint, you could enroll another finger. But at the end of the day, you have a maximum of ten possible credentials with fingerprint biometrics. With iris, that number drops down to two. With voice biometrics, you have an infinite amount of possible voiceprints.
Let’s say that you have the following voiceprint to authenticate into your account: “My voice is my password at VB Bank.” Should a malicious individual record you saying this passphrase, you could revoke this credential and create a new one where you say “At VB Bank, my voice is my password.” You can easily see how there are an infinite amount of possibilities with voice, and so it’s important not to lump all biometric technologies into the same boat. Irrevocability is only an issue with static biometrics.
Publish Date: June 2, 2016 5:00 AM
The world of customer service looks vastly different than it did 20 years ago. With the pace of change, new channels and higher expectations have forced a change from what defined industry leading service even five years ago. Consumers are communicating in fundamentally different ways and the number of touch points continues to explode.
Gaining massive popularity are messaging apps such as WhatsApp, Facebook Messenger, WeChat and Viber, which tout a combined user base of roughly 2.9 billion. These apps are particularly popular among Millennials, as 50 percent of the users for the ten leading chat apps are under the age of 35. Similarly, chatbots are the hot topic in customer service right now. Companies from Facebook to Google to Microsoft are deploying these all-in-one virtual assistants as new ways to communicate with consumers. And finally, we can’t forget about text messaging. In a recent survey, more than 42 percent of Americans reported wanting to communicate with businesses via text message, but only 7 percent received reminders and notification on this channel. Another 25 percent wished they could conduct customer service via two-way text.
Taken together, these trends paint a clear picture: The market is changing. Message-based communication is what consumers want. To stay relevant, businesses must adapt again.
To address this shift in consumer preference, Nuance announced Nina for Messaging, leveraging Nuance’s Natural Language Understanding and conversational technologies to provide an intelligent, automated experience on popular messaging channels, through a common platform. With Nina for Messaging, customers more easily find answers, solve complex problems and execute purchases via in-app messaging, conversational text messaging, and within apps such as Facebook Messenger. The solution leverages a common mulitichannel platform, allowing businesses to cost-effectively extend a consistent self-service experience across messaging channels, while maintaining control of both data and security. In doing so, Nina for Messaging increases customer satisfaction by creating personalized, effortless experiences that allow consumers to conduct business quickly and easily.
The market momentum speaks for itself – message-based customer service will rapidly represent a quality experience. But this shift doesn’t need to represent added cost to the enterprise. Fifty-nine percent of consumers agree that automated self-service options have improved customer service, according to a recent Wakefield survey. Nina for Messaging is designed to provide the self-service experiences your customers want, on the new channels they prefer.
Publish Date: May 27, 2016 5:00 AM
We all know how good customer service looks. That thoughtful touch. The extra mile. Added efficiency. And effortless interactions. But what specifically distinguishes the customer service leaders from the laggards? What do the leaders do differently? And how can other companies replicate the success model to achieve better customer service results?
The industries which consistently receive high customer service scores may surprise you. Supermarkets, fast food, banking and retail are all at the top of the list.
What do those industries have in common? And why do they hold the key to the treasure chest of customer service secrets? Across these leading industries for customer service, clear patterns emerge in how these industries help customers accomplish their goals and build an experience to admire.
Here are their secrets to success.
- Self-service options. Not only do customers increasingly prefer self-service options (especially Millennials), automated self-service also saves businesses resources. Customer service leaders provide valuable tools which allow customers to solve their own problems and find their own answers, such as self-checkout lines, ATMs, drive-thru lanes, mobile apps, information kiosks, and downloadable coupons.
- User control. Effective customer service allows the customer to be in the driver’s seat. Let your customers do what they want to do, when they want to do it, how they want to do it and then store those decisions as future preferences.
- Personalization. Everyone likes to feel special. Whether it’s a store employee who knows you by name or a barista who remembers your last order, customers enjoy that personal, individualized treatment. Companies with successful customer service often use recommendation engines to help tailor the experience by predicting your next action based on previous interactions and uncovered behavioral patterns.
- Relevant choices. You know the feeling – you go into the department store looking for shoes, then the salesperson spends 30 minutes trying to sell you a watch. Being presented with irrelevant, unwanted options is frustrating. When you have a goal in mind, what can help you make the right choice is critical information and a list of available options. Companies that offer great customer service cut out what’s unnecessary, and only present you with the choices relevant to your current situation.
- Multichannel support. Customers don’t rely on one communication channel alone. They use phone, email, text, web, and mobile apps (sometimes simultaneously). Companies need to leverage an encompassing view of customers, across all channels and contact points, and must consider face-to-face, inbound, and outbound interactions.
These patterns aren’t unique to the supermarket, fast food, retail or banking industries. These principles can be applied and implemented in any industry in order to achieve superior customer service success.
Publish Date: May 26, 2016 5:00 AM
The IVR mindset is shifting. Originally, the essential goals of a company’s IVR were containment and automation. But now there’s a lot more an IVR needs to do to keep customers satisfied and allow companies to reap the business benefits of using an automated system.
Many times customers call into an IVR with the express intent of speaking to a live agent, and 39 percent of customers complain not being able to reach a real person through the IVR system is a top (and regular) frustration. Consumers now view the IVR as a gateway to the call center.
The IVR is increasingly being used as an escalation channel, where consumers only call in when they have already tried to find a solution on their own, and were unsuccessful. So by the time they call the IVR, they’re already frustrated and impatient. In this environment, the purpose of the IVR is increasingly shifting. Its purpose is to provide the call center with immediate information in an effort to route callers to the right agent and reduce call handle times.
With this new purpose in mind, call center metrics are more important than ever. We need to know if agents use the information passed to them by the IVR, whether calls are being routed to the correct agent, and evaluate the length of wait and agent handle times.
There are great tools to evaluate how callers get through the IVR, how many callers are self-served, and how many callers are routed correctly.
But here’s the issue: There’s a dead space between the IVR and the call center, and we currently can’t connect the dots between. Contact center managers need to be able to measure results – the IVR’s direct impact on the call center – and thus the costs to provide customer service.
With the IVR now playing the role as gatekeeper for the call center, the two should be more integrated. This is something the industry will need to embrace as we enter the future of a phone-based customer experience.
The best strategy at this point in time is to treat the entire caller experience as a single call, because for the callers, it is.
Don’t stop tracking the call after it exits the IVR. Following the call into the call center allows companies to monitor the effectiveness more acutely, showing wait time, whether the right agent was reached, whether a resolution was reached, etc. This knowledge allows you to focus on those areas in the IVR that have the most impact on your specific call center, and tailor the experience to meet your goals.
I envision a future with a logging standard, designed to log the agent actions and how they affect the overall call result. This would mean there is one repository for data, and companies can receive full-bodied information with more meaningful insights into their customer actions and adjust the experience accordingly to save money and increase customer satisfaction.
To properly judge a company’s IVR, it’s essential that businesses understand critical metrics such as agent-to-agent transfers and agent handle time. There must be an ongoing industry discussion to address how we can best connect the IVR and the call center. Although this is in the future, there are things companies can be doing now to gain valuable insight into what’s happening in the gap between the call center and IVR.
Publish Date: May 24, 2016 5:00 AM
I’ve been a writer since I was very young. In fact, long before I wrote my first book I won an employee Valentine’s Day poetry contest while working for Harrah’s Casino in San Diego. I even remember winning a poetry contest in elementary school. The poem was about the peace that I felt as a child when walking through the forest, listening to nature. I have come a long way since then and my transition into becoming a non-fiction writer is something that, believe it or not, happened completely by accident.
It was 2011 and I had just moved to Hawaii to renew my sense of self and purpose when I wrote my first book, “Aloha Joe in Hawaii: ‘A guided journey of self-discovery and Hawaiian adventure’.” At the time, I was writing by hand with pen and paper, which I felt was easier than typing on a computer. It took me a full year to write my first book by hand and another full year to type it on a computer. With that much time invested, I believed that there had to be a better and more efficient way to write.
Soon after, I had just purchased a new computer and heard about this new technology called “voice recognition software.” I was really excited to hear about this and after doing some research, I settled on purchasing Dragon Naturally Speaking. It took me a little time to get the commands down and for the software program to adapt to my voice. To speed this process up, I would read a few books aloud with the software turned on. I still remember when I told my kids about my experience trying the software for the first time. Of course, they just laughed at me because apparently they had already been using this technology for several years at school.
Up until that point, I had been taking notes for a number of years on other topics that I wanted to write about, but since it had taken me so long to type the first book, I couldn’t imagine how long it would take for me to type up all of this new information. But after playing with Nuance’s Dragon Software, I decided to find out just how much faster I could produce my second book. The short answer is: three days.
When I gave the finished book to my editor she was pleasantly surprised. After going through everything that I had “composed” in those three days, she figured out that I had actually created enough material for not one, but TWO books! My second book, published in 2014, was titled: “Stories I Can’t Tell My Kids – Yet.” And the third, “Your Brain is the Key to the Universe: A Comprehensive Guide to Manifesting Your Ideal Reality and World Harmony,” was recently up for a Pulitzer Prize in the General Non-Fiction category this year. It is in this book that I reflected on many current issues and also wrote about my experience using Dragon software.
I really do owe Nuance a debt of gratitude for pushing the research needed to advance this field. I am a disabled Marine veteran and I have had many injuries in my life, including disabilities in my hands, fingers, wrists, and more. Dragon software has allowed me to realize my dreams of becoming a published author.
About Joe Holt:
Joe Holt (aka Aloha Joe) is a Pulitzer Prize-nominated author, artist, photographer and life coach. He is the author of Aloha Joe in Hawaii: “A guided journey of self-discovery and Hawaiian adventure” (August 5, 2013), Stories I Can’t Tell My Kids – Yet (August 11, 2014), Your Brain is the Key to the Universe (March 4, 2015). Holt’s fourth-coming book, Godfather of Fisherman’s Wharf, is currently in production, and he just finished his fifth book, a fictional children’s story entitled “Gordy the Ferret.” Both were developed using Dragon Naturally Speaking. Click here to learn more about Joe Holt.
Publish Date: May 23, 2016 5:00 AM
In my last post, I discussed how human agents and human assisted virtual agents (HAVAs) can work together when machine learning and artificial intelligence are applied to customer care systems. Now let’s take it a step further.
In machine learning you often need to compare or “match” things. For example, when you are looking for the right answer in a database, you compare the question to the possible answers stored there. If you want to sort intents into buckets (so-called clustering) you need to compare them with each other and see how similar they are. In many modern approaches you do this by only looking for words to be there (or not) at face value, and in any order, an approach that is also called quite intuitively “bag of words.” If two sentences or texts are roughly composed of the same words, so the intuition, they are probably similar and capture a similar meaning. This approach works surprisingly well for many tasks (classical Internet search relies on this approach), although it seems to ignore that language is actually more than a bag-of-words: sentences have a structure and words have a meaning. Let’s look at these example sentences.
- How do I change the motor oil?
- Tell me how the engine lubricant gets replaced.
From the superficial bag-of-word perspective these look very different, although intuitively they capture a similar request or meaning and customers would expect an HAVA to understand that. Purely statistical approaches solve this by making the observation (after looking at thousands and thousands of texts) that the words “oil” and “lubricant” often appear in similar contexts and in that way implicitly learn the meaning of a word by identifying it with the contexts a word typically appears in.
However, there is a very old tradition within Computational Linguistics and Symbolic AI to capture aspects like structure and meaning of language more explicitly. For one, you try to capture the structure by assigning a syntax tree to a sentence, or an utterance. One class of such structures, so-called dependency trees, starts from the observation that the core of a sentence is the verb and the other words “depend” on the verb; similarly adjectives and other modifiers depend on the noun they are next to. Simplified dependency trees for (1) and (2) above could look like this:
And if you look at the parts circled in red you can see that they have become similar in structure. So if only we knew that change/replace, oil/lubricant and motor/engine mean the same or at least similar things, we would be there. In fact, many efforts have been made to capture such similarities, to sort words into buckets of similar meaning and organize these buckets in hierarchies of concepts. Not the first but a well-known one was Roget’s Thesaurus. Its modern, machine-readable equivalent is WordNet, a collection of 155,287 words mapped to 117,659 concepts (as of today!). And if we look at what it has to say on “engine,” we will see that it lists “motor” as “sister” term to “engine.”
S: (n) engine (motor that converts thermal energy to mechanical work)
- direct hyponym / full hyponym
- part meronym
- direct hypernym / inherited hypernym / sister term
- S: (n) motor (machine that converts other forms of energy into mechanical energy and so imparts motion)
In WordNet lingo that means “engine” and “motor” are in the same “synset,” we could also say they represent the same concept. So, if we now replace words by “synsets” in our two trees, they will become very similar or even identical in the relevant area. That way, measuring the similarity of text passages will be a lot more precise (as we will see later).
Now, the use of lexicons and syntactic structures will strike some people as a little old-school, pitting Symbolic Processing against Machine Learning.
But we at Nuance think differently: why not combine Machine Learning and symbolic processing? Enriching the raw data with syntactic and semantic information helps to turn mere “big data” (think of it as lots and lots of “bags of words”) into “Big Knowledge.” This can then be applied to HAVAs for a better customer interaction. We will explore what else this means for customer service in our third and last post of this series.
Publish Date: May 18, 2016 5:00 AM
Care team communication technology is key for physician efficiency and patient care, as the current amount of time physicians and nurses waste trying to coordinate care without these tools is staggering
This is part of our series highlighting apps that power physicians with voice using the new Dragon Medical One cloud platform.
Care Thread is on a mission to eliminate miscommunication and medical errors in healthcare. They do this with a secure mobile communications platform for hospitals and health systems that allows clinicians to communicate securely and accurately about patient care in real time from any mobile device or web browser. The Care Thread platform, now integrated with Nuance Dragon® Medical speech recognition, is used by all types of clinically-trained professionals to better coordinate care across the continuum while improving the clinician’s experience and patient care.
Jonathon Dreyer: What challenges in the healthcare industry drove you to build Care Thread?
Nick Adams: We were compelled to reduce the sheer number of serious medical errors that directly result from miscommunication. Growing up in the healthcare industry, my co-founder and I witnessed the staggering amount of time physicians and nurses waste keeping track of information, playing phone tag and generally trying to coordinate care. We knew this had to be a contributing factor to the miscommunication.
JD: What inspires you when creating an app?
NA: We build our platform and communication application for all types of professionals who make up patient care teams. Part of our mission of eliminating miscommunication in healthcare is to build digital tools that actually improve the experience of being a clinician today. That is what drives us in everything we do.
JD: Why is it so hard for clinicians to communicate in healthcare?
NA: It’s not that clinicians are bad communicators, but rather there is such a large amount of information to keep track of that there needed to be a better way to stay on top of the information beyond securing text message apps and other disparate modes of communication. We realized communication technologies in healthcare are totally separated from EMR systems so clinical care teams are stuck using old modalities that further the challenge by wasting time and creating delays rather than fixing the issue.
JD: How does your app help enhance physician-to-patient communication?
NA: Care Thread saves physicians the time it takes to get in sync with care teams about each patient. By spending less time gathering information and coordinating care, physicians can spend more time providing care to patients, including directly communicating with them. Additionally, the platform can enable care team-to-patient secure communication, accurately show the patient who their care team is, and make the patient feel that their physicians and broader care teams are working together and are in sync.
JD: How will Nuance technology and the power of voice enhance Care Thread?
NA: By integrating Nuance Dragon Medical and Care Thread, physicians will have the anywhere, anytime ability to dictate communication messages, notes, forms and even Macros templates, back into the EMR. All of the dictation is medically accurate, secure and patient-specific.
JD: What is your vision for Care Thread in the next 5 years?
NA: We see the need for full EMR integration which will enable predictive communications that engage the right people at the right time so every patient is digitally managed. This includes analysis of unstructured text messaging and conversations of care per patient per disease state, to identify the presence (or lack thereof) of pertinent clinical discussion topics.
JD: What do you think the future of mobile health will look like?
NA: The future of mobile health will become predictive, enabling anywhere, anytime patient care that is both proactive and preventative because of the ability of mobile to reach everyone who has a smart device and needs healthcare engagement.
To learn more about Care Thread, please visit http://www.carethread.com/.
To learn more about Nuance Dragon Medical One, please visit www.nuance.com/dragonmedicalone.
Publish Date: May 18, 2016 5:00 AM
Last month, we talked about the reasons millennial employees are more environmentally aware and tech-savvy than other generations in the workplace. We also discussed ways companies can put those strengths to good use in an effort to advance green workplace initiatives. Of course, millennials can help inspire and the lead the way, but to truly achieve a green workplace requires the participation and commitment of every employee.
In the second half of this two-part blog series, we reveal five easy, practical tips that millennials can implement in order to help create a greener workplace.
- Using mobile devices for display. Millennial employees (or anyone for that matter) should challenge themselves to minimize printing and instead, preview documents on a smartphone or tablet. Additionally, they can use digital editing tools to suggest changes, insert comments and generally collaborate. Changing these types of behaviors can help the organization reduce the amount of printed documents and its use of paper.
- Make the electronic version the first option. In another recent blog post, we talked about converting invoices to electronic documents for circulating through approval rather than paper bills. They may seem like small steps, but if employees can transform a paper process into an electronic one, they can have a positive impact on the workplace. Office memos, company newsletters, even employee reviews are all ripe for an electronic-first approach.
- Challenge the routine of “when in doubt, print it out.” How often have you printed an email because you wanted to keep a copy on file? Or are you guilty of printing documents as a reminder to complete tasks, review information, or take work home? By encouraging other employees to convert paper to an electronic document – just as easily as they could print one – millennials can challenge the routine of printing information for safekeeping.
- Route printed documents to the right recipient. Converting printed documents to electronic makes it far more likely that the intended recipient will receive the intended information. Millennials can start by taking advantage of these electronic workflows in your organization, and help prevent too much printing as information tries to make its way to the right person.
- Encourage other employees to propose green ideas. No one is more familiar with the processes that drive your company than your employees. Employees should encourage other workers to come up with other good ideas, and the organization should recognize them for these efforts. For example, why not reward them for converting previously paper processes to electronic? For example, an employee may propose that all agendas for team meetings now be shared as electronic PDFs. Or a manager may encourage his team to carry smartphones or tablets to meetings instead of notebooks. Ideas like these that come from employees are much more likely to be successfully adopted.
Support green initiatives
By implementing a reliable document management solution and mobile connectivity, you can provide employees with the foundation for a greener workplace and better productivity. Think of the savings that can result from reducing paper, toner cartridges, and other waste materials , not to mention the time saved from manual processes. Don’t let your company’s inability to move processes into a digital format be what holds them back.
Publish Date: May 18, 2016 5:00 AM
In my last blog post, I explained how we use different types of Neural Networks for both ASR and NLU. We already touched upon DNNS, RNN, and NeuroCRF, and I did not even mention that we use CNNs (Convolutional Neural Networks) for the “intent” discovery aspect of NLU. Does this sound confusing? Fortunately for end-users everywhere, you don’t have to worry about keeping all of the terminology and machine learning concepts straight – you just see the added benefits of increasingly accurate ASR and NLU.
Now, here is even better news: if you are a developer who wants to create a great app for the Internet of Things using speech technology (such as ASR and NLU), you no longer have to worry about the mechanics behind advanced concepts like machine learning. The reason is that we have done the heavy lifting for you. Through Nuance Mix, we are able to utilize our knowledge and expertise around neural networks of various types and how to apply them to specific tasks in order to create intuitive spoken interactions.
This new developer platform provides you with everything you need to quickly create, assess and refine your own speech application ideas. Perhaps most importantly, it gives you an easy to use interface for the setup and maintenance of your speech application’s ontology. What this really means is that you can determine what the app is to be used for, and provide your own sample utterances as the nucleus of training data. Once you’re past this stage, you can then apply the machine learning training machinery, with just the press of a button. Now that you have trained models unique to your app (which are basically the NNs we discussed earlier), you can deploy to a cloud based runtime environment and have your app up and running. Because you don’t have to be an expert in machine learning to use Mix, my colleague Kenn Harper called it “the democratization of voice technology” recently.
By taking a lot of the hard work out of integrating speech into your app, we allow you to focus your creativity on the app you want to create- an area in which you are the expert. And a creative approach is especially important now, as more and more devices enter the IoT sphere that can make sense of speech and natural language. To help spark that creativity, we are holding a series of “hackathons” and similar events, addressing both the needs of industrial users as well as enabling students to experiment and innovate with speech technology.
We recently partnered with DFKI (the German Research Center for Artificial Intelligence), which is located on campus at the University of Saarland, to host a hackathon of our own. Having been a proud stakeholder in DFKI since 2014, and understanding the way in which DFKI can bring AI into the German industry, we knew we would see some exciting projects. On the first day, we saw great participation by industrial partners who learned first-hand how to use mix from Mix Masters Nirvana Tikku and Samuel Dion-Girardeau. After a thorough workshop, the group gave it a try on their own, having the chance to test out our web-based developer platform.
The second portion of this event was a student hackathon, which my colleagues Christian Gollan and Hendrik Zender, DFKI alumni, have just returned from. Running from 5:00 PM Friday until 5:00 PM Saturday, the students engaged in a 24 hour coding spree to speech enable devices using Nuance Mix and SIAM-dp (DFKI’s own dialog platform). Having seen university students create some amazing championship winning inventions such as Lisa the robot, we had high expectations. We weren’t disappointed as every team involved came up with impressive solutions that would help address existing problems or areas of need by using speech, natural language and DFKI’s multimodal dialog platform.
Overall, the event resulted in a number of captivating applications that worked to simplify the interactions between people and technology. However, especially of note were our prize-winning teams. Our top winners were as follows: in third place a chatbot that could act as a personal assistant; in second place a speech-enabled robot that could help children learn how to do math; and, in first place, an intelligent home solution that enabled would-be houseguests to use a voicemail box for when no one is home. For the announcement of the winning teams and the award ceremony, we were joined by Professor Wolfgang Wahlster, CEO and Scientific Director of DFKI. He congratulated the students for their excellent results and emphasized the importance of speech interfaces and artificial intelligence for the ongoing transformation of how people will interact with the technology that surrounds them. He also stressed the pivotal role that the collaboration between DFKI and Nuance plays in this transformation.
We agree and think this event gave students with an interest in speech technology the opportunity to learn and work with cutting-edge tools in a fun, yet challenging environment. Besides winning prizes, eating pizza and drinking a lot of coffee, everybody involved exemplified the ways in which tools such as Nuance Mix and SIAM-dp could very well help build the intelligent, interactive solutions of our future.
Publish Date: May 17, 2016 5:00 AM
Customer experience is a prime differentiator for many organizations. Many products and services are becoming commoditized and today, the experience a company provides can set them apart. This was recently showcased in the Temkin report on Experience Ratings which highlighted companies and industries at the top and bottom of the customer experience spectrum and considered their performance based on three components: Success, Effort, and Emotion.
But this got me thinking: why should a company have to wait to see their customer experience ranking until a report is released? So I determined six call center metrics that really matter in judging the effectiveness of your own customer’s experience, so you can track how you’re performing on an ongoing basis.
When we call a company to resolve an issue we just want it fixed. That’s all we, as customers, care about: a successful resolution. The questions any organization needs to ask themselves then are:
- How well does a customer successfully solve their issues in our call center?
- How well do they navigate our IVR?
The ‘Success’ metrics that address these questions are ultimately the most critical areas of focus.
First Call Resolution (FCR): This is one of the most important metrics for any company. First call resolution (FCR) is how well your company takes care of the customer on their first attempt to resolve an issue. It’s calculated formulaically as number of calls resolved / all incoming calls.
Why it matters – FCR is important both as an indicator of external customer satisfaction but also an internal metric for effectiveness of your company’s processes and technology. Get this wrong and customers must call in multiple times – putting a strain on their patience and your systems.
Containment: This is a surprisingly straightforward measurement. All call center executives want to improve the ability of their IVR to accurately and effectively answer customer questions without having to reach a live agent. That is keep them within the IVR, i.e. containment. Containment is measured by the number of incoming calls resolved within the IVR as a percentage of total inbound calls. If the IVR is poorly designed and confusing, customers will not progress and instead “zero out” to a live agent. We’ve all been through that scenario.
Why it matters – Getting containment right keeps other metrics on track. Increasing the number of people who effectively self-serve increases their satisfaction and helps the company’s bottom line. Customers are happier, agents are happier due to decreased call volumes, and CFOs are happier due to decreased need for investments.
Nobody wants to spend a ton of time dealing with issues with their bank, insurance company, or TV provider. If this becomes necessary, we want to minimize how much time we put into it. Our effort must be low. And in fact, research shows the lower the effort, the greater the loyalty and satisfaction a customer will show to a company. Consumers like to be delighted with minimal effort and reduced friction on the way to problem resolution.
Misroutes: Put simply, misroutes occur when a company’s IVR sends a caller to the incorrect destination. When someone calls a customer service line and ends up someplace they didn’t intend, it’s usually the work of a misroute. Misroutes occur for a variety of reasons, including outdated technology that incorrectly recognizes speech or confusing phone menus that force annoyed customers to ask for a live person.
Why it matters – Misroutes directly increase the effort required to close a query. Each stop along the way creates more work and extends the call. Key metrics eroded by misroutes include average handle time, containment, first contact resolution, and more. Plus, misroutes dramatically increase costs and irritate customers, decreasing satisfaction and driving churn.
Average handle time: Some calls seem to take forever, going on and on with pushing buttons and repeating information. Looking at an aggregate view of all calls together allows a company to track the average handle time (AHT), or length of time a customer is on the phone. This is a very popular call center metric and is traditionally measured from the moment the customer calls to the time they hang up – including hold times.
Why it matters – In addition to wanting to lower handle times to improve the customer satisfaction, AHT is a prime factor when deciding call center staffing levels. Knowing the typical duration of a call allows companies to successfully model the number of agents they’ll need and how best to balance workloads during peak hours.
We live in a world driven by feelings. Consumers want “Likes” on their Facebook posts. They enjoy videos showing the good in people. They are quick to rave – or rant – on social media about how a company made them feel. Organizations that tap into these emotional needs positively will generate great interest in their brand.
Customer satisfaction: “Cust Sat”. NSAT. CSAT. The shorthand and acronyms vary and every company uses one or another. No matter which one is chosen, the two most important aspects are to 1) know that it’s the measure of the overall satisfaction of the interaction or service and 2) to get it right.
Why it matters – Customer satisfaction is the number one indicator of how well you are doing to satisfy your customers. It’s also a great way to gain insight into customers’ thoughts on the products you offer today as well as identify future direction for product development and feature updates. By keeping tabs on overall customer satisfaction, companies can make adjustments quickly to improve service levels, reduce wait time, or address frequent queries. Call centers are often the front line of issues and companies can get instant feedback as to how they are doing.
Net promoter score: If customer satisfaction is the number one indicator of IF your customer likes you, then Net Promoter Score (NPS) helps you understand just HOW much they like you. Customers may like your product or service after they get off the phone with you. But if they really liked it, they’ll pass it along to friends or post on social media. The Net Promoter Score essentially allows you to measure customer loyalty. It classifies customers into one of three categories:
- “Promoter” – customers are enthusiastic and loyal, continually buy from the company and ‘promote’ the company to their friends and family.
- “Passive” – customers are happy but can easily be tempted to leave by an attractive competitor deal. Passive customers may become promoters if you improve your product, service or customer experience.
- “Detractor” – customers are unhappy, feel mistreated and their experience is going to reduce the amount of which they purchase from you.
The Net Promoter Score is derived by subtracting the percentage of detractors from promoters to get an overall NPS result.
Why it matters – As you’d guess, the more detractors you have the lower your NPS and the increased likelihood that your service isn’t very good. Detractors are more likely to spread negative word of mouth and do so much faster than if they receive average or great service. A continually low NPS score will spell trouble and ultimately impact the brand. Companies that successfully track NPS and spark action from a high number of Promoters can improve customer loyalty and drive long term growth.
Understanding and effectively balancing the metrics based on Success, Effort, and Emotion will help you achieve your IVR goals.
Publish Date: May 17, 2016 5:00 AM