Virtual Assistant Update

 

We recently published “Virtual Assistant Update.” It’s a broad and not too deep update on virtual assistant technologies, products, suppliers, and markets from the perspective of the five leading suppliers: [24]7, Creative Virtual, IBM, Next IT, and Nuance. These are the leaders because they:

  • Have been in the virtual assistant business for some time (from 16 years for [24]7 via its acquisition of IntelliResponse to four years for IBM).
  • Have attractive and useful virtual assistant technology
  • Offer virtual assistant products that are widely used and well proven.
  • Want to be in the virtual assistant business and have company plans and product plans to continue.

The five suppliers are quite diverse. There’s the public $80 billion IBM and the public $2 billion Nuance. Then there are the private [24]7, a venture backed company big on acquisitions and the more closely held Creative Virtual and Next IT. Despite these big corporate-level differences, the five’s virtual assistant businesses are quite similar. Roughly they’re all about same size and the five compete as equals to acquire and retain virtual assistant business.

By the way, across the past 12 to 24 months, business has been good for all of the five suppliers. Customer growth has been very good across the board. Our suppliers have expanded into new markets and have introduced new and/or improved products.

Natural Language Processing and Machine Learning

Technologies are quite similar, too. All five have built their virtual assistant offerings with the same core technologies: Natural Language Processing (NLP) and machine learning.

Virtual Assistants use NLP to recognize intents of customer requests. NLP implementations usually comprise an engine that processes customer requests using an assortment of algorithms to parse and understand the words and phrases in a customer’s request. An NLP engine’s processing is guided by customizable and/or configurable deployment-specific mechanisms such as language models, grammars, and rules. These mechanisms accommodate the vocabularies of a deployment’s business, products, and customers.

Virtual assistants use machine learning technology to match actual customer requests with anticipated customer requests and then to select the content or execute the logic associated with the anticipated requests. (Machine learning algorithms learn from and then make predictions on data. Algorithms learn from training. Analysts/scientists train them with sample, example, or typical deployment-specific input then with feedback or supervision on correct and incorrect predictions. A trained algorithm is a deployment-specific machine learning model. The accuracy of models can improve with additional and continuing training. Some machine learning implementations are self-learning.)

Complex and Sophisticated Work: Consultant-led or Consultant-assisted

The work to adapt NLP and machine learning technology implementations for virtual assistant deployments is sophisticated and complex. This is work for experts: scientists, analysts, and developers in languages, data, and algorithms. The approach to this is work differentiates virtual assistant suppliers and products. The approach drives virtual assistant product selection. Here’s what we mean.

All the virtual assistant suppliers have built tools and package predefined resources to make the work simpler, faster, and more consistent. Some suppliers have built tools for the experts and these suppliers have also built consulting organizations with the expertise to use their tools. Successful deployments of their virtual assistant offerings are consultant-led. They require the services of the suppliers’ (or the suppliers’ partners’) consulting organizations.

Some suppliers have built tools that further abstract the work and make it possible for analysts, business users, and IT developers to deploy. While these suppliers have also built consulting organization with expertise in virtual assistant technologies and in their tools, successful deployments of their virtual assistant offerings are consultant-assisted and may even approach self-service.

So, a key factor in the selection of a virtual assistant product is deployment approach: consultant-led or consultant-assisted. Creative Virtual, Next IT, and Nuance offer consultant-led virtual assistant deployments. [24]7 and IBM offer consultant-assisted deployments. For example, IBM Watson Virtual Agent includes tools that make it easy to deploy virtual assistants. In the Figure below, we show the workspace wherein analysts specify the virtual assistant’s response to the customer request to make a payment. Note that the possible responses leverage content, tool, and facilities packaged with the product.

ibm watson va illos

© 2017 IBM Corporation

Illustration 7. This Illustration shows the Watson Virtual Agent workspace for specifying responses from the bot/virtual assistant.

 

Which is the better approach? Consultant-assisted is our preference, but we’ve learned over our long years of research and consulting that deployment approach is a function of corporate, style, personality, and culture. Some businesses and organizations give consultants the responsibility for initial and ongoing technology deployments. Some businesses want to do it themselves. For virtual assistant software, corporate style could very well be a key factor in product selection.

 

 

 

 

Microsoft Dynamics 365 for Customer Service

Serious Customer Service Capabilities

In our more than 10 years of customer service research, publishing, and consulting, we’d never before published a report about a Microsoft offering. It’s not because Microsoft hasn’t had a customer service offering or that the company hasn’t had success in business applications. Since 2003, its CRM suite has always included a customer service app. And, its Dynamics CRM brand has built a customer base of tens of thousands of accounts and millions of users. But, Dynamics CRM had always been more about its sales app and that app’s integration with Office and Outlook. Customer service capabilities have been a bit limited. No longer.

Beginning in November 2015, the improvements in two new releases—CRM 2016 and CRM 2016 Update 1—and, in November 2016, the introduction of the new Dynamics 365 brand have strengthened, even transformed, Microsoft’s customer service app and have made Microsoft a player to consider in the high end of the customer service space.

Our Product Evaluation Report on Microsoft Dynamics 365 for Customer Service, published December 1, 2016, will help that consideration. These are the new and/or significantly improved customer service components:

  • Knowledge management
  • Search
  • Customer service UI
  • Web self-service and communities
  • Social customer service

Let’s take a closer but brief look at each of them.

Knowledge Management

Knowledge Management is the name of a new customer service component. Introduced with CRM 2016, it’s a comprehensive knowledge management system with a rich and flexible knowledge model, a large set of useful knowledge management services, and an easy to learn and easy to use toolset. The best features of Knowledge Management are:

  • Visual tools of Interactive Service Hub, the customer service UI
  • Knowledge lifecycle and business processes that implement and support the lifecycle
  • Language support and translation
  • Version control
  • Roles for knowledge authors, owners, and managers

For example, Knowledge Management comes with a predefined but configurable knowledge lifecycle with Author, Review, Publish, and Expire phases. The screen shot in Figure 1 shows the steps in the Author phase.

ish-knowledge-author-stage-stepsFigure 1. This screen shot shows the steps in the Author phase of the knowledge management process.

Note that Knowledge Management is based on technology from Parature, a Reston, VA-based supplier with a customer service offering of the same name that Microsoft acquired in 2014. Beginning with the introduction of Dynamics 365, Microsoft no longer offers the Parature customer service product.

Search

Search is not a strength of Dynamics 365. Search sources are limited. Search query syntax is simple. There are few search analyses and few facilities for search results management. However, with the Dynamics 365 rebranding Microsoft has made improvements. Categorized Search, the new name of the search facility in Dynamics 365, retrieves database records with fields that begin with the words in search queries and lets administrators and seekers facet (Categorize) search results. The new Relevance Search adds relevance and stemming analyses. Microsoft still has work to do, but faceting, stemming, and relevance are a start to address limitations.

Customer Service UI – Interactive Service Hub

Interactive Service Hub (ISH) provides several useful and very attractive capabilities in Dynamics 365. It’s the UI for Knowledge Management, one of two UIs for case management, and a facility for creating and presenting dashboards. For the case management and knowledge management UIs, ISH provides visual tools that are easy to learn and easy to use. The tools let agents perform every case management task and let authors and editors perform every knowledge management function. For example, Figure 2 shows a screen shot of ISH’s presentation of an existing Case—the Name of the Case at the top left, the Case information to display “SUMMARY | DETAILS | CASE RELATIONSHIPS | SLA” under the Name, the phases of the deployment’s case management process “IDENTIFY QUALIFY RESEARCH RESOLVE” within a ribbon near the top of the screen, and the (SUMMARY) Case information in the center.

ish-existing-caseFigure 2. This screen shot shows the Interactive Service Hub display of an existing Case.

In addition to tools for building dashboards, ISH also packages useful predefined dashboards, two for case management and two for knowledge management. The four help customer service managers and agents and knowledge management authors and editors manage their work. Figure 3 shows an example of the My Knowledge Dashboard. It presents information useful to authors and editors very visually and interactively.

my-knowledge-dashboardFigure 3. This screen shot shows an example of the My Knowledge Dashboard.

Web Self-service and Communities

We were quite surprised to learn that, prior to the May 2016 introduction of CRM 2016 Update 1, Dynamics 365 for Customer Service and all of its predecessor products did not include facilities for building and deploying web self-service or communities sites. This limitation was addressed in Update 1 with the then named CRM Portal service, renamed the Portal service in Dynamics 365. Portal service is a template-based toolkit for developing (web development skills are required) and deploying browser-based web self-service and communities/forums sites. It’s based on technology from Adxstudio, which Microsoft acquired in September 2015 and it packages templates for a Customer Service Portal and a Community Portal. Note that Dynamics 365 for Customer Service licenses include one million page views per month for runtime usage of sites built on the Portal service (licenses may be extended with additional page views per month).

Social Customer Service

Microsoft Social Engagement is a separately packaged and separately priced social customer service offering that Microsoft introduced early in 2015. Social Engagement provides facilities that listen for social posts across a wide range of social sources (Instagram, Tumblr, WordPress, and YouTube as well as Facebook and Twitter), that analyze the content and sentiment of those posts, and that interact with social posters. In addition, Social Engagement integrates with Dynamics 365 for Customer Service. Through this integration, the automated or manual analysis of social posts can result in creating and managing customer service Cases. It’s a strong social customer service offering. What’s new is Microsoft bundles Social Engagement with Dynamics 365 for Customer Service. That’s a very big value add.

All This and More

We’ve discussed the most significant new and improved capabilities of Dynamics 365 for Customer Service. Knowledge Management, Interactive Service Hub, improved Search, the Portal service, and bundled Social Engagement certainly strengthen the offering. Although not quite as significant, Microsoft added and improved many other capabilities, too. For example, there are language support improvements, improvements to integration with external apps, new Customer Survey and “Voice of the Customer” feedback capabilities, and the use of Azure ML (Machine Learning) to suggest Knowledge Management Articles as Case resolutions automatically based on Case attribute values. Bottom line, Microsoft Dynamics 365 for Customer Service deserves serious consideration as the key customer service app for large businesses and public sector organizations, especially those that are already Microsoft shops.

IntelliResponse VA

Accurate Answers with Fast and Easy Deployment

We’ve just published our Product Review of IntelliResponse Virtual Agent (IntelliResponse VA), the virtual assisted-service offering from IntelliResponse Systems, Inc., a privately held supplier founded in 2000 and based in Toronto, ON Canada. The report completes our latest research series on virtual agents/virtual assisted-service.

We’ve published evaluations of the four leading virtual agent offerings:

  • Creative Virtual V-Person
  • IntelliResponse VA
  • Next IT Active Agent
  • Nuance Nina Web (VirtuOz Intelligent Virtual Agent when we published. Nuance acquired VirtuOz earlier this year.)

Virtual agents implemented on all four can deliver a single answer to a customer’s question on web, mobile, and social channels. Expect the answer to be correct about 90 percent of the time.

Virtual agents deliver bottom line benefits. They can lower cost to serve as compared to live agents and they can improve customer sat by improving the speed, accuracy, and consistency of the answers to customers’ questions.

 Contrast virtual agents with search and knowledgebase approaches that deliver many answers and leave it to the customer to pick the correct one. This single correct answer makes virtual agents useful for answering many kinds of customers’ questions, certainly customer service questions but also questions about your business and about your business policies, processes, and practices, about your products, and everything about your customers’ relationships with you—accounts, orders, bills, and passwords, for example. They can be your agents for marketing, for sales, and for service.

 Like your live agents, it takes time and effort to get virtual agents ready to engage with your customers. You have to give them the knowledge about the business areas that they support. You have to train them to understand your customers’ questions and to correlate or match those questions with the correct answers. The knowledge is contained in/represented by the items in their knowledgebases, their store of predefined answers. Anticipate the questions that your customers will ask, specify the answers, and store them in the virtual agent’s knowledgebase. All four virtual agent products have knowledgebases and provide tools and facilities for creating and managing answers. Your customers’ questions will change and evolve with their relationships and with changes to your offerings of products and services and to your business. Virtual agent’s knowledge has to keep up with those changes (just like live agents’ knowledge).

Training virtual agents to understand your customers’ questions and to correlate/match them to correct answers is the harder part. Virtual agents use very sophisticated and complex technology to analyze customers’ questions and to match them with the answers in their knowledgebases. Analysis and matching is the core processing that virtual agents perform. Analysis and matching technology is the virtual agent supplier’s core IP, its secret sauce. Each of the four has patented some or all of this technology. The suppliers want you to appreciate the sophistication and power of the technology. They don’t give you much detail of what it does or how it works.

(We describe and evaluate how a virtual agent analyzes and matches questions in our product review. We actually read many of the suppliers’ patents to help us understand the technology. In our reports, we describe it a bit, but we focus on what you’ll have to do to use it effectively.)

Creative Virtual V-Person, Next IT Active Agent, and Nuance Nina Web use Natural Language Processing (NLP) technology for their analysis and matching. Each has its own NLP implementation. NLPs perform computational linguistic analyses on customers’ questions, parsing for subjects, verbs, object, and qualifiers, extracting entities, identifying actors and roles, and codifying relationships. This is sophisticated and complex processing.

For a successful virtual agent deployment, you provide critical input to your virtual agent supplier’s NLPs, for example:

  • Words that your customers will likely include in their questions
  • Misspellings, typos, slang, idioms, ad stems for those words
  • Conditions/rules/expressions for how your customers combine words into phrases
  • Parameters for configuring the NLP processing

If you don’t specify the actual words and their various alternative forms that your customers use in their questions, then your virtual agent cannot deliver answers. Complete specification of your customers’ vocabularies is critical. Virtual agent products help considerably with packaged dictionaries of common industry and application terms, but it’s on you to provide the vocabulary specific to your business and your products.

Virtual agent suppliers also provide consulting services to help the NLP specification. These services are essential for a successful virtual agent deployment. These services are also essential for ongoing management of your virtual agent. Remember that customers’ questions are always changing. So is your business.

IntelliResponse VA uses machine learning technology for its analysis and matching. Machine learning is an algorithmic approach. The algorithm learns by training it with sample data in a controlled environment. It applies its learning when it goes live. The sample data that you provide to train an IntelliResponse VA virtual agent are the typical questions that you want it to answer, not the words and phrases in those questions, not various forms of those words, not the relationships between them, just the questions. IntelliResponse VA can do the rest of the work, even to accommodate the ongoing changes in customers’ questions and in your business. IntelliResponse VA virtual agent deployment is easier and faster than NLP-based deployments and delivers answers with the same level of accuracy. Read our report for the details and note that IntelliResponse can also provide those consulting services to help you deploy and manage virtual agents. The details of the work will be a bit different and there will be less work to do, but the objective will be the same—deploying virtual agents that answer customers’ questions.