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.

 

 

 

 

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Nuance Nina Virtual Assistants

We evaluated Nina, the virtual assistant offering from Nuance, for the third time, publishing our Product Evaluation Report on October 29, 2015. This Report covers both Nina Mobile and Nina Web.

Briefly, by way of background, Nina Mobile provides virtual assisted-service on mobile devices. Customers ask questions or request actions of Nina Mobile’s virtual assistants questions by speaking or typing them. Nina Mobile’s virtual assistants deliver answers in text. Nina Mobile was introduced in 2012. We estimate that approximately 15 Nina Mobile-based virtual assistants have been deployed in customer accounts.

Nina Web provides virtual assisted-service through web browsers on PCs and on mobile devices. Customers ask questions or requests actions of Nina Web’s virtual assistants questions by typing them into text boxes. Nina Web’s virtual assistants deliver answers or perform actions in text and/or in speech. Nina Web was introduced as VirtuOz Intelligent Virtual Agent in 2004. Nuance acquired VirtuOz in 2013. We estimate that approximately 35 Nina Web-based virtual assistants have been deployed in customer accounts.

The two products now have common technologies, tools, and a development and deployment platform. That’s a big deal. They had been separate and pretty much independent products, sharing little more than a brand. Nuance’s development team has been busy and productive. Nina also has many new and improved capabilities. Most significant are a new and additional toolset that supports key tasks in initial deployment and ongoing management, PCI (Payment Card Industry) certification, which means that Nina virtual assistants can perform ecommerce tasks for customers, support for additional languages, and packaged integrations with chat applications.

Nina Evaluation Process

We did not include an evaluation of Nina’s Ease of Evaluation. Our work on the Nina Product Evaluation Report was well underway before we added that criterion to our framework. So, we’ll offer that evaluation here.

For our evaluation, we used:

  • Product documentation, which was provided to us by Nuance under an NDA
  • Demonstrations, especially of new tools and functionality, conducted by Nuance product management staff
  • Web content of nuance.com
  • Online content of Nina deployments
  • Nuance’s SEC filings
  • Discussions with Nuance product management and product marketing staff
  • Thorough (and very much appreciated) review of report draft

We also leveraged our knowledge of Nina, knowledge that we acquired in our research for two previously published Product Evaluation Reports from July 2012 and January 2014. We know the product, the underlying technology, and the supplier. So we were able to focus our research on what was new and improved.

Product Documentation

Product documentation, the end user/admin manuals for Nina IQ Studio (NIQS) and the new Nuance Experience Studio (NES) toolsets, was they key source for our research. We found the manuals to be well written and reasonably easy to understand. Samples and examples illustrated simple use cases and supported descriptions very well. Showing more complex use cases, especially for customer/virtual assistant dialogs, would have been very helpful. Personalization facilities could be explained more thoroughly. Also, there’s a bit of inconsistency in terminology between the two toolsets and their documentation.

Nina Deployments

Online content of Nina deployments helped our research significantly. Within the report, we showed two examples of businesses that have licensed and deployed Nina Web are up2drive.com, the online auto loan site for BMW Financial Services NA, LLC and the Swedish language site for Swedbank, Sweden’s largest savings bank. The up2drive Assist box accesses the site’s Nina Web virtual assistant. We asked, “How to I qualify for the lowest rate new car rate?” See the Illustration just below.

up2drive

Online content of Nina Mobile deployments show how virtual assistants can perform actions for customers. For example, we showed how Dom, the Nina Mobile virtual assistant, could help you order pizza from Domino’s in our blog post of May 14, 2015. See https://www.youtube.com/watch?v=noVzvBG0GD0.

Take care when using virtual assistant deployments for evaluation and selection. They’re only as good as the deploying organization wants to make them. Their limitations are almost never the limitations of the virtual assistant software. Every virtual assistant software product that we’ve evaluated has the facilities to implement and deliver excellent customer service experience. Virtual assistant deployments, like all customer experience deployments, are limited by the deploying organization’s investment in them. The level of investment controls which questions they can answer, which actions they can perform, how well they can deal with vague or ambiguous questions and action requests, and their support for dialogs/conversations, personalization, and transactions.

No Trial/Test Drive

Note that Nuance did not provide us with a product trial/test drive of Nina. In fact, Nuance does not offer Nina trials/test drives to anyone. That’s typical of and common for virtual assistant software. Suppliers want easy and fast self-service trials that lead prospects to license their offerings. Virtual assistant software trials are not any of these things. They’re not designed for self-service deployment either for free or for fee.

Why not? Because virtual assistant software is complex. Even its simplest deployment requires building a knowledgebase of the answers to the typical and expected questions that customers ask, using virtual assistant facilities to deal with vague and ambiguous questions, engaging in a dialog/conversation, escalating to chat, or presenting a “no results found” message, for example, and using virtual assistant facilities to perform actions that customers request and deciding how to perform them. (Performing actions will likely require integration apps external to virtual assistant apps.) This is not the stuff of self-service trials and test-drives.

In addition, most virtual assistant suppliers have not yet invested in building tools that speed and simplify the work that organizations must perform for the initial deployment and ongoing management of virtual assistants software even after it has been licensed. Rather, suppliers offer their consulting services instead. (That’s changing for Nuance with toolsets like NES and for several other virtual assistant software suppliers and that’s certainly a topic for a later time.)

Thank You Very Much, Nuance

One more point about Ease of Evaluation. Our research goes into the details of customer service software. We publish in-depth Product Evaluation Reports. We demand a significant commitment from suppliers to support our work. Nuance certainly made that commitment and made Nina Easy to Evaluate for us. We so appreciate Nuance’s support and the time and effort taken by its staff.

Nina was very easy for us to evaluate. The product earns a grade of Exceeds Requirements in Ease of Evaluation.

Voices of Customers

With this week’s report, the 4Q2013 Customer Service Update, we complete our tenth year of quarterly updates on the leading suppliers and products in customer service. These updates have focused on the factors that are important in the evaluation, comparison, and selection of customer service products.

  • Customer Growth
  • Financial Performance
  • Product Activity
  • Company Activity

Taking from the framework of our reports, for Company Activity, we cover company related announcements, press releases, and occurrences that are important to our analysis of quarterly performance. In 4Q2013, three of our suppliers, Creative Virtual, KANA, and Nuance, published the results of surveys that they had conducted or sponsored over the previous several months. All of the surveys were about customer service and the answers to survey questions demonstrated customers’ approach, behavior, preferences, and issues in their attempts to get service from the companies with which they’ve chosen to do business. The responses to these surveys are the Voices of the Customers for and about customer service. This is wonderful stuff.

Now, to be sure, suppliers conduct surveys for market research and marketing purposes. Suppliers’ objectives for surveys are using the Voice of the Customer to prove/ disprove, validate, demonstrate, or even promote their products, services, or programs. Certainly, all of the surveys our suppliers published achieved those objectives. For this post, though, let’s focus on the broader value of the surveys, the Voice of the Customer for Customer Service.

Surveys

The objectives in many of the survey represent the activities that customers perform, the steps that customers follow to get customer service from the companies with which they choose to do business. By getting customer service, we mean getting answers to their questions and (re)solutions to their problems. Ordering our examination and analysis of the surveys in customers’ typical sequence of these steps organizes them into a Customer Scenario. Remember that a Customer Scenario is the sequence of activities that customers follow to accomplish an objective that they want to or need to perform. For a customer service Customer Scenario, customers typically:

  • Access Customer Service. Customer login to their accounts or to the customer service section of their companies’ web sites, or call their companies’ contact center and get authenticated to speak with customer service agents
  • Find Answers and (Re)solutions. Use self-service, social-service, virtual-assisted service, and/or assisted-service facilities to try to help themselves, seek the help of their peers, seek the help of customer service agent for answers and (re)solutions.
  • Complain. If customers cannot get answers or (re)solutions using these facilities, they complain to their companies.

Here, in Table 1, below, are the surveys that examine how customers perform these activities and how companies support those activities. Note that these surveys are a subset of those surveys that were published by our suppliers. Not all of their surveys mapped directly to customer activities. Note that our analyses of survey results are based on the content of the press releases of the surveys. This content is a bit removed from the actual survey data.

Sponsor Survey Objective Activity Respondents
Nuance Privacy and security of telephone credentials Access Smartphone users
Nuance Telephone authentication issues and preferences Access US consumers
KANA Email response times for customer service Find answers and (re)solutions N/A
KANA Twitter response times for customer service Find answers and (re)solutions N/A
Nuance Resolving problems using web self-service Find answers and (re)solutions Web self-service users, 18–45 years old
Nuance Issues with Web self-service Find answers and (re)solutions Windstream Communications customers
KANA Usage of email vs. telephone for complaints Complain N/A
KANA Customer communication channels for complaints Complain UK consumers
KANA Customer complaints Complain US consumers, 18 years old and older

Table 1. We list and describe customer service surveys published by KANA and Nuance during 4Q2013 in this Table.

Let’s listen closely to the Voices of the Customers as they perform the activities of the customer service Customer Scenario. For each of the surveys in the Table, we’ll present the published survey results, analyze them, and suggest what businesses might do to help customers perform the activities faster, more effectively, and more efficiently.

Access

If questions and problems are related to their accounts, before customers can ask questions or present problems, they have to be authenticated on the customer service system that handles and manages questions and problems. Authentication requires usernames and passwords, login credentials. In these times of rampant identity theft, security of credentials has become critically important.

Nuance’s surveys on privacy and security of telephone credentials and on telephone authentication shed some light on customers’ issues with authentication.

  • 83 percent of respondents are concerned or very concerned about the misuse of their personal information.
  • 85 percent of respondents are dissatisfied with current telephone authentication methods.
  • 49 percent of respondents stated that current telephone authentication processes are too time consuming.
  • 67 percent of respondent have more than eleven usernames and passwords
  • 80 percent respondents use the same login credentials across all of their accounts
  • 67 percent of respondents reset their login credentials between one and five times per month.

Yikes! Consumers spend so much time and effort managing and, then, using their credentials. We’ve all experienced the latest account registration pages that grade our new or reset passwords from “weak” to “strong” and reject our weakest passwords. While strong passwords improve the security of our personal data, they’re hard to remember and they increase the time we spend in their management.

In voice biometrics, Nuance offers the technology to address many of these issues. On voice devices, after a bit of training, customers simply say, “My voice is my password,” to authenticate account access based on voiceprints and  voiceprints are unique to an individual.

Find Answers and (Re)solutions

KANA’s surveys on email response times for customer service and Twitter response times for customer service examine response times for “inquiries.” When customers make inquiries, they’re looking for answers or (re)solutions. In the surveys, KANA found:

  • According to Call Centre Association members, response times to email inquiries was greater than eight hours for 59 percent of respondents and greater than 24 hours for 27 percent of respondents.
  • According to a survey by Simply Measured, a social analytics company, the average response times to Twitter inquiries were 5.1 hours and were less than one hour for 10 percent of respondents.

While it’s dangerous to make cross-survey analyses, it seems reasonable to conclude that customer service is better on Twitter than on email. That’s not surprising. Companies have become very sensitive to the public shaming by dissatisfied customers on Twitter. They’ll allocate extra resources to monitoring social channels to prevent the shame. Customers win.

However, remember that these are independent surveys. The companies that deliver excellent customer service on Twitter might also deliver excellent customer service on email and the companies that deliver not so excellent customer service on email might also deliver not so excellent customer service on Twitter. The surveys were not designed to gather this data. That’s the danger of cross-survey analysis.

If your customers make inquiries on both email and social channels, then you should deliver excellent customer service on both. Email management systems and social listening, analysis, and interaction systems, both widely used and well proven customer service applications, can help. These are systems that should be in every business’s customer service application portfolio.

Email management systems help business manage inquiries that customer make via email. These systems have been around for way more than ten years, helping businesses respond to customers’ email inquiries. Businesses configure them to respond to common and simple questions and problems automatically and to assign stickier questions and problems to customer service staff. Business policies are the critical factor to determine response times to customers’ email inquiries.

Social listening, analysis, and interaction systems have been around for about five years. They help businesses filter the noise of the social web to identify Tweets and posts that contain questions and problems and the customers who Tweet and post them. These systems then include facilities to interact with Tweeters and posters or to send the Tweets and posts to contact center apps for that interaction.

Find Answers and (Re)solutions Using Web Self-Service

Nuance’s surveys about web self-service really show the struggles of customers trying to help themselves to answers and (re)solutions.

In the survey about consumers’ experiences with web self-service, the key findings were:

  • 58 percent of consumers do not resolve their issues
  • 71 percent of consumers who do not resolve their issues spend more than 30 minutes trying
  • 63 percent of consumers who do resolve issues, spend more than 10 minutes trying

In Nuance’s survey of Windstream Communications’ customers about issues with web self-service, the key finding were:

  • 50 percent of customers who did not resolve their issues, escalated to a live agent
  • 71 percent of customers prefer a virtual assistant over static web self-service facilities

The most surprising and telling finding of these surveys was the time and effort that customers expend trying to find answers and (re)solutions using web self-service facilities. 30 minutes not to find an answer or a solution seems like a very long time. Customers really want to help themselves.

By the way, Windstream’s customers’ preference for a virtual assistant is not a surprise. Windstream Communications, a Little Rock, AK networking, cloud-computing, and managed services provider, has deployed Nina Web, Nuance’s virtual agent offering for the web. Wendy, Windstream’s virtual agent, uses Nina Web’s technology to help answer customers’ questions and solve their problems. The finding is a proof point for the value of virtual agents in delivering customer service. Companies in financial services, healthcare, and travel as well as in telecommunications have improved their customer services experiences with virtual agents. We cover the leading virtual agent suppliers—Creative Virtual, IntelliResponse, Next IT, and Nuance—in depth. Check out our Product Evaluation Reports to find the virtual agent technology best for your business.

Complain

Customers complain when they can’t get answers to their questions and (re)solutions to their problems. KANA’s surveys about complaints teach so much about customer’s behavior, preferences, and experiences.

  • In KANA’s survey on usage of email or telephone channels for complaints, 42 percent of survey respondents most frequently use email for complaints and 36 percent use the telephone for complaints.
  • In KANA’s survey of UK consumers on communications channels for complaints, 25 percent of UK adults used multiple channels to make complaints. Fifteen percent of their complaints were made face-to-face.

The surprising finding in these surveys is the high percentage of UK consumers willing to take the time and make the effort to make complaints face-to-face. These customers had to have had very significant issues and these customers were very serious about getting those issues resolved.

The key results in KANA’s survey about customer complaints by US consumers were:

  • On average, US consumers spend 384 minutes (6.4 hours) per year lodging complaints
  • In the most recent three years, 71 percent of US consumers have made a complaint. On average, they make complaints six times per year and spend one hour and four minutes resolving each complaint.
  • Thirty nine percent of US consumers use the telephone channel to register their complaints. Thirty three percent use email. Seven percent use social media.
  • Millenials complained most frequently—80 percent of 25 to 34 year old respondents. Millenials are also most likely to complain on multiple channels—39 percent of them.
  • Survey respondents had to restate their complaints (Retell their stories) 69 percent of the time as the responsibility to handle their complaints was reassigned. On average, consumers retold their stories three times before their issues were resolved and 27 percent of consumers used multiple channels for the retelling.

The surprising findings in this survey are the time, volume, and frequency of complaints. Six and a half hours a year complaining? Six complaints every year? Yikes!

No surprise about the low usage of social channels to register complaints. Customers want to bring our complaints directly to their sources. They may vent on the social web, but they bring their complaints directly to their sources, the companies that can resolve them.

Lastly and most significantly, it’s just so depressing to learn that businesses are still making customers retell their stories as their complaints cross channels and/or get reassigned or escalated. We’ve been hearing this issue from customers for more than 20 years. Customers hate it.

Come on businesses. All the apps in your customer service portfolios package the facilities you need to eliminate this issue—transcripts of customers’ activities in self-service apps on the web and on mobile devices, threads of social posts, transcripts of customers’ conversations with virtual agents, and, most significantly, case notes. Use these facilities. You’ll shorten the time to solve problems and resolve customers’ complaints. Your customers will spend less time trying to get answers and (re)solutions (and more time using your products and services or buying new ones).

4Q2013 Was a Good Quarter for Customer Service

By the way, Customer Service had a good quarter in 4Q2013. Customer growth was up. Financial performance was up as a result. Product activity was very heavy. Nine of our ten suppliers made product announcements. Company activity was light. Five suppliers did not make any company announcements. Most significantly, KANA was acquired by Verint. And of course, three suppliers published customer service surveys.

Nuance Nina Web

Flexible and Accurate Answers to Customers’ Questions

We published our Product Evaluation Report on Nina Web from Nuance Communications this week. Nina Web is virtual assisted-service software for web browsers on desktops, laptops, and mobile devices. Type a question in a text box and a Nina Web-based virtual agent will deliver an answer or will engage you in a dialog when it needs more information to answer your question. Answers are text, images, links, URLs, and/or data from external applications.

Nina Web was originally developed as VirtuOz Intelligent Virtual Agent by VirtuOz, Inc., a privately held firm founded in France in 2002. Nuance acquired VirtuOz in March 2013. Nina Web became the third member of the Nina family of customer self-service offerings from Nuance’s Enterprise division, joining Nina IVR and Nina Mobile.

Nuance has made and continues to make significant improvements to the VirtuOz IVA. A bit less than a year after the acquisition, Nina Web is stronger and more attractive virtual agent offering, earning good grades on our Report Card for Virtual Assisted-Service. (See the Product Evaluation report for the details.)

Most significantly, Nuance’s Enterprise division developers have just about completed what they call a “brain transplant” for Nina Web, replacing the question analysis and matching technology built by VirtuOz with Nuance’s Natural Language Understanding (NLU) technology, the same technology used by Nina IVR and Nina Mobile. NLU combines Natural Language Processing (NLP) with statistical machine learning. NLP does some parsing and linguistic analysis of customers’ questions. Statistical machine learning, which Nuance implements in neural networks, matches customers’ questions with typical and expected “User Questions” and variations of User Questions that analysts create and store in Nina Web’s knowledgebase. Analysts also create knowledgebase answers and associate an answer with each User Question. When NLU matches a customer’s question with a User Question, Nina Web presents the answer associated with the User Question to the customer.

Analysts “train” NLU’s machine learning algorithms with User Questions and their variations. Nina Web provides the facilities and tools for initial training and ongoing refinement/retraining. Analysts add, delete, and modify User Questions as the intent and the vocabulary of customers’ questions changes to ensure that their Nina Web virtual agent delivers accurate answers. They must refine answers, too.

As you might infer by our description, NLU is a black box. Train it with a set of User Questions and it will match customer’s questions with them. The critical tasks for a Nina Web deployment are the initial specification and continuing refinement of User Questions and of answers. Nina Web insulates deployment work from NLU, from the complexity of NLP and statistical machine learning. Analysts do not specify language models or matching rules. They do not (and cannot) configure and/or customize neural network processing. Knowledge management is the focus deployment efforts. That can make for easier and faster deployment, a strength and differentiator for Nina Web.

One more thing. We mentioned that NLU is the analysis and matching technology in Nina IVR and Nina Mobile as well as in Nina Web. One set of User Questions can match customer questions with one set of answers across telephone, web, and mobile channels. Together, Nina IVR, Nina Mobile, and Nina Web can deliver a consistent cross-channel customer self-service experience, but, today, that consistency requires creating and managing three copies of the set of User Questions and three copies of the set of answers because the products are not integrated. Each Nina deploys independently of the others. But, cross-Nina integration is on Nuance’s product roadmap. An integrated, cross-channel Nina will be quite a customer service offering.

A Good Quarter for Customer Service in 3Q2013

This week, continuing our tenth year of quarterly updates on the suppliers and products in customer service, we published our 3Q2013 Customer Service Update Report. Just a reminder, these reports examine customer service suppliers and their products along the dimensions of customer growth, financial performance, product activity, and company activity. We currently cover ten leading customer service suppliers. They lead in overall market influence and share, in market segment influence and share, and/or in product technology and innovation.

3Q2013 was a good quarter for customer service. Customer growth was up and improved customer growth resulted in improved financial performance. Product activity was light. Six of our suppliers did not make any product announcements, but remember that third quarters are summer quarters. They’re usually never big for products. Company activity was also on the light side but what company action we saw was highlighted by expansion into new markets by four of our suppliers. That’s a key customer service trend and a solid indicator of customer service growth in the quarters ahead. Here’s a bit more detail:

  • On July 17, IntelliResponse and BolderView, a Melbourne, AU-based consultancy specializing in virtual agent solutions for large enterprises in utilities, banking, technology, higher education and government markets, jointly announced that BolderView had become a value-added reseller of IntelliResponse VA for Australia and New Zealand. Within the release, IntelliResponse also announced the opening of its own office in Sydney, AU.
  • On September 5, KANA and Wipro jointly announced a partnership that will apply Wipro’s consulting, systems integration, and insurance industry expertise and experience to accelerate deployments of KANA Enterprise for large global insurers and financial services providers. The companies will form a dedicated, joint deployment team to work on customer deployments.
  • On September 17, Clarabridge announced the expansion of its global operations into Latin America. A sales team will use Miami, FL offices and will leverage Clarabridge’s partnerships with Accenture, Deloitte, and Salesforce.com initially to focus on opportunities in Argentina, Brazil, Chile, Colombia, Mexico, and Peru.
  • On September 25, Moxie announced the expansion of its operations in Europe. The expansion includes opening an office in Reading, UK, forming partner ships with Spitze & Company in Denmark and IZO in Spain, and appointing Andrew Mennie General Manager for EMEA.

This expansion is a win for customer service suppliers, a win for their customers, and a win for their customers’ customers.

It’s already winning for customer service suppliers. For example, Moxie claims to have doubled its European customer base in the last six months. New customers include Allied Irish Bank and the British Army. IntelliResponse and BolderView recently launched “Olivia,” their first joint virtual agent deployment. Olivia is the virtual agent for Optus, Australia’s second largest telecommunications provider. And, Creative Virtual, a UK-based virtual agent software supplier that we’ve been covering in our quarterly reports for the past four quarters, recently announced Sabine, the Dutch-speaking virtual agent for NIBC Direct, the online retail unit of The Hague, NE-based bank. Sabine’s deployment is supported from Creative Virtual’s new Amsterdam office. See Sabine at the bottom right of NIBC Direct’s home page, below.

nibc png

Expansion demonstrates the strength and viability of customer service suppliers. Their products have reached the level of maturity and reliability that their deployment “far from home” carries little or no risk. They have the resources to open offices and hire the staff to promote, sell, and support their products in new markets. And they recognize the potential for new and additional business in those markets.

Our suppliers’ customers and their (end) customers in Australia and New Zealand, Latin America, and Europe benefit, too. Customer service applications like Clarabridge Analyze, a CEM (Customer Experience Management) app, Creative Virtual V-Person and IntelliResponse VA (Virtual Agent) virtual agents apps, and Moxie Social Knowledgebase, a social customer service app have been proven to lower cost to serve and to improve customer experiences. Companies in expanded markets that deploy these apps will have more satisfied, more profitable customers. These apps will help answer customers’ questions and solve customers’ problems more quickly and more easily.

We’ve been ready for this expansion. Language support has long been a criterion in our frameworks for evaluating customer service applications. We examine the languages that the apps support for internal users and the globalization/localization facilities to deploy the apps to end customers. Generally, we’ve found that most customer service apps can be localized to support locale-specific deployments. On the other hand, the tools and reporting capabilities for internal users tend to be implemented and supported only in English.