(2018 Edition)
In its installment, Opus Research provides a comprehensive buying guide detailing 2 solution providers for enterprise intelligent assistants. | » | Report »
(2018 Edition) In its installment, Opus Research provides a comprehensive buying guide detailing 2 solution providers for enterprise intelligent assistants. »
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Published June 2018 © Opus Research, Inc. All rights reserved.
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» Table of Contents
The Urgency for Brands to Choose an Intelligent Assistance Platform ...... 4 Key Trends and Findings: ...... 5 A Groundswell of Organic Demand ...... 7 A Parallel World of Conversational Marketing...... 8 The Conversational Commerce Genome ...... 8 Moving Toward an Open, End-to-End Platform ...... 9 Enterprises Have Had to Adapt Quickly ...... 11
Table of Tables Figure 1: Forecast Spending on EIA (in $millions) ...... 5 Figure 2: Smart Speaker Proliferation ...... 7 Figure 3: Conversational Commerce Technology Landscape...... 9 Figure 4: The Ultimate AI Platform ...... 9 Figure 5: Moving Along the IA Maturity Curve ...... 10 Figure 6: EIA Companies Under Review ...... 11 Figure 7: EIA Solution Provider Comparisons...... 13 Figure 8: Evaluation Criteria Descriptions ...... 16
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Introduction: Current State of Enterprise Intelligent Assistants
In this report, Opus Research presents a comprehensive assessment of the current Intelligent Assistant (IA) solution provider landscape with special focus on those offering “enterprise-grade” solutions.
Enterprise-based, NLP-powered self-service solutions, also known as “Intelligent Assistants” (IAs), have gained traction and proven their value over the past ten years. To support competitive differentiation and omnichannel strategies, the age of Intelligent Assistance is being thrust upon Marketing, Customer Care and Digital Commerce executives around the world and across multiple industries; it is no longer a matter of “if” but “when.”
The Urgency for Brands to Choose an Intelligent Assistance Platform For marketing, advertising and support executives, implementing an intelligent assistance strategy has become an imperative. Tens of millions of their prospects and customers have grown accustomed to conversing with their selected brands in much the same way that they correspond with friends, acquaintances or colleagues; that is, conversationally, through mobile apps, messaging platforms, social networks or over the phone.
The proliferation of “smart speakers” and other intelligent endpoints adds to the urgency. Mid-2018 found such devices in over one-half of homes in the U.S. and, as Amazon and Google vie for “voice-frst” supremacy, they are making the investment necessary both to attract, train and compensate application developers and to promote frequent and repeated use across multiple generations of users.
In response, enterprises have stepped up spending and implementation plans for Intelligent Assistants as part of their “Digital Transformation” strategies as well as investments in what is broadly called “Conversational AI.” The impact of this virtuous cycle is refected in the results of Opus Research’s census of Enterprise Intelligent Assistants, as well as forecasted spending for licenses, professional services and cloud-based services that fuel their flavor of IA. Once again Opus Research has compiled information on a community of solution or platform providers in order to provide enterprise decisionmakers with criteria to apply when evaluating options and choosing solution providers.
In spite of confusion created by a cacophony of competing bot technologies, the market for Enterprise Intelligent Assistants is impressively robust. Based on information provided by respondents, the number of companies offering some favor of chatbot, virtual agent or intelligent assistant has grown to 2,100 from the 1,200 reported in our last survey, representing a 75% growth rate. At the same time, the number of claimed implementations approaches 40,000. As illustrated in Figure 1 , enterprise spending on IA has kept pace with spending in excess of $1.2 billion in 2017 on its way to $5.5+ billion in 2021.
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Figure 1: Forecast Spending on EIA (in millions )
$6,000
$5,000
$4,000
$3,000
$2,000
$1,000
$0 2016 2017 2018 2019 2020 2021
Source: Opus Research 2018)
Key Trends and Findings:
Smart speakers sparked preference for Conversational User Interfaces: Already in tens of millions of homes, Amazon Echo devices and other “smart speakers” have precipitated a rush by recognized brands to build services or “skills” that support conversations between them and their prospects or customers.
Bot platforms are the beneficiaries: At the same time, we’ve witnessed a population explosion among messaging bots, and other flavors of chatbots to provide continuous access to intelligent assistants through text-based channels.
Enterprise have long-standing experience in IA: Enterprises may feel like the “Botsplosion” has left them behind, but many have found that their investments in speech-enabled IVRs and Web-based chatbots has created raw material that can be ingested and integrated into Intelligent Assistant platforms and services.
T vendors generated $1.2 billion in spending in 2017: We are well past proof-of-concepts and controlled implementations; meaning that first-order challenges surround providing correct answers or actions consistently and at large scale.
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Vendors differentiate by tackling tough challenges: The latest RFIs and RFPs for Intelligent Assistants reflect levels of sophistication that have not been seen before. Enterprises judge by “what works out of the box,” “how well systems ‘learn’ (i.e. recognize new categories and intents), “how well it support multiple devices and channels”, “what tools and roles are assigned to departmental employees,” and “what standard connectors integrate with existing Contact Center, telecommunications, CRM, ERP and IT Systems.
Sympathy, empathy and emotion recognition come next: As solutions mature, bots become less “bot- like” and another area of differentiation for core platform vendors involve the ability to recognize who an individual is and his or her emotional state to inform the dialogue.
Enterprises are Where the Action is for Intelligent Assistance Developer admiration for Amazon and fawning over Facebook nearly obscures the fact that leading brands and large enterprises around the world have a long history of supporting Conversational Commerce. Banks, brokerage houses, hotel chains, airlines, communications carriers and others have over a decade of experience in the field. With the help of the companies described in this document, they procured and put into service platforms that support Intelligent Assistants through Web sites and voice channels has swelled from 1,200+ in 2016 to 2,000+ today. That 80% bump represents a huge vote of confidence.
Meanwhile, Opus Research forecasts that enterprise spending on the licenses and professional services that support Intelligent Assistance will exceed a projected $2 billion in 2018, heading for $5.5 billion by 2021, a 67% CAGR for the next five years.
It represents a perfect storm where technological advancements in Speech Processing, Natural Language Understanding, Machine Learning and Knowledge Management coincides with (or gives rise to) heightened comfort levels of comfort and confdence in human-to-machine communications. It has redefned self-service and customer support and is poised to redefne advertising technologies (AdTech), as well as marketing technology (MarTech) by replacing highly imprecise targeting of ads, email and online content, with user-initiated conversations.
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A Groundswell of Organic Demand Global conversion to conversational user interfaces is accelerating, and it is happening at an unprecedented pace. Evidence is everywhere. In homes, one need look at how quickly so-called “VoiceFirst” or Smart Speakers have proliferated. As Illustrated in Figure 2 below, smart speakers reached people in half of households at a pace that has never been seen before, surpassing smartphones and TV on the way.
Figure 2: Smart Speaker Proliferation
Smart Speaker Penetration, US, Years from Inception, % Population
Smart TV Smart Phone Speaker Radio 50%
Internet
Computer 25% Percent Adoption by U.S. Population Percent
0 5 10 15 20 Years, Since Commercial Introduction to US Market 1
Radio, TV, and computer measured as share of U.S. households. Smartphone and Internet measure as share of U.S. population. Source: Active analysis, U.S. Census Bureau, World Bank
Source: Activate 2018
Rapid acceptance has been accompanied by a fundamental change in the way that individuals interact with their favorite devices and the services they support. They speak, type or tap in full sentences; no longer blurting or pecking out search terms. They are not shy about testing their newly found NL chops by talking to everything from their TV remotes (often with successful results) to their dishwasher or toothbrush.
More importantly, people are framing their Google queries in complete sentences and expecting results in the same format. This has implications for marketing and customer service professionals because individuals are taking charge of their digital lives and activities in unprecedented ways. Spurred on by their own success, individuals have quickly taken to the idea of relying on Chatbots on their messaging platform of choice to understand what tasks they are undertaking, answer questions, schedule meetings and even suggest when to start preparing for their next activity.
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Thus the number of “skills” offered through Amazon’s Alexa has grown from a standing start to 30,000 in less than three years. The number of marketing ‘bots on Facebook Messenger expanded from about 100,000 in mid 2017 to over 200,000 today. The most recent entries to the ranks of essenger bots have deep hooks into dynamic data sets maintained in the CRM, product data, inventory and systems that inform customer service agents or e-commerce web sites. Like Web-based chat bots, they can answer questions, process orders, take payments, track the status of an order. All these functions are invoked by using natural language.
A Parallel World of Conversational Marketing The companies under investigation in this report (and three preceding Decision Makers’ Guides) concentrate on customer care and support. In a recently issued study, Opus Research evaluated a separate, but related, cohort of companies offering platforms to support development and deployment of Intelligent Assistants dedicated to engagements that precede a sale. They support the goals of Advertising and Marketing Departments and prove value by replacing the ineffcient platforms for email management, targeted advertising and other forms of MarTech.
Leaders in the Conversational Marketing category concentrate on text. Their engagement model is an asynchronous give and take over popular messaging services and apps. Success is measured in classic metrics for digital advertising and promotion; that is, frequency of exposure, response rates and ultimately closing a sale. The most highly regarded companies, therefore, offer an end-to-end experience with hooks into a company’s inventory tracking system and payment processing (cash register) as well as customer records (CRM) and other data.
In the coming months, the distinction between the two categories is bound to evaporate. You’ll note in this document that many of the highly rated platforms for Enterprise Intelligent Assistants (EIAs) are learning to support the goals of sales and marketing. And both camps have their eyes on the end-to-end relationship with both customers and prospects. For the time being, we will keep the two groups separate.
The Conversational Commerce Genome Enterprise Intelligent Assistants are indeed part of the much larger landscape incorporated within Conversational Commerce that Opus Research has tracked and defned over the past three years. All of these platforms rely on a common set of capabilities that are depicted in the lower two layers of Figure 3 below.
At their core are resources that support natural language processing (NLP) and machine learning. The former is able to derive meaning from input that individuals provide in their own words (typed or spoken). The latter insures that recognition of intent and responses to those words improve over time.
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Figure 3: Conversational Commerce Technology Landscape
Personal As istants Personal Advisors Conversational Sales & Marketing V rtual Customer Assistants Employee Assistants Shopping Assistants Assistants Scheduling & Conversational Marketing Mobile Care Wellness Assistants Collaboration Internet of Things Travel & Entertainment
Financial Advisors Sales Assistants Customer Service HR, On-Boarding, Metabots Virtual Assistants Operations, Service Desk Social & Dating
Intelligent Authentication Technologies
Identifcation (Federated & Distributed) Authentication (Biometrics & Multi-Modal) Fraud ( Analytics & Prevention)
Conversational Technologies Conversational Bot Messaging Emotions Speech Avatars Platforms Platforms Platforms & Sentiment
Enabling Platforms & Technologies
NLP, Machine Learning, & Semantic Search Conversational Analytics Knowledge Management
(Source: Opus Research)
Moving Toward an Open, End-to-End Platform While the community has moved dramatically forward along a maturity curve, “Intelligent Assistance” has a long way to go. The solution providers that bring the greatest value to enterprises are those that organize resources and services into a platform that:
1. Recognizes or, better yet, anticipates an individual’s intent across a signifcant percentage of contacts covering a large number of
2. Responds consistently with the right answer or recommended action at large scale.
This means that the best solutions come from vendors that have invested time and effort to build an inventory of “intents” or conversation fows to suit a broad set of vertical industries, call categories and use cases. These are baked into the Natural Language Understanding engines that work out-of-the-box. They should also be closely linked to Machine Learning resources that constantly improve the quality of responses, often with human assistance.
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Figure 4: The Ultimate AI Platform Single “truth” / mul iple channels • Centralized Resources Human-Like -Intent Recognition Advisor Intent Recognition Automated { & Answer Engine -Best Answers Document Prep
Predictive -Learning Analytics Next Best Answer • Decentralized Channels -
Virtual Chat Personalized “Simple” Bots Agent(Web) Mobile App Channels -Conversation } Message Speech Bots Enabled IVR Task Sophistication/Nuance Task -Mobile Apps Technology Maturity Source: Opus Research 2018)
Pursuing an approach whereby the centralized resources can respond as appropriate over an individual’s channel of choice is imperative.
Figure 5: Moving Along the IA Maturity Curve
Conversational More granular sources Traditional Aware of “state” & Embraces “Big preferences Static Data” User controlled Q&A Based on Unstructured Trusted & personal limitless info sources Real-time Single turn Security-minded We are here Source: Opus Research 2018)
Meanwhile, Opus Research sees the community of solution providers, in conjunction with their visionary clients, to move inexorably toward a more conversational future. It will be one in which the technology platform in use is able to provide precise answers to an individual’s question because it is employing a trusted line of communications over which an authenticated individual can use familiar terminology (natural language) to make requests and get answers based on more granular bits of knowledge than the answer in an FAQ or product pages in a ebsite.
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Enterprises Have Had to Adapt Quickly The rapid adoption and use of new, conversational end-points and services may not have caught every business by surprise, but it sure has them scrambling to introduce bots, chatbots, virtual agents and intelligent assistants to meet the growing demand.
Businesses around the world and across multiple verticals must come to grips with the rapid pace that tens of thousands of developers showed when building thousands and thousands of chatbots. Last year we said that companies could use their conversational commerce strategies to differentiate themselves from competitors, but it is too late for that. Today and in the foreseeable future, enterprises will come to realize that:
The full stack of solutions spans, Conversational Technologies, Conversational Intelligence, Conversational Marketing and Intelligent Authentication
In hyper-private environment, Intelligent Assistants can simplify authentication procedures and personal information management
In this environment, the criteria for evaluating prospective solution providers and their platforms distills into:
Enabling Platforms & Technologies: What tools are provided? (core NLU, service creation, analytics & reporting, tweaking tuning, authentication)
Enterprise Intelligent Assistant Maturity: What works out of the box? Speed to deploy, existing categories and intents, machine learning and “AI” capabilities (automated, self-improving, predictive, emotion/ sentiment), human-assisted, level of human involvement (professional services)
Track Record: Market presence, ability to scale, number of channels supported, number of verticals, library of knowledge
Future Plans & Vision: Key differentiators, partner strategies, technology roadmap
Therefore Opus Research has organized a comparison matrix that looks at each of the respondents according to these four overall categories and assigns values according to the following guidelines. This format supports understanding of what each vendor does well. Each business organization should attach its own level of importance (or weights) to these criteria.
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Figure 6: EIA Companies Under Review
Interactions AgentBot IPsoft Artifcial Solutions Jacada Aspect Software Kasisto Botanic Technologies LogMeIn Creative Virtual noHold CX Company Nuance DigitalGenius Omilia FaceMe SmartAction Flamingo SundownAI Genesys Synthetix IBM Watson Verbio Inbenta Verint
Below Opus Research has developed a solution provider comparison chart to help decision-makers evaluate how current enterprise solutions fulfll the requirements of Intelligent Assistance. Using a “Harvey Ball” rating system, Opus Research assesses each vendor’s product offerings within the following criteria: Enabling Platforms & Technologies; Enterprise Intelligent Assistant Maturity; Track Record; and Future Plans & Vision. [Further criteria defnition is detailed below.]
EDITOR’S NOTE: The accompanying dossiers contain information provided by the vendors under evaluation in response to a questionnaire and guidelines Opus Research provided during the first of 2018. While the information is directly from vendors, we have made an effort to normalize the responses in order to support comparison by prospective implementers in light of criteria that Opus Research has deemed important based on feedback from decision makers.
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Figure 7: EIA Solution Provider Comparisons
Enabling Enterprise IA Future Plans In Brief Platforms & Maturity Track Record & Vision Technologies Two versions of virtual assistant: “Answers” (quickstart) and AIVA (AI-based)
Automated AgentBot omnichannel customer service
Coined term “Natural Artifcial Language Interaction” Solutions (NLI)
Aspect Originated Interactive Software Text Response (ITR)
New focus on EIA, Botanic holds several patents; Technologies expertise in avatars, blockchain
Creative Virtual Trademarked V-Person & V-Portal
DigitalCX promotes CX Company rapid deployment and easy admin
Applies deep learning Digital Genius algorithms for customer service
Digital employee to FaceMe mimic human attributes, cross-channel aspirations
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Enabling Enterprise IA Future Plans In Brief Platforms & Maturity Track Record & Vision Technologies
Guided selling platform; Flamingo Collaborative Customer Interface
Introducing Kate, next Genesys generation Genesys product support for intelligent assistants
Cognitive Computing. IBM Watson Watson Conversation, virtual agent
“Intelligent Chatbot for Inbenta Business”; Consistent responses
Interactions Human-assisted adaptive understanding
IPsoft Amelia is a Digital Employee
Impressive enterprise Jacada install base, offers “low-code” IA integrations Focused on FiServ, Kasisto offer pre-packaged Banking Knowledge
Accessible ready- LogMeIn to-use, self-service solutions
SICURA, knowledge noHold mgt. and Natural Language Search
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Enabling Enterprise IA Future Plans In Brief Platforms & Maturity Track Record & Vision Technologies NINA, speech-enabled Nuance and human assisted virtual assistants
One platform, one Omilia integration – all channels and formats
Proprietary advanced SmartAction speech recognition engine; SaaS model
Offers Cloe, powered SundownAI by own NLP/ML resources
Long-time online Synthetix customer service specialist
Verbio Provides IA Framework
Acquired NextIT to Verint bolster dialog design, AI, NLP capabilities
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Figure 8: Evaluation Criteria Descriptions
Column 1: Brief description of Company, capture Opus Research’s POV
Column 2: Enabling Platforms & Technologies: What tools are provided? (core NLU, service creation, ana- lytics & reporting, tweaking tuning, authentication)
“Democratizes IA” easy to use tools for monitoring performance, refning responses; incorporating input from business unit executives
Deep domain knowledge for a number of verticals, relies on professional services for creation and tuning
Deep domain knowledge for limited number of verticals, heavy reliance on PS
Reliance on 3rd party resources for core NLU and ML and offers tools for branding and other forms of customization
Column 3: Maturity of Offerings: What works out of the box? Speed to deploy, existing categories and intents, machine learning and “AI” capabilities (automated, self-improving, predictive, emotion/sentiment), human-assist, level of human involvement (professional services)
High success rates for multiple verticals, categories and intents, up-to-date ontologies, support of multiple devices, channels and modalities; minimizes human supervision
Demonstrates ability to add categories and intents quickly; has framework for human assistance and supervision
Integrates of 3rd party resources for ML, cognition, NLU into coherent package
Largely reliant on 3rd party solutions to solve specifc problems
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Column 4: Track Record: Market presence, ability to scale, number of channels supported, number of verticals, library of knowledge
Longevity, customer base, documented use cases and case studies
Limited number of use cases, high-profle case studies, references. Limited years in business
Multiple deployments, operating history, largely proof of concepts and…
Just getting started, much in development, limited feld experience/testimonials
Column 5: Future Plans & Vision: Key differentiators, partner strategies, product roadmap
Takes a comprehensive end-to-end approach to intelligent assistance and customer journey from search to shopping cart.
Vision encompasses the latest DNN, ML, NLU, conversation development resources. Fosters growth and longevity through coherent vision
Focus on results, plans growth through additional geographic areas, verticals or languages
Specialist with well-developed technologies for point solutions.
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Enabling Platforms & Enterprise IA Track Record Future Plans Technologies Maturity & Vision
Headquarters: Burlington, MA Website: http://www.nuance.com
FIRM GRAPHICS Year business started: 1992 Investment/Funding: N/A Number of employees: 13,500 Revenue (either estimated or publicly available): Non-GAAP revenue of $1,977.4 million in FY17
BRIEF COMPANY DESCRIPTION: .
CORE INTELLIGENT ASSISTANT PRODUCTS AND SERVICES:
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Customer Engagement Strategy Consultative sales approach combines the delivery of software technology with professional services experts including digital analysts, graphic, UI and content designers, big data reporting experts, customization engineers, optimization strategists, voice of the customer analysts and speech scientists.
Revenue Models
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KEY DIFFERENTIATORS: • • • • •
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About Opus Research Opus Research is a research-based advisory frm providing critical insight and analysis of enterprise implementations of software and services that support multimodal customer care and employee mobility strategies. Opus Research calls this market “Conversational Commerce” with tailored coverage and sector analysis that includes: Self-Service & Assisted Self-Service, Voice & Call Processing, Web Services, Personal Virtual Assistance, Mobile Search and Commerce and Voice Biometrics.
For sales inquires please e-mail [email protected] or call +1(415) 904-7666 This report shall be used solely for internal information purposes. Reproduction of this report without prior written permission is forbidden. Access to this report is limited to the license terms agreed to originally and any changes must be agreed upon in writing. The information contained herein has been obtained from sources believe to be reliable. However, Opus Research, Inc. accepts no responsibility whatsoever for the content or legality of the report. Opus Research, Inc. disclaims all warranties as to the accuracy, completeness or adequacy of such information. Further, Opus Research, Inc. shall have no liability for errors, omissions or inad- equacies in the information contained herein or interpretations thereof. The opinions expressed herein may not necessarily coincide with the opinions and viewpoints of Opus Research, Inc. and are subject to change without notice. Published June 2018 © Opus Research, Inc. All rights reserved.
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