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The Top 10 Chatbots For Enterprise Customer Serviceby Ian JacobsJune 29, 2017

For ApplIcAtIon Development & DelIvery proFessIonAls

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Key takeawaysNuance, IPsoft, And [24]7 Earn Spots on Forrester’s recommended Vendor Listnuance’s multimodal and multichannel efforts stand out. Intent engines for Ipsoft and [24]7 shine. creative virtual, Artificial solutions, and Inbenta sport a mix of good technologies; Interaction’s speech-based tools are notable. next It and nanorep are deepening their intriguing road maps, and reply.ai is starting to gain momentum with an open ApI approach.

NLU, machine Learning, And Dialogue management Are The Biggest Differentiatorsno vendor can succeed without a strong intent engine, security and authentication, and multichannel capabilities. natural language understanding (nlU), machine learning, and dialogue management are critical, as are reporting and analytics and a robust product road map.

Why read this report

In Forrester’s evaluation of the emerging market for chatbots in customer service, we identified the10 most significant providers — [24]7, Artificial solutions, creative virtual, Inbenta, Interactions, Ipsoft, nanorep, next It, nuance, and reply.ai — in the category and ranked them. this report details our findings about how well each vendor scored in 10 criteria and where they stand in relation to each other. Application development and delivery (AD&D) and customer service professionals can use this review to select the right partner for their chatbot needs.

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table of contents

Chatbots For Enterprise Customer Service Evaluation Overview

Why companies Buy: Digital experience platforms Anchor your Digital presence

product overview

1. Nuance

product overview

2. IPsoft

product overview

3. [24]7

product overview

4. Creative Virtual

product overview

5. Artificial Solutions

product overview

6. Inbenta

product overview

7. Interactions

product overview

8. Next IT

product overview

9. Nanorep

product overview

10. Reply.ai

Supplemental Material

related research Documents

Assess customer service capabilities to pinpoint opportunities For Better service

executive Q&A: Boost your chatbot IQ

How to Differentiate With excellent mobile customer service

For ApplIcAtIon Development & DelIvery proFessIonAls

The Top 10 Chatbots For Enterprise Customer Service

by Ian Jacobswith stephen powers, Bill seguin, and Diane lynch

June 29, 2017

http://www.forrester.com/go?objectid=RES59308





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For ApplicAtion Development & Delivery proFessionAls

The Top 10 Chatbots For Enterprise Customer ServiceJune 29, 2017

© 2017 Forrester research, inc. Unauthorized copying or distributing is a violation of copyright law. [email protected] or +1 866-367-7378

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chatbots For enterprise customer service evaluation overview

In the summer of 2016, a Wall street Journal headline blared, “robots on track to bump humans from call-center jobs.”1 chatbots are at peak hype right now. need proof? Facebook messenger had zero bots in February 2016 — and 100,000 of them 14 months later.2 Few of those Facebook messenger chatbots provide the robust service resolution and security features that would allow larger enterprises to remove contact centers from the customer service flow. But AD&D professionals have begun to deploy a different type of technology: enterprise-grade chatbots that can augment and, in some cases, replace human agents.

to truly meet a need for enterprise-grade customer service, chatbots (also called virtual agents and cognitive agents) must be able to understand what a customer speaks or types, discern their intent, respond in a conversational manner, and act on the customer’s behalf. All of this must take place in a secure environment, and the chatbot must seamlessly hand off the interaction to a live agent when required. companies have a wide range of supplier options for this type of chatbot. several vendors, such as Artificial solutions and next It, have been steaming toward this vision for more than 15 years. others, such as reply.ai, have only recently debuted.

Why Companies Buy: Digital Experience Platforms Anchor Your Digital Presence

enterprise-grade chatbot tools enable companies to achieve several key outcomes. they can:

1. Deflect customers from expensive live agent support through successful self-service with the chatbot.

2. reduce the average handle time for agent-assisted support by managing some of the conversation in the chatbot.

3. expand self-service to emerging channels such as mobile apps, social media, and mobile messaging.

4. Use existing contact center agents and logs of historical customer service interactions to train chatbots.

5. Identify gaps in knowledge bases used by agents through analysis of chatbot interactions.

6. Drive new revenue through improved online conversion.

When considering a vendor for your enterprise customer service chatbot, look at Forrester’s top 10 picks and assess their performance against each of our criteria (see Figure 1 and see Figure 2).




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FIGUrE 1 the top 10 chatbots For enterprise customer service

CompanyRank Mac

hine

learn

ing

Reporti

ng & a

nalytic

s

Multi

chan

nel

Inte

nt engin

e

Securit

y & a

uthen

ticat

ion

Dialogue

man

agem

ent

Road m

ap

Natura

l languag

e under

stan

ding

Vision

Nuance

IPsoft

[24]7

Creative Virtual

Artificial Solutions

Inbenta

Interactions

Next IT

Nanorep

Reply.ai

1

2

3

4

5

6

7

8

9

10

Differentiated On parNeeds improvement Recommended

Reven

ue




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FIGUrE 2 Assessment criteria

Criteria item Criteria description

How well does the product automatically improve with experience (for example, using supervised learning, unsupervised learning, etc.)?

How robust are the product’s tools for monitoring and reporting both defined KPIs and knowledge performance (white space analysis)?

How well does the product support conversational interactions over multiple touchpoints such as web, native apps, messaging apps, and interactive voice response (IVR)? How well does the product support escalation to assisted service? How well does the product integrate into other customer service systems, such as CRM, back office systems, and transactional systems, and other customer service channels?

How well does the product determine intent based on both aggregated interactions across users and personalized data pulled from back-end systems?

How robust are the product’s security, authentication, and authorization features, including two-factor and time-out authentications, biometric authentications, and self-destructing messages?

How well does the product enable the creation and management of the dialogue with the customer, incorporating everything that has happened so far during the dialogue? How well does this work across multiple languages?

How well does the product comprehend customer input (speech or text) using typical and natural utterances? How well does it understand the structure and context-independent meaning of human language? How well does the product comprehend multiple languages? What prebuilt language models ship with the product?

How well defined are planned enhancements, and how effectively do they address changing customer requirements?

How well does the product vision align with the need for its clients to win, serve, and retain customers? How does the product vision drive differentiated customer service experiences?

What is the annual product revenue?

Machine learning

Reporting & analytics

Multichannel

Intent engine

Security & authentication

Dialogue management

Natural language understanding (NLU)

Road map

Vision

Revenue




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Product overview

1. nuance

Forrester’s Take

our evaluation found that (see Figure 3):

› Nuance leads the pack with robust NLU and multichannel capabilities. With a focus on both customer acquisition and customer retention, nuance offers a stout product vision and differentiated enterprise-grade security, including biometrics.

› Nuance still needs to expand its channel reach. Although it currently offers a wide set of several options for deploying a chatbot, the company must also integrate with multiple messaging platforms. In addition, it needs to beef up cross-channel intent prediction.

› Nuance makes an excellent match for companies requiring enterprise-grade solutions. nuance allows companies to deploy multimodal chatbots across web, mobile, and voice channels and seamlessly connect those self-service tools to assisted service.

Nuance Customer references Summary

nuance has very happy customers that were thrilled to drive both demonstrable customer satisfaction improvements and cost savings in under six months.

FIGUrE 3 nuance Quickcard

RANK 1/10

SAMPLE REFERENCE QUOTES

“The ease of access to its most authoritative and knowledgeable staff was a huge benefit.”

“The account manager and the professional services team have been great to work with.”

Nuance

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue

Differentiated On parNeeds improvement

RECOMMENDED PRODUCT

Products evaluated: Nina and Nuance Digital Portfolio *NLU = natural language understanding




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Product overview

2. Ipsoft

Forrester’s Take


› IPsoft provides a very well-rounded solution, strong in all core categories. Ipsoft offers innovative features, including the ability for the solution to learn by observing human agents. It also has an intriguing road map that includes facial sentiment detection.

› IPsoft’s sophisticated functionality comes with a hefty price tag, lengthening roI. the company’s dogged persistence in pushing the concept of animated avatars won’t help in bringing those costs down.

› IPsoft fits companies looking to automate end-to-end customer-facing processes. Ipsoft’s robust nlU and dialogue management, married to enterprise-grade security, make it a top pick for companies looking to do more than just answer questions.

IPsoft Customer references Summary

customers said they could refocus their agents on higher-value tasks by handling simpler queries through the chatbot. they also applauded Ipsoft’s account management.

FIGUrE 4 Ipsoft Quickcard

RANK 2/10


“It helps us avoid outsourcing — not replacing a human with a cheaper human but with a machine.”

“It’s somewhat difficult to navigate the organization to find the right person.”

IPsoft

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


RECOMMENDED PRODUCT

Products evaluated: Amelia *NLU = natural language understanding




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Product overview

3. [24]7

Forrester’s Take


› [24]7’s heavy-duty intent engine and multichannel features set it apart. concentrating on a “build once, deploy many” approach and an ambitious and unique road map, [24]7 is looking to establish a more componentized and reusable approach to chatbots.

› [24]7’s high-end tools require high-end vendor involvement. [24]7’s data scientists and service personnel create robust solutions, but the company has yet to open some basic management and tuning functions to its customers.

› [24]7 is a strong fit for firms looking to blend chatbots into an omnichannel strategy. [24]7 allows these companies to apply the same nlU, prediction, and decisioning technology across self- and assisted-service in different channels.

[24]7 Customer references Summary

customers believe that [24]7 drives digital deflection while improving net promoter scores.3 However, they need more help in enabling the [24]7 solution to coexist with other AI technologies.4

FIGUrE 5 [24]7 Quickcard

RANK 3/10


“The solution was quick to prototype to produce proof of concepts to test and learn.”

“Proactive success/account management provides us with continuous improvement with the solution.”

[24]7

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


RECOMMENDED PRODUCT

Products evaluated: [24]7 Answers and [24]7 AIVA Assistant *NLU = natural language understanding




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Product overview

4. creative virtual

Forrester’s Take


› Creative Virtual delivers enterprise-grade features. several larger customers host their own version of the creative virtual product, providing tighter security controls. the nlU marries an automated approach with a hands-on power-user approach.

› Creative Virtual needs improvement in reporting and data visualizations. creative virtual’s reporting remains historical, and live chat agents lack actionable dashboards. Additionally, customer concentration in europe and Asia may limit appeal outside of that market.

› Creative Virtual would work well for companies with mobile-first mindsets. these companies would value creative virtual’s ability to blend input types (click, text, and speech) in a mobile environment, coupled with leading machine learning tools.

Creative Virtual Customer references Summary

customers lauded creative virtual’s willingness to solve all technical issues. some, however, identified complications when integrating chatbots with third-party tools.

FIGUrE 6 creative virtual Quickcard

RANK 4/10


“One of the best partners I’ve encountered at working with us to quickly develop effective solutions.”

“No real-time reporting; there’s at least a day lag.”

Creative Virtual

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: V-Person, V-Person Live Chat,and V-Portal *NLU = natural language understanding




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Product overview

5. Artificial solutions

Forrester’s Take


› Artificial Solutions offers rapid speed-to-deployment. With Artificial solutions’ intuitive graphical development environment, companies can quickly design, test, and deploy chatbots with the prebuilt ability to engage in “chitchat” (“tell me a joke,” for example).

› Artificial Solutions lags in its machine learning abilities. Although recent technology improvements show promise, Artificial solutions needs to move toward a stronger learning model. Additionally, the company’s developer and partner community remains small.

› Artificial Solutions is a nice match for companies looking for multilingual solutions. Artificial solutions helps customers quickly build and deploy conversational chatbots that maintain conversational context across 35 languages.

Artificial Solutions Customer references Summary

customers praised Artificial solutions’ customer service and technical support but felt that technological areas that help with continuous improvement need beefing up.

FIGUrE 7 Artificial solutions Quickcard

RANK 5/10


“The stack around multiple languages and data supporting our chatbot is highly professional.”

“Automated improvements and machine learning are currently a gap that we’re looking for them to fill.”

Artificial Solutions

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: Teneo *NLU = natural language understanding




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Product overview

6. Inbenta

Forrester’s Take


› Inbenta provides robust multilingual and conversational abilities. Inbenta offers a distinctive “chitchat” module enabling nonservice conversations with the chatbot. Its intent engine captures information for later usage in determining intents.

› Inbenta’s multichannel story needs shoring up. Although Inbenta offers its own chat tool, it lacks many enterprise-grade features. Its method of providing context during an escalation from a chatbot overwhelms the agent with information.

› Inbenta is a fit for companies needing chatbot consistency across multiple languages. these companies typically want to create a single program to drive self-service in multiple countries and are heartened by proven similar deployments.

Inbenta Customer references Summary

Inbenta’s customers lauded the company’s multilanguage capabilities, its ability to drive cost savings, and the lack of need for intensive professional services engagements.

FIGUrE 8 Inbenta Quickcard

RANK 6/10


“I particularly liked the functionality that autoextracted the knowledge base we had on 14 websites.”

“The KPIs provided by the vendor aren’t exactly what we’re searching for.”

Inbenta

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: InbentaBot *NLU = natural language understanding




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Product overview

7. Interactions

Forrester’s Take


› Interactions shines in speech-based assistance. Its adaptive understanding model, which uses both AI and human analysts, drives better accuracy, while its reusable dialogue components make dialogue management simpler and offer vertical-specific functionality.

› Coming in the voice world and moving to digital, Interactions lags in digital maturity. Unlike others that expose their machine learning, Interactions offers under-the-cover resources and a managed services approach to continuous improvement.

› Interactions is a good fit for companies looking to replace traditional IVrs.5 these companies continue to see high volumes of inbound voice calls and want a method to make that self-service experience more conversational, natural, and compelling.

Interactions Customer references Summary

Interactions’ customer references cited consumer satisfaction with the solution as a major plus. However, they also identified room for improvement in post-sales account management.

FIGUrE 9 Interactions Quickcard

RANK 7/10


“Our customers overwhelmingly like using the solution.”

“It’s a challenge to keep our application up to date. ”

Interactions

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: Interactions Intelligent Virtual Assistantand Voice Biometrics (add-on) *NLU = natural language understanding




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Product overview

8. next It

Forrester’s Take


› Next IT’s reporting and analytics stand out. sporting clean and clear visualizations, next It helps companies with smart targeting that determines which functions to focus a chatbot on. It also ranks among the leaders in chatbot-specific revenue.

› Next IT trails in security and dialogue management. next It concentrates on back-end security, leaving the front-end issues primarily to others. It also needs to better empower business users to build and manage complex dialogues.

› Next IT is a good fit for enterprises looking to cover all the basics well. these companies want intelligent search, deflection of basic service issues away from assisted channels, and some commerce functionality.

Next IT Customer references Summary

customers saw rapid return on investment through deflection of contacts away from human agents. they also praised next It’s account management and customer support chops.

FIGUrE 10 next It Quickcard

RANK 8/10


“Next IT’s administration tools are intuitive, easy to use, and provide good control.”

“Next IT could be more aggressive in pushing us to be more innovative.”

Next IT

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: AIme Cognitive Integration Platform,AIme Design Kit, and AIme Intelligence Kit *NLU = natural language understanding




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Product overview

9. nanorep

Forrester’s Take


› Nanorep’s intent classification requires only small training sets. this is the backbone of nanorep’s vision. Its knowledge base provides a single source of truth across all interactions; a promising road map includes a one-to-many model for case creation and resolution.

› In several areas, Nanorep lacks enterprise maturity. though its reporting contains attractive visualizations, nanorep lacks conversational analytics. While it can be embedded in multiple touchpoints, it can share a conversation ID only during escalation.

› Nanorep is a good fit for companies driving chatbots with a mature knowledge base. nanorep’s all-inclusive packaging gives customers immediate access to all its nlU and knowledge tools as well as all the currently supported touchpoints.

Nanorep Customer references Summary

customers praised nanorep’s staff for acting as true partners in problem solving. However, they also cited a need for greater maturity in omnichannel and dialogue management.

FIGUrE 11 nanorep Quickcard

RANK 9/10


“Working with extremely knowledgeable senior technical staff is the best part of this solution.”

“Biggest issue: The chatbot isn’t able to carry on an extended conversation in email.”

Nanorep

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: Nanorep Self-Service *NLU = natural language understanding




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Product overview

10. reply.ai

Forrester’s Take


› reply.ai focuses on chatbots for messaging. reply.ai offers customers a clear focus and innovative commerce tools such as supporting chatbots in ad units. Its design tools sport a line-of-business-friendly drag-and-drop approach.

› reply.ai views natural language understanding as a commodity. this forces customers to use third-party services such as ApI.ai or Wit.ai and limits reply.ai’s ability to control the direction of the technology and customers’ ability to tune it.

› reply.ai makes a good fit for companies looking to adopt a fully API-driven approach. these companies want to replace Ivrs using a conversational strategy and already have their own security and natural language priorities sorted out.

reply.ai Customer references Summary

customers love reply.ai’s customer success services. However, they also recognize that some of the company’s technologies — including machine learning — require further development.

FIGUrE 12 reply.ai Quickcard

RANK 10/10


“The ease of access to its most authoritative and knowledgeable staff was a huge benefit.”

“Content management integration is still maturing, as are the analytics capabilities.”

Reply.ai

Machine learning


Multichannel

Intent engine


Dialogue management

NLU*

Road map

Vision

Revenue


Products evaluated: ReplyAnalytics, ReplyCRM,ReplyFlow, and ReplySupport *NLU = natural language understanding




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supplemental material

The Forrester Evaluation methodology

We conducted primary research to develop a list of vendors that met our criteria for the evaluation and definition of this emerging market. We evaluated vendors against 10 criteria, seven of which were based on product functionality, product vision, product road map, and product revenue. We invited the top vendors in this space to participate in an rFp-style demonstration and interviewed customer references. We then ranked the vendors along each of the criteria and summed these to determine the overall rankings. the vendor with the lowest score ranked first overall, while the vendor with the highest score ranked 10th. We gave vendors ranking between first and third for a criterion the “differentiated” designation, vendors ranking fourth through seventh the “on par” designation, and vendors ranking eighth through 10th the “needs improvement” designation.

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endnotes1 source: trefor moss, “robots on track to Bump Humans From call-center Jobs,” the Wall street Journal, June 21,

2016 (https://www.wsj.com/articles/robots-on-track-to-bump-humans-from-call-center-jobs-1466501401).

2 source: Khari Johnson, “Facebook messenger hits 100,000 bots,” ventureBeat, April 18, 2017 (https://venturebeat.com/2017/04/18/facebook-messenger-hits-100000-bots/).

3 net promoter and nps are registered service marks, and net promoter score is a service mark, of Bain & company, satmetrix systems, and Fred reichheld.

4 Artificial intelligence.

5 Interactive voice response.

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