Criteria for Comparing AI Chatbots and Customer Experience Solutions

Navigating the market for a customer experience or customer service engagement solution such as a chatbot, virtual assistant, asynchronous messaging platform, or IVR can be confusing. With multiple vendors offering solutions that sound alike, how can you choose the best one for your business?

Making customer engagement consistent across all channels is key to maintaining your brand’s equity. From the time consumers see your ad or engage with your web content to when they are greeted by your chatbot or escalate to an agent for faster resolution, their journey must be seamless. Your experiences need to delight customers at every stage, on all the channels you support. That calls for enterprise-grade enabling technology to bring customer experience to life.

To help you find your way in the end-to-end AI chatbot and customer experience solution market, we have put together our view of some of the detailed criteria to assess based on multiple analyst reports so you know what to look for in a comprehensive solution.

REQUEST DEMO

Customer-Facing Experience

Criteria	[24]7.ai	Genesys	IPSoft	LivePerson	Nuance
Chatbot / Virtual agent analyst ranking		Somewhat	Somewhat	N/A (not ranked)	
Conversational AI & FAQ		Somewhat		 (partner offering)	Somewhat
Blending AI chatbots & agents		Somewhat	Somewhat (Focuses on internal Apps & RPA)	Somewhat	
Unified digital & voice channels			 (Digital only)	 (Digital only)	Somewhat
Apple Business Chat & smart messaging capabilities				Somewhat	
Digital media personalization					

 – aligns with all the critical capabilities listed in the respective section of capabilities below.

Enterprise-Grade Enabling Technology for Customer Experience

Criteria	[24]7.ai	Genesys	IPSoft	LivePerson	Nuance
Intent prediction		Somewhat		N/A (not ranked)	Somewhat
Enterprise customer engagement AI		Somewhat		N/A (not ranked)	Somewhat
Blending AI chatbots & agents		Somewhat	Somewhat	Somewhat	
Enterprise grade		Somewhat	Somewhat (Focuses on internal Apps & RPA)		

 – aligns with all the critical capabilities listed in the respective section of capabilities below.

The foregoing items represent our opinion of some of the key criteria, compiled based on our review and interpretation of current information publicly available from company web sites, analyst reports, and other sources. Analyst source material includes: Forrester Top 10 Chatbots for Enterprise customers 2017, Decision Maker’s Guide to Enterprise Intelligent Assistants, Opus 2018, 2017 Dimension Data: Global Customer Experience, 2017 Mitch Kramer Virtual Assistant Update, 2017 CCW Chatbots, 2017 Gartner Chatbot Guide: 7 Decision Points, Gartner Top 10 Strategic Technology Trends for 2018, Forrester Top 10 2018 Predictions, Forrester 2018 Blended AI Customer Service Predictions, 2018 DMG Intelligent Virtual Agent Report, 2018 DMG Speech Analytics Product Guide Additional sources: Live Person website Oct, 2018

Chatbot / Enterprise Intelligent Assistant Analyst Ranking

Not all chatbots and enterprise intelligent assistants are created equal—don’t let imposters with limited functionality fool you. Leading analysts consistently rank [24]7.ai as a top vendor thanks to our comprehensive range of cutting-edge capabilities. But don’t take our word for it.

“The [24]7.ai 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.ai is looking to establish a more componentized and reusable approach to chatbots.”

—Forrester Research: The Top 10 Chatbots for Enterprise Customer Service

“[24]7 AIVA is the only solution to deliver unified self-service from simple FAQs to complex, conversational issues and online transactions, all with one end-to-end virtual agent.”

—Opus Research: Decision Maker’s Guide to Enterprise Intelligent Assistants

“What sets apart [24]7 AIVA is the demonstrated ability to enable brands to leverage both AI and human resources to perform tasks swiftly and accurately at scale, thereby creating conversational customer experience and brand affinity.”

—Dan Miller, Lead Analyst at Opus Research

Capabilities

Conversational AI and FAQ

AI chatbots and virtual agents are powerful, data-driven solutions that give customers the option to self serve and complete journeys on their own—the experience most are after. But not all chatbots perform the way your customers expect. Simple chatbots are limited to casual use and can only answer basic questions, similar to an FAQ. For the majority of businesses, AI chatbots need to be smarter to be effective. This chart outlines the range of chatbot capabilities offered by chatbots on the market today.

AI Chatbots Span a Range of Capabilities

Assessing Conversational AI and FAQ Capabilities

From a customer-facing perspective, look for the following:

1. Natural, human-like chatbot conversations.
2. Quickly identifies what the customer needs and routes to the best resource.
3. Proactive, contextual greetings.
4. Combined natural and scripted (FAQ) conversations.
5. Multi-modal voice, visual, and touch engagement.
6. Tone changes based on sentiment.
7. Journey changes based on sentiment.
8. Interactive cards for complex information, such as product comparison.
9. Branded look and feel.

Look for the following in the enabling technology:

1. Intent prediction engine.
2. Enterprise AI for customer engagement.

Blending AI Chatbots and Agents

Leveraging AI for a successful customer service or sales program requires the right mix of technology and human assistance. Handing off from a chatbot to a human customer service agent is one example of blending, but if it’s done without maintaining data from the chatbot conversation, the customer will have to start over—which is both frustrating and annoying. Intelligent blending elevates the experience to support chatbots handing off conversations to a human agent with context, humans assigning bots to continue conversations, agents assisting bots to disambiguate conversations, and chatbots supporting agents with response recommendation during conversations.

Assessing Agent and Chatbot Blending Capabilities

From a customer-facing perspective, look for the following:

1. Escalating to agents with ease, including context and dialog transitions.
2. De-escalate to chatbot to continue the conversation, freeing up agents.
3. Agents help chatbot understand conversational context.

Look for the following in the enabling technology:

1. Disambiguation by agents.
2. Chatbot supports agents with response recommendation.

Unified Digital and Voice Channels

Today’s customers expect to engage with you on their channel of choice and experience a continuous conversation regardless of elapsed time or if they change channels during their journey—for example, starting on phone and continuing on chat, or starting on web and continuing in a mobile app. With more channels than ever before, offering a consistent experience everywhere is crucial: Chat (with agent, chatbot, or enterprise intelligent assistant), social media, IVR (intelligent voice response or simply the 1-800 number), and messaging apps (SMS, Apple Business Chat, WhatsApp, FB Messenger, WeChat).

Unifying digital and voice channels by building them on the same technology platform enables transitions between channels, and makes it easy to deploy updates. Your enterprise intelligent solution should be built with a common business logic and intent engine so you can build natural language models once and easily deploy them on any digital or voice channel. This also allows you to quickly expand to new channels and offer an uninterrupted experience, no matter how often customers change channels.

“Already used by Fortune 500 companies in digital and conversational IVR configurations, [24]7 AIVA is built on a unified platform so that clients can build once, then deploy anywhere across digital and voice channels in multiple configurations.”

—Opus Research

Assessing Unified Digital and Voice Channel Capabilities

From a customer-facing perspective, look for the following:

1. Continuous conversations across preferred channels.
2. Easy transitions between channels (for example, IVR to chat, voice to mobile, agent to bot).
3. Consistent digital experience on all channels including web, mobile, branded apps, VPAs, and messaging.
4. Alexa / Google Home integration.

Look for the following in the enabling technology:

1. Futureproof platform that builds once and deploys on any channel with a common business logic, UX, common AI and intent engine.
2. Single platform to empower digital and voice.
3. VPA and IoT integration.

Apple Business Chat and Smart Messaging Capabilities

Messaging apps have become the channel of choice among the 25-and-under demographic and are gaining popularity every day. Part of their appeal is that they allow customers to control the pace and timing of conversations. Asynchronous messaging capabilities let customers pick up their conversations where they left off at any time, even if they’re using a different device or returning days later. An enterprise intelligent assistant solution allows you to meet your customers where they are by offering leading conversational experiences on chatbots as well as through all social apps, business apps, and Apple Business Chat.

Assessing Apple Business Chat and Other Messaging Channel Capabilities

From a customer-facing perspective, you need to:

1. Enable conversational AI and agent-chatbot blending on messaging channels.
2. Engage on social apps, business apps, and Apple Business Chat.
3. Pick up the conversation on any device.

Digital Media Personalization

Customer experience extends to all your brand’s customer interactions, starting with ads. More than ever, consumers today feel that the advertising they see is irrelevant, impersonal, and annoying. Customer service and chat data are powerful sources for understanding what a consumer wants (their intent) and personalizing the message in ads, web pages, or mobile to help them achieve their goal. At the same time, sales and customer service conversations can benefit from what digital ads can teach us, given that most customer engagement journeys still start on search engines. Using ad-intent to personalize your sales and customer service enables agents and chatbots to engage customers with relevant information from the first hello.

Assessing Digital Media Personalization Capabilities

Look for the following customer-facing functions:

1. Engage with highly relevant 1:1 messages on web pages and digital ads.
2. Adapt messages based on intent and context such as location, affinity, proximity and real-time behavior.
3. Personalize sales and/or customer service greetings.

Look for the following in the enabling technology:

1. Omnichannel intent prediction that’s self-learning with every interaction, on any channel.
2. Predicts customer value based on real-time behavioral and contextual signals.
3. Uses AI to match message, creative, audience, and bid for every user.
4. Dynamically populate data-infused message templates based on real-time signals, context, and behavior.

Intent Prediction

Customers expect companies to understand who they are and what they intend to do. To accurately predict intent, it isn’t enough to look at the last click, the last page view, or analyze natural language. Anticipating what a customer wants in real time requires pairing multiple sources of data with AI to combine user behavior, transactions, and profile details. At the same time, you need to understand the value of the customer and provide the best channel treatment for that customer at precise moments in their journey, on any device, in any environment—down to the millisecond. To do this you need a platform that can determine intent based on both aggregated interactions for known and unknown users, and personalized data pulled from back-end systems.

Assessing Intent Prediction Capabilities

From a customer-facing perspective, look for the following:

1. Omnichannel intent prediction.
2. Multi-layered intents beyond natural language that combines user behavior, transactions and profile details.
3. Pre-trained industry Intent models.
4. Unsupervised learning to discover top chat transcript intents.

Look for the following in the enabling technology:

1. Multi-layered intents.
2. Omnichannel intents prediction and orchestration.
3. Industry intent models.
4. Reusable models.
5. Intent discovery.

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

—Forrester Research

Enterprise AI for Customer Experience

Cutting-edge enterprise AI uses machine learning (ML) to focus on solving real-world problems with neural networks designed to mimic our own decision-making. AI powered by customer data uses deep learning to solve just about any problem requiring thought—either human or artificial. When combined with relevant industry data, enterprise AI can understand your organization’s most common customer journeys, ensuring your deployment is effective right out of the box.

Assessing Enterprise AI Capabilities

Make sure the following is available:

1. Omnichannel AI integrates learning and signals from all interactions.
2. Out-of-the-box models for common customer journeys in key industry sectors.
3. Cutting-edge deep learning / ML / AI technology optimizes engagement with minimal human intervention.
4. Advanced conversational models include algorithms for identifying social intent and user sentiment.
5. Kickstart development with unsupervised learning to discover conversational flows and dialogs.
6. Bot development tool suite enables internal teams to easily design, develop, and deploy bots.

Enterprise grade

To be effective and meet customer expectations, your solution needs to be intelligent. Enterprise grade solutions will mimic your best human agents, helping you effectively handle an increasing volume of customer inquiries, reduce operating costs, and deliver the self-serve experiences your customers crave. An enterprise-grade solution will fit right into your existing technology environment, integrating with ease. It should be reliable and support your strict security, authentication, and user privacy needs. When you get it right, agents learn from bots and bots learns from agents, elevating every aspect of your contact center at scale.

Assessing Enterprise Readiness

Look for the following:

1. Integrates with back-end systems including industry leading CRMs, helpdesk systems, and in-house CRMs (for example, Salesforce, Zendesk, Microsoft Dynamics).
2. Integrates with routing and telephony systems (such as Avaya, Cisco, and Genesys).
3. 100% cloud-based SaaS.
4. Multi-tier security and authentication.
5. Scalability, reliability, and redundancy.
6. User data privacy.
7. Clear long-term vision and roadmap that is committed to innovation.
8. Mission critical deployments at top F1000 organizations.