IDC

November 2021

Worldwide Conversational Artificial Intelligence Software Platforms for Customer Service 2021 Vendor Assessment

Written by: David Schubmehl, Hayley Sutherland & Mary Wardley
Product Type:
IDC: MarketScape
This Excerpt Features: Omilia

Worldwide Conversational AI Software Platforms for Customer Service 2021

Capabilities Strategies Participants Contenders Major Players Leaders

Leaders

Amelia

Cognigy

Kore.ai

Microsoft

Oracle

Verint

OmiliaFeatured Vendor

Major Players

Google

IBM

[24]7.ai

Boost.ai

Genesys

Salesforce

Avaya

Ada

Contenders

Inbenta

IDC MarketScape Methodology

IDC Opinion

Almost all types of organizations have customers, and most of them struggle to effectively scale communications with customers that have questions or need actions taken. Significant amounts of money are spent on contact centers, interactive voice recognition (IVR) systems and websites meant to support a company’s interaction with customers. When the COVID-19 pandemic struck, companies found themselves with an even larger challenge than they had faced previously. COVID-19 placed massive stress on communities and economies around the globe. Healthcare providers, companies, and government agencies were overwhelmed by the number of urgent inquiries and concerns caused by this pandemic. Across the globe, companies in virtually every industry — whether banks, hotels, manufacturers, or retailers — were exploring ways to communicate with customers while their physical locations were closed to the public. Call centers were swamped, as anxious consumers looked for answers about the virus, purchased needed supplies and goods, or attempted to cancel or change travel plans. This situation caused long wait times and dropped connections, preventing callers from getting help when they needed it most. At the same time, call centers were short-staffed as agents called in sick or attempted to transition to remote work. 

Throughout all of this, conversational artificial intelligence (AI) tools and technologies proved their worth during the COVID-19 crisis. Organizations turned to conversational AI software platforms, developing customer service applications for help during these unprecedented times. For years, organizations have wished for “virtual” or “digital” assistants that could carry some of this conversational load working with customers. The good news is that recent breakthroughs and improvements in speech recognition, natural language processing(NLP)/natural language understanding (NLU), and conversational artificial intelligence made that wish come true for an ever-increasing number of organizations over the past two years.

Over the past three to five years, due to advances in deep and machine learning, conversational AI applications can understand and respond to conversation in all its various forms, including telephony, voice, text messaging, web messaging, WhatsApp, and Facebook Messenger. The conversational AI software platforms that IDC has evaluated as part of this IDC MarketScape have shown that organizations can develop and deploy sophisticated AI-based conversational agents that can interact with customers, consumers, and the public at large to answer their questions, help them conduct transactions, and provide a wide range of self-service that wasn’t possible only a few years ago.

As part of this evaluation, IDC spoke with dozens of organizations using these conversational AI software platforms to develop and deploy applications that are providing great customer service and generating significant return on investment (ROI). Among the technology buyers IDC spoke with, we noted a range of maturity in implementations of conversational AI, from point solutions to enterprisewide deployments. If your organization is not using or evaluating conversational AI applications for customer service use cases, it should be. 

The technologies behind these conversational AI software platforms are good and getting better by the day, but that shouldn’t stop organizations from evaluating and implementing these solutions as soon as they can. Conversational AI tools and technologies are rapidly evolving, and new vendors, products, technical innovations, and acquisitions are a frequent occurrence. Conversational AI platforms can be used for a broad set of use cases related to customer service, for both customer-facing applications and internal-facing agent assistance, and these platforms can vary greatly in terms of prepackaged offerings and templates, low-code/no-code tools for business analysts and line-of-business (LOB) subject matter experts, and customizable developer tools. For example, some organizations will benefit from vendors that offer low-code/no-code tools and other features that can eliminate the need for one or more of the initial three steps in the conversational AI-build process (see Figure 2). Other organizations will need the ability to work directly with one or more of these areas to customize aspects such as language, conversation flows, and workflows.

Tech Buyer Advice

IDC offers the following advice to technology buyers considering conversational AI:

  • Assess your starting point. If your organization is new to conversational AI or embarking on a new use case or channel, decide up front how you will train and develop the system, educate users, and measure success. Consider the following questions:
    • Does the organization already have a knowledge base and/or archive of past conversations that can be used for training? If not, will the vendor or public sources provide adequate training data?
    • To what extent will you want to use in-house resources for training and development versus having the vendor manage this for you? Depending on your organization, you may want to consider working with the vendor to train internal resources.
    • How important is customizability (i.e., the ability for in-house developers to tinker directly with code to make changes wherever they see fit) versus low code/no code (i.e., tools that often include a graphical user interface [GUI] and are aimed at enabling business analysts and LOB experts to develop with little to no coding expertise)? While some platforms offer both, there are also a number that focus on one of these over the other. Buyers should also be aware that so-called “low code/no code” tools may vary in terms of user-friendliness for those with no developer experience or expertise. Many vendors will offer training on these tools, where and as needed. 
  • Develop requirements. Regardless of whether you are focused on voice- or text-based channels, consider the type of knowledge, interactions, question answering, and task completion that the conversational AI application will need to handle. Important questions to ask include:
    • What languages will the platform need to support? How flexible will it need to be in moving between languages?
    • What channels of interaction are most important for users? 
    • How domain specific will the application need to be? How accurate will it need to be on domain-specific terms?
    • What other back-end systems will the application need to connect with to answer questions and complete tasks?
  • Decide what reporting capabilities you want. Consider whether and what reporting capabilities you will need to both monitor conversational AI performance and build on the capabilities of the conversational AI. Some of the buyers that IDC spoke with wished they had spent more time up front ensuring they could use reporting and analytics to capitalize on the rich conversational data generated by user interactions with conversational AI.
  • Test conversational AI for customer service in one use case, then embrace it across the entirety of your customer service operation. Conversational AI systems can provide value across a variety of use cases in the customer service domain. These systems can be costly and time consuming to develop, so it is worth considering early how you will build on initial use cases and adjust business processes to expand the reach of your conversational AI investment.
  • Educate customers and employees. For some, conversational AI applications will be a natural interface for asking questions or completing actions, but others may require some education about the benefits, limitations, and best uses of these applications. When rolling out a virtual assistant to a customer base that may be used to, for instance, communicating with a human by phone, communicate these aspects early and often.

Featured Vendor

This section briefly explains IDC’s key observations resulting in a vendor’s position in the IDC MarketScape. While every vendor is evaluated against each of the criteria outlined in the Appendix, the description here provides a summary of each vendor’s strengths and challenges.

Omilia

After a thorough evaluation of Omilia’s strategies and capabilities, IDC has positioned the company in the Leaders category in this 2021 IDC MarketScape for worldwide conversational AI software platforms for customer service. 

Omilia offers Omilia Cloud Platform (OCP) miniApps, a set of modular pretrained software services for building and deploying virtual assistants, including no-code options for business users. OCP miniApps includes prebuilt integrations to platforms such as NICE InContact and Genesys to support contact center deployments as well as pretrained models for specific industries. Omilia supports both text- and voice-based channels with 29 languages and dialects out of the box and is headquartered in Cyprus, with five additional offices in Greece, Czech Republic, South Africa, Ukraine, and Canada. It is venture backed, with $20 million in funding.

Quick facts about Omilia include the following: 

  • Year founded: 2002
  • Total number of employees: 250+
  • Total number of clients: 100+ 
  • Globalization: Omilia supports sales and deployments globally with offices in Greece, Czech Republic, South Africa, Ukraine, and Canada and with multilingual support for 29 languages and dialects.
  • Industry focus: Manufacturing, retail, transportation, utilities, telecommunications, wholesale, healthcare, financial services, and government
  • Deployment options: Omilia is a cloud-based offering but can also be deployed on premises via a perpetual or subscription license model.
  • Pricing model: The company’s pricing differs depending on the deployment type, whether cloud or on premises. Cloud is a SaaS consumption model based on the duration of each session, rounded up to the next 10-second increment, while on premises can be purchased via perpetual or subscription license.
  • Partner ecosystem: Omilia has 35+ partners including NICE, Genesys, Concentrix, Route101, and Converge One.

Strengths

  • Forward-looking features: Omilia is one of the few providers we are aware of that provides customers with tools for testing for both bias and explainability, which can be important factors for certain industries and use cases. Omilia also provides some strong prepackaged templates for industry-specific customer support use cases, all within a no-code user interface.
  • Value: The Omilia customers that IDC spoke with praised both its ROI and overall value, including a high-touch customer support model that provides for regular dialogue between the vendor and its customers.

Challenges

  • Staffing and growth: Omilia will need to continue to add new offices and employees, particularly in areas outside of R&D. With $20 million in funding from its most recent funding round in May 2020, Omilia should be able to focus on building out its sales, marketing, and delivery resources as needed. Specifically, Omilia may want to consider quick growth options in North America where many conversational AI applications are now being deployed, such as resellers in the communications and customer contact spaces.
  • Global market visibility: Omilia is currently in a very crowded market space, so it will need to increase its marketing and partnering activities to ensure that potential customers are aware of its products and offerings. Omilia may want to consider additional strategic partners to get its products into more customers, especially in the IVR space and also in the ecommerce space. 

Consider Omilia When

Consider Omilia when you are a midsize or large enterprise seeking a vendor with modular conversational AI services that is willing to work closely with your organization to ensure a successful deployment and ROI. Omilia is also a good choice for those looking to include support for voice-based channels, since it has a broad set of voice capabilities including speech to text and text to speech. Combined with its strong developer and dialog capabilities, Omilia’s voice-based features make it a vendor to consider as a comprehensive solution for conversational AI for customer service use cases. 

Find out more about Omilia here

Methodology

IDC MarketScape Vendor Inclusion Criteria

The criteria used for the selection of IT suppliers that were evaluated are the following:

  • The offering should be commercially available for use as a single product family or a suite of services and purchased by customers for at least one year. IDC will also consider and include new product features and capabilities introduced through the CY21 as part of vendor strategy evaluation. In addition, IDC will consider these features as part of its capabilities evaluation if there is sufficient customer adoption and use for IDC to properly evaluate them. 
  • It must have the ability to develop conversational AI services that organizations can deploy for customer service and contact center use cases. 
  • The product must have at least 50 customers that have used this solution/service in production in CY20.
  • The product must be offered and available on a worldwide basis.
  • The offering must include capabilities and APIs for creating, developing, and deploying conversational AI solutions for customer service. 
  • The ideal offering should include the following capabilities: 
    • Support multiple channels.
    • Offer multilingual support.
    • Offer customized language/dialog support.
    • Integrate with enterprise applications.
  • It must have achieved at least $10 million in software revenue from the product/service in CY20.

Reading an IDC MarketScape Graph

For the purposes of this analysis, IDC divided potential key measures for success into two primary categories: capabilities and strategies. 

Positioning on the y-axis reflects the vendor’s current capabilities and menu of services and how well aligned the vendor is to customer needs. The capabilities category focuses on the capabilities of the company and product today, here and now. Under this category, IDC analysts will look at how well a vendor is building/delivering capabilities that enable it to execute its chosen strategy in the market.

Positioning on the x-axis, or strategies axis, indicates how well the vendor’s future strategy aligns with what customers will require in three to five years. The strategies category focuses on high-level decisions and underlying assumptions about offerings, customer segments, and business and go-to-market plans for the next three to five years.

The size of the individual vendor markers in the IDC MarketScape represents the market share of each individual vendor within the specific market segment being assessed. 

IDC MarketScape Methodology

IDC MarketScape criteria selection, weightings, and vendor scores represent well-researched IDC judgment about the market and specific vendors. IDC analysts tailor the range of standard characteristics by which vendors are measured through structured discussions, surveys, and interviews with market leaders, participants, and end users. Market weightings are based on user interviews, buyer surveys, and the input of IDC experts in each market. IDC analysts base individual vendor scores, and ultimately vendor positions on the IDC MarketScape, on detailed surveys and interviews with the vendors, publicly available information, and end-user experiences in an effort to provide an accurate and consistent assessment of each vendor’s characteristics, behavior, and capability.

Market Definition

Conversational artificial intelligence (AI) refers to product/services that are used to develop conversational solutions, such as chatbots or voice assistants, which users can talk to via a text- and/or voice-based interface. They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and/or text inputs and translating their meanings across various languages. Conversational AI products/services are used by organizations to create solutions that can communicate like a human by recognizing speech and/or text, understanding intent, deciphering different languages, and responding in a way that mimics human conversation. This evaluation is focused on those conversational AI platforms that can create conversational AI applications for customer service–related use cases.

Related Research

  • IDC MarketScape: Worldwide General-Purpose Conversational AI Platforms 2021 Vendor Assessment (IDC #US47354421, October 2021)
  • Worldwide Conversational AI Tools and Technologies Forecast, 2021–2025 (IDC #US48051121, July 2021)
  • Worldwide Conversational AI Tools and Technologies Market Shares, 2020: Conversational AI Ramps Up (IDC #US47993321, June 2021)
  • Creating and Deploying Conversational Artificial Intelligence Interfaces (IDC #US47571221, April 2021)
  • IDC Market Glance: Conversational Artificial Intelligence Technologies, 1Q21 (IDC #US47540221, March 2021)
  • IDC PlanScape: Conversational Artificial Intelligence (IDC #US47354821, March 2021)
  • How Important Are Voice-Based Interfaces for Contactless Experiences in the Era of COVID-19? (IDC #US46855320, September 2020)
  • Conversational AI in the Era of COVID-19 (IDC #US46212119, April 2020)
  • Smart Assistants: Moving Digital Assistance and Worker Augmentation from the Consumer to the Enterprise (IDC #US45674319, December 2019)

IDC MarketScape: Worldwide Conversational Artificial Intelligence Software Platforms for Customer Service 2021 Vendor Assessment