Chatbots or voicebots, also called conversational agents, simulate human interactions with customers and enable intelligent, interactive voice or text conversations with customers to support acquisition or servicing activities. They are typically used by industries with large customer interaction volumes (such as financial services, telecom and utilities) as well as outsourcing providers that integrate them into their contact center offering.

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Conversational solutions usually encompass three types of software with varying degrees of automation. First, live solutions are web-based chats with a human agent offering in-depth customer engagement on select, complex or sensitive topics. They can also be complemented by automated routing solutions.

Second, rule-based bots respond to interactions based on specific, predefined rules. Similar to a phone routing system, users choose from a fixed menu of options to interact with the bot. Users get the convenience of interacting with a business through text, but interaction remains simple.

Third, artificial intelligence-based chatbots and voicebots use machine learning to improve interaction patterns, and natural-language processing to recognize and process human speech.

In the past few years, consumer behaviors and expectations have shifted significantly. Many consumers have moved beyond the branded website and the native mobile application and expect an integrated mesh of touchpoints across visual, text and voice channels. In addition, the digital landscape has shifted from web-based content to mobile-first experiences.

Voice is taking a major role to change digital interaction models. Rapid adoption of voice interaction platforms and engagement, with intelligent virtual assistants through voice or text, suggest that the ability to deliver conversational experiences to customers will soon become a high priority for companies. 

The growing use of voice-based platforms such as Amazon Echo and Google Virtual Assistant, along with embedding voice interaction capabilities in mobile devices, will spur demand for digital conversations as people spend more time with microphones activated without touch. The availability of smarter ear buds and watches will accelerate the trend. Voice and ambient computing capabilities may create new sources of delight, just as the mobile channel did over the past decade. Companies that aim to become experience leaders in this environment should start developing their conversational strategy and capabilities now.

How companies will manage the digital conversation with customers

Conversational use cases are emerging in two broad groups: basic enablement and humanistic interactions.

Basic enablement use cases create conversational voice-based solutions for routine iterations. Externally facing examples include:

• Customer service. Virtual agents (VAs) designed to support general customer service inquiries, and accessible via multiple digital touchpoints, reduce agent-managed phone calls.
• Sales. VAs can be designed to offer sales support to customers and invoked at the point of sale.
• Marketing. VAs can also assist advertising or marketing campaigns.

Internally facing examples include:

• Human resources. VAs designed to automate routine questions and queries coming into HR cover areas such as vacation time, entitlements, hour tracking, overtime pay and workplace rules.
• IT service desk. VAs can automate parts of the IT service desk to more quickly and effectively solve routine problems or reduce the need for IT support staff.
• Sales support. VAs support the salesforce throughout the sales cycle.
• Enterprise software front ends. VAs serve as conversational interfaces, making an alternative user interface for enterprise software.

The evolution of conversational use cases will likely follow a common trajectory. First, firms will seek to replicate experiences available through other touchpoints. Second, use cases will develop based on the unique attributes of modalities or platforms.

Ultimately, use cases will move to more humanistic, personalized interactions. These involve the ability to approximate human interactions with a greater level of personal context. At the highest level, voice agents will understand the context of an interaction, detect emotion, respond with empathy and personalize a response. This would be the virtual equivalent of a barista or bartender knowing your routine order and preferences.

Key considerations for managing digital conversations

• Conversational strategy. Companies need to develop a strategy for using conversational tools to support the digital ambition. How, for instance, will branding be brought to life conversationally? Successful deployment hinges on establishing the right use cases for conversational tools, designing the operating model for delivery and continuous testing and learning.
• New competencies. To address evolving customer expectations, firms must develop new competencies to become aware of contexts, offer the ability to use multiple channels and provide seamless handovers between different digital channels. A seamless transition from bots to human agents without losing context is also critical.
• Integration capabilities. The conversational solution should integrate with other systems, such as customer relationship management, analytics solutions, help-desk ticket tracking, contact-center routing software, interactive voice response, other bots or security solutions.