Even before the pandemic caused long wait times to reach an agent, there was growing consumer interest in using self-service to resolve questions and issues. Now, a Gartner survey conducted in 2021 shows that 71% of customers prefer to resolve their issues without having to contact customer service1.
Self-service can be a win-win for companies and their customers. Effortless self-service experiences increase digital adoption and boost customer satisfaction and Net Promoter Scores, while deflecting interactions from contact center agents.
Yet, many companies have failed to deliver on the benefits of self-service. Customers still find it difficult and time consuming to get helpful, relevant answers across existing web self-service, knowledge management and web content management solutions. In fact, a Gartner survey in 2020 reported that only 13% of customers are fully contained in self-service2. That means customers must often start over in another channel to get the assistance they need, creating an even more frustrating experience.
Given the past failures in self-service and current contact center challenges, it’s more important now than ever for customer experience and contact center leaders to embrace conversational artificial intelligence (AI) for human-like, self-service interactions. With an intuitive, conversational experience, companies can improve self-service completion rates, enhance the customer experience and reduce contact center volumes and cost.
This guide can help you understand the features and capabilities you should be
looking for in a conversational self-service solution.
What you’ll learn in this guide
The difference between simple chatbots and intelligent virtual assistants
How to create the business case for self-service
Whether it makes sense to build an intelligent virtual assistant yourself
Essential capabilities in a conversational self-service solution
Why a conversational automation platform is important
The difference between Traditional Chatbots and an Intelligent Virtual Assistant
Any discussion about conversational self-service needs to begin by addressing the questions around chatbots and their relative success or failure for self-service.
Traditional chatbots are typically simple, rule-based self-service tools that follow a predefined workflow and are tightly scripted. Usually text-based only, the primary use case is to help customers get quick answers to frequently asked questions without having to speak to an agent.
As a first-generation technology, chatbots had a role to play in introducing customers to guided self-service. However, they inherently have drawbacks and limitations in terms of their functionality and user friendliness. And chatbots are typically siloed from the rest of the customer experience, so if customers switch channels to get the help they need, they are forced to start their journey over again.
Fast forward nearly a decade. Today’s intelligent virtual assistants (IVAs) built using advanced conversational AI are in a different class altogether than traditional chatbots. A conversational IVA can deliver a human-like experience, simulating human conversations and delivering frictionless experiences in multiple channels, including text and voice. Multimodal capabilities allow an IVA to combine inputs via text, voice and touch (on a screen) with the ability to process data from various additional sources, such as images, videos, tables, maps and more.
All of this means that conversational IVAs can assist customers with far more than getting answers to FAQs, and they can do so in a user-friendly, human-like way. These tools can engage customers for routine journeys across their channel of choice, helping them with requests such as:
IVAs can also automatically and seamlessly transfer higher-need inquiries — together with context, intent and other AI-obtained information — to agents for more personalized care and handling.
Making the Business Case for Conversational Self-Service
Companies that implemented traditional chatbot capabilities typically focused on call deflection as the primary metric for success, often to the detriment of other important outcomes, such as customer satisfaction, Net Promoter Score (NPS) and agent experience, among others. Today’s conversational IVAs deliver on the operational efficiencies of self-service without sacrificing the customer experience.
In fact, with the right conversational IVA, contact center leaders can achieve measurable, sustainable improvements in:
To begin creating your business case for investing in a conversational IVA, consider the following use cases, questions to ask to uncover specific pain points and related metrics, and the benefits your company can anticipate.
Can you create your own IVA in house?
With the availability of open source chatbot platforms and conversational AI toolkits, your company may be considering taking a do-it-yourself approach to automating self-service. While it’s possible to build your own traditional chatbot, most companies will struggle to create a fully functional conversational IVA using open source or AI frameworks.
Choosing an off-the-shelf conversational IVA solution that is customizable by non-technical business users will almost always be faster, more cost effective and deliver greater return on investment than taking a DIY approach.
That’s because building and integrating a conversational IVA capability from scratch demands technical expertise and experience, as well as an ongoing development program and resources to optimize machine learning and implement new functionality. Your organization may have some or all of the technical resources required in house; but before you decide, consider the following:
Evaluating a Conversational Self-Service Solution
Once you’ve established the use cases and business case for conversational self-service, it’s time to search for the right solution. To deliver a human-like, conversational self-service experience, you’ll need to look for an IVA that offers the following core technologies and capabilities.
Maximizing Business Value with a Complete Conversational AI Platform
Applying real-time conversational AI across the entire customer journey — not just self-service — can help your company realize far greater returns and strategic business outcomes than with siloed solutions. As part of your evaluation of conversational self-service solutions, consider whether the IVA is part of a broader platform of AI-powered capabilities.
With a platform approach to conversational AI, your company can create the operational backbone for driving contact center transformation. For best-in-class transformational results, look for an enterprise-grade conversational AI and automation platform that offers the following capabilities:
Effortless self-service experiences are essential for improving customer satisfaction and Net Promoter Scores, while deflecting interactions from the contact center. IVAs built on a conversational AI platform deliver a human-like, easy-to-use and multimodal
self-service interaction that improves completion rates, enhances the customer experience and reduces contact center volumes and cost.
Choosing the right solution starts with defining the use cases for your company, creating a solid business case, understanding the capabilities you will need and carefully evaluating your options. We’re here to help as you take the next step in your conversational self-service journey.
1. “Younger Generations Increasingly Self-Serve Through Non-Company Digital Channels,” Deb Alvord, Smart Customer Service, May 2021
2. “Enable Customer Self-Service to Deliver Better Support,” Gartner, 2020