Advanced digital capabilities in Artificial Intelligence (AI) and Natural Language Processing (NLP) have altered how people interact with data—the widespread adoption of voice platforms such as Amazon Alexa and Google Assistant, as well as messaging platforms like Facebook Messenger and Slack, means humans are interacting increasingly more with technology through conversational interfaces (CI) instead of actual people.
But even as technological challenges of CI lessen, newer, broader challenges are popping up: How can humans interact with robots in a way that doesn’t diminish our own human experience?
West Monroe takes a human-centered design approach in the work we do to offer clients a framework for the future. We’ve seen a pattern with emerging technologies in the past. In recent history, with mobile apps—and both websites and physical products before that—there is a habit of letting technology lead the experience. But just because you build it, doesn’t mean they will come. It’s difficult to demonstrate the value that new technology will have on broad business initiatives without wide customer understanding. Organizations must start with the human experience: Identify a problem or need in a customer’s interaction with the business, and then figure out how we can best leverage technology to achieve a lasting solution.
Users don’t care that they’re interacting with a conversational interface or that you’re using the latest technologies. They care that their needs are being met—quickly, reliably, and with as little effort on their part as possible.
Given those priorities, we’ve produced 10 best practices to follow when approaching a conversational interface design. Guided by human-centered design methods, these best practices will help provide a seamless user experience to meet your customers’ needs:
Scope: Bots can't do everything—but they can do some things really well
Look for areas where the level of technological capabilities aligns well with use case needs. Areas where bots can be especially effective include onboarding, transactions, task completion aid, quick queries, brand promotion, gamification, frequent customer inquiries, and market research. Identify which is most important now and begin with a focus on that area to gain the most traction from users.
Challenges: Understanding context is critical to success
Something humans are very good at and bots struggle with is understanding an interaction’s bigger picture. But if bots are going to aid in effectively solving problems, they must be aware of and act appropriately for the context of use. Organizations must design bots to establish empathy and trust with users by being transparent with their capabilities—while giving users a sense of security through authentication.
Channel Choice: Meet users where they already are (or use a channel that reinforces the company’s other business initiatives)
One of the first decisions in chatbot design? Determining which platform to use. The way we speak is much different than the way we write. Even within that, mediums like text message, email, and Facebook all have their own rules of communication. The idiosyncrasies of the channel’s unspoken rules must be accounted for; for instance, consider the widespread use of abbreviations over SMS, emoji in Slack and Messenger, and full sentences with salutations over email. Having a multi-channel chatbot that's effective requires redesigning the conversation flow and structure to appropriately adapt.
Personality: Chatbots are more than a persona, they need a fully developed personality to be effective
People will naturally humanize bots, so an opportunity exists for businesses to be intentional and control this narrative. Determine upfront who the bot is to enhance overall brand strategy, engage with consumers in familiar ways, and maintain consistency. It may help to give your bot an archetype first and build from there (e.g. a helpful teacher, a knowledgeable advisor, the friend who listens). This will directly impact the bot's conversational style and will govern the response type, messaging, and chosen platform.
Introductions: Bots should always introduce themselves and begin with a simple question to engage users
Hook users with short, simple messages that either ask a question or inform the user about the bot's capabilities. Start simple and suggest capabilities through intuitive examples versus taking time to teach the users what to say in an unnatural menu-style format listing out everything.
Dialogue structure: Follow natural conversational patterns, anticipate user intent, and account for user variability in speech
A bot should mimic natural dialogue, including turn-taking and the ability to provide enough novelty and variability with responses to maintain engagement. Begin by identifying the goal of each specific interaction, and then write sample conversations to map possible scenarios as if two humans were speaking.
Message length and frequency: Bots don't need to share everything at once
As with human conversations, interactions should be brief to avoid information overload and allow users time to process. Break messages into smaller pieces and prioritize the information. If written, a user should not have to scroll to read critical information. With voice, follow a natural conversation style with pauses for user responses.
Error Correction: It's OK not to have all the answers
Bots must adapt to different modes of conversation from different users—and be truthful when unable to answer requests. Users should always be asked for confirmation on critical steps, and they should be given the opportunity to fix misunderstandings. This builds trust and allows users to feel confident with the bot's capabilities. In areas where frustrations could run high, giving the user a way to interact with a human directly if needed may be essential. Don’t be afraid to be upfront about limitations.
Don't boil the ocean: Start small and be realistic about what you can achieve
Look for small proof-of-concept wins that demonstrate business value first. Use these interactions to develop reusable patterns and refine all the previous best practices mentioned to align with your users. Build on successes to take on more complex and expanded scenarios.
Test, test, test: Bot design is an iterative process and refinement should be an ongoing effort
Put users in front of the chatbot and listen to their interactions. Use transcripts to see both sides of the conversation or shadow users as they’re interacting with the bot. Note the specifics of what people say. If repetitive user missteps occur, additional conversation inputs may be needed to make the bot functional. If there are errors, is the bot able to correct or direct the user to a human to take care of their needs? Bots built with natural language processing can be trained over time, so learn from your users and include the variations they say in the testing process.
Chatbot adoption is an ever-growing concept—and rapid technological advancements are expediting that shift, making preparation critical. Leveraging these UX best practices during early stages will set your business apart and keep you well-positioned to spearhead new and expanding conversational interface technologies.