6 steps to successful conversational design for chatbots
As anyone who has navigated through a complex interactive voice response system knows, it’s time for a different approach to voice assistants. Customers now demand conversational experiences that demonstrate an understanding of their needs and that empower them with the service they need, when and where they need it.
Fortunately, artificial intelligence and natural language understanding can transform previously frustrating customer service use cases into opportunities to foster engagement and loyalty.
How do you build good conversations that meet your users’ needs and provide the best possible customer experience? Let’s dive into the principles of conversational design.
Conversational design starts with understanding the user journey. The design process takes six main steps.
1. Question collection and understanding utterances through user research
In the first crucial step, you’ll need to collect your users’ frequently asked questions. Resist the urge to anticipate what your users might ask. Instead, train your AI assistant on what your users actually ask on a regular basis.
From there, plan for how your users will speak. Teach your virtual assistant the relevant shorthand, slang, acronyms, and all the other ways your users already communicate. You don’t have to provide every possible utterance. Just give the system enough examples of real human conversations to capture the typical ways a user expresses key concepts.
2. Ground truth mapping and intent clustering
Ground truth mapping allows you to align action to and provide clarity on “like concepts” your customers are likely to reference when engaging a conversational AI solution. This entails grouping phrases with the same meaning (intent). As a rule of thumb, make sure you have at least 10 versions (“utterances”) of a question for each intent.
For example, a user who says: “I’m frustrated; I haven’t been able to login into the online billing system,” can be mapped to the intent Password Reset, which could trigger a corresponding action.
3. Designing the dialogue
Designing your AI assistant’s dialogue involves customizing the words, phrases, and Q&A that make up the user experience.
Designing the dialogue can be described in terms of three P’s.
- Personality: The tone of the AI assistant and how that informs interactions.
- Positioning: The purpose of the dialogue: Does it inform or take action for a user?
- Proactivity: Defines how much your AI assistant leans forward and directs users versus sitting back and letting the user guide the experience.
4. Crafting the conversational flow
What steps do you want your users to take as a result of dialog? Conversational flow leads them in the right direction.
To begin, think about your outcome. Where do you want customers to go? What do you want them to achieve? Understanding that will inform the rest of the process.
To start a dialog, welcome customers and tell them what kinds of questions the AI assistant can answer for them.
Next, guide users throughout the experience. For example, you might offer several actions to choose from through multiple choice questions.
To finish this step, think about how to end the flow. You may want to transfer customers to a human agent, or end the conversation by saying goodbye.
5. Designing responses
You can design responses to make your virtual assistant’s interactions feel natural. Adjusting for tone, restating the intent, and introducing variation in the conversation all can help your users stay engaged.
At the same time, make sure your answers stay concise so that users can get the answers they need quickly. Inject personality into your AI assistant, making it more engaging, intelligent, and even fun, without asking your users to read a novel.
6. Continuous learning
Finally, build in continuous learning functionality to ensure that your virtual assistant gains capabilities as your business develops. You will want to keep your conversational interfaces up-to-date on any business and legal changes that will impact customer service, for example.
You should also monitor human interaction patterns. How your users interact will give you a lot of insight into how to update your AI assistant to make it more user friendly and helpful.
Along with all the benefits of conversational design come some potential pitfalls. You should avoid:
- Failing to leverage representative data
- Trying to solve every problem at once
- Failing to establish success criteria
- Underestimating the time needed to train your bot
- Lacking vision and alignment in your organization
- Forgetting about UX design and visual design
Now that you’re armed with the keys to success for a natural conversation for your voice user interface, you’re ready to create an amazing customer experience to meet your business needs.