How to Design Digital Assistants?
Nina Habicht • July 31, 2019
CUI Design Learnings
I summarized the most evident facts you need to follow to create your digital assistant. Various Bestseller books and papers on chatbot development as well as my long-year-research experience were used. In general, you can use these recommendations for bots, avatars, voice interfaces but also other types of digital assistants. Start with these points to become a successful CUI designer.
1 clear onboarding phase and greeting:
Make clear to the user what he can expect from the digital assistant. For example, it should be clear what the chatbot's goal and functionality are. You can do this by offering mini-tutorials at the beginning of the conversation. This clarifies the expectations of how intelligent an assistant is and reduces the probability of a user being disappointment (Valério, Guimarães, Prates & Candello, 2017). A “capability check", i.e. a possibility to ask the assistant, in the sense of "What can you do?", should be built in (Moore, 2018).
2 personality and the branding
are declared by numerous conversational designers as the first step to start with:
•
First, think about the vision, mission, goals, and actions your CUI needs to solve.
•
Second, consider the opinion, goals, and needs of the users: What are there personas? What are their needs? pain points?
•
Third, depending on the use case and emotional level of a conversation, visualize your digital agent (Pearl, 2017). Comic-like chatbots are perceived as more likable and trustworthy (Luo, McGoldrick, Keeling, & Beatty, 2006). Photorealistic agent, called avatars tend to be higher concerning their abilities and level of intelligence (Dehn & Mulken 2000, p. 2).
•
In which context do you use the agent? In e-commerce for example, voice and text-based chatbots are more common than embodied agents. These are increasingly used in the context of games and as educational agents (Knote et al., 2018).
3
guided, contextual conversation.
Depending on whether you build a rather text-based interface or voice-first agent you need to guide your user. You can either use:
• Rich controls
(e.g. buttons, images, carousels, maps) to respond to the intentions of the user (Shevat, 2017). Of course, they limit the user’s freedom but can reduce the risk of entering something the system is not prepared to (Valério et al. 2017).
• Design contextual: The agent should remember the previous nouns ( "Peter likes apples (...)", answer with pronouns ("he" instead of "Peter") to respond more natural. Use variations for the same user intention ("Peter likes fresh fruit"). Prepare your assistant for upcoming negations ("I don't want red apples"(Jain et al., 2018)), silly user inputs or complete new requests during a conversation which are not referred to the current context.
4 assistance and repetition
The user should be able to say “I need help”. Consider all cases: The agent helps in the current context but also when the user needs to get back to an overview or start. With chatbots, use context-related global help
function via a persistent menu. At the same time, however, it should also be possible to ask for help during the conversation (Moore, 2018).
5
main functions, persistent menus
Focus on fewer functions when developping a conversational interface. Take the main functions or use cases (also intentions) and implement them consistently and sufficiently. The user should be able to go back in the conversation, easily change already entered or said inputs. The user can use a main menus to display main functions again during the chat process and react to them. This makes it possible to change messages and entries from the past, thus, change time schedules, booking entries or chosen articles.
6
humour and playfulness
are fostering a satisfactory user experience since the conversational agent is perceived as more human (Luger & Sellen, 2016, Habicht 2019). However, some agents use fun elements for error handling which – when appearing too often – are not solving the user’s problem, and are annoying for the user. Studies show that more conversational turns are generated with entertainment/gaming bots than with shopping chatbots, having less hedonistic goals (Jain, et al., 2018).
7 humour and playfulness
When building assistants think about these possible errors: A) No speech/input detected, B) Speech/input detected but not recognized, C) Recognized but wrongly handled by the system D) Incorrectly recognition. Whether an error handling is initiated by your assistant or not highly depends on: The options to continue the conversation (or break it!), presence of listening indicators (i.e. Alexa ring light, or an Avatar actively looking at you until you ask the question again).
8 avoid media breaks
Create an assistant being able to call-up a network of services, including basket, payment options, calendar, and other third-party functionalities. Assistants opening up too many external links are not optimal from a user-perspective but sometimes legally necessary (i.e. checkout, privacy, opt-in).
9 conversation exit
Your assistant should say goodbye or offer a way to finish the conversation easily.
Keep in mind that a loss of confidence and trust can be avoided with a user-friendly design. Successful examples of conversational interfaces are known to convey high levels of trust.
Nina Habicht
Founder VOICETECHHUB
Growth Hacker and Business Developer provides strategic and operational support to start-ups and companies in the development of visions and products. She holds two Masters degrees, an MAS in Business Informatics and an MSc in Strategic Management and Marketing. In Switzerland she is an expert, author and researcher in the fields of AI Design, Conversational and Voice User Interfaces as well as Chatbot & Avatars since 2011.
With over 10 years of experience, she supports various companies and industries in the fields of Digital Leadership, Strategic Management, Business Development, Web & Data Analytics, Requirements Engineering, UX-/CUI-Design, Prototyping, Communication and Digital Marketing. From 2016 to 2018, she was founder of Brainshare, an AI startup for innovation and ideation. In 2019 she founded VOICETECHHUB - a platform fostering AI Experience and Voice Tech projects and products. It also supports customers with the implementation of digital agents such as Amazon Alexa or Google Home and on-premise Conversational Interfaces.
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