Do It Fluid: Innovation in Smart Conversational Services Through the Flow Design Approach

Do It Fluid: Innovation in Smart Conversational Services Through the Flow Design Approach

John Knight, Rachel Jones, Deniz Sayar, Damian Copeland, Daniel Fitton
Copyright: © 2020 |Pages: 21
DOI: 10.4018/978-1-7998-2112-0.ch012
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This chapter draws on practical experience in designing, delivering, operating, and innovating conversational services. The article summarises the current context for these distinctively new kinds of services and provides an overview of the relevant technologies and common platforms used in commercial service production. The chapter explores the broader commercial context for smart voice-oriented services and provides an applied framework to aid service innovation. The two concluding parts move into service production, outline a grounded design approach (FLOW) for maximising service flow, and discuss future research directions, specifically how design anthropology can help in radical service innovation.
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Service Technology Context

Speech interaction is nothing new. It is a mode of interaction that has been around for many decades and has a history that can be traced back to the end of the Second World War. The Turing Test (1950) is an early and critical milestone in conversational interaction. Likewise, voice-based products are not wholly new. Indeed, a range of conversational agents have been available commercially for some time, with voice becoming a popular way of interacting with Virtual Private Assistants (VPAs).

VPAs are offered by a range of service providers. This is often via proprietary platforms, technologies and products, including Microsoft’s Cortana, Google Assistant, Amazon Alexa etc. These VPAs enable voice interaction with a conversational agent that uses human conversation as a metaphor for interaction. Applications of this kind include some familiar product archetypes including dictation software, in-car satellite navigation systems, telephony call-routing and automation and, more recently, speech-enabled IoT, speech-enabled web-chat and human-like conversational bots. Rather than being truly conversational, many of these applications are tightly constrained and highly task-oriented in nature (Clark et al., 2019b), with users requesting the proxies to execute tasks on their behalf. Henceforth, for consistency, the term agent is used to describe human actors within a service in this article. ‘Agent’ connotes a role beyond constrained notions of the ‘user’ and ‘operator’ and thus accounts for discretionary use and value co-creation.

Key Terms in this Chapter

Wizard of Oz Studies: A research method in which participants interact with a voice-based interface, that is enacted by a human proxy. This kind of role-playing allows conversational content to be tested and iterated on the fly.

Card Sorting: A research method based on subject’s categorising items in either closed or open sorts. The grouping and naming of items elicits tacit-level knowledge about the domain in question. Applications include information architecture testing.

Service Design: A human-centred, collaborative, and holistic approach to developing new services or improving existing ones. This is achieved primarily through evidencing (blueprinting service touchpoints) and co-design (see below) within a use-centred design methodology.

Co-Design: A design process, where deliverables are produced, throughout the project lifecycle, by the collaborative efforts of designers and stakeholders. This work is facilitated and, usually occurs via workshops.

Design Anthropology: An innovation methodology, built on ethnographic principles, that speculates about the future through introducing collaboratively developed prototypes into social settings. Extending the remit of participatory design, this approach is not only technology agnostic, but also independent of predefined modalities of interaction and even whether the outcome is a product, service or experience.

Service Flow: An aggregated measure of service quality. Service flow is based on value-in, exchange, use, experience and context data pertaining to a specific service.

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