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Designing Context-Aware Chatbots for Product Configuration

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Chatbot Research and Design (CONVERSATIONS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13815))

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Abstract

Product configurators provide an interface for customizing complex products. However, large form-based configurators overwhelm many end users and are often considered expert tools. This paper therefore addresses the problem of the complexity of current product configurators. Since chatbots can respond flexibly to queries and offer a natural language interface, they have the potential to simplify the configuration process. In this paper, we present a chatbot for product configuration that we developed using the design science research approach and in collaboration with an industrial partner. We derive design principles for configurator chatbots from user interviews that relate in particular to the flexibility of the chatbot compared to a static process. These design principles were implemented in our chatbot artifact which was evaluated in an online experiment (N = 12) and compared to a baseline chatbot with an inflexible configuration process. Our results indicate that the proposed design increased dependability and configuration performance, and overall had positive effects on participants’ engagement. Thus, this study contributes prescriptive knowledge on the design of context-aware chatbots for product configuration and a novel artifact in the form of a context-aware configurator chatbot prototype.

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Author information

Authors and Affiliations

  1. Karlsruhe Institute of Technology, Kaiserstraße 12, 76131, Karlsruhe, Germany

    Tom Niederer & Daniel Schloss

  2. CAS Software AG, CAS-Weg 1 - 5, 76131, Karlsruhe, Germany

    Noemi Christensen

Authors
  1. Tom Niederer
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  2. Daniel Schloss
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  3. Noemi Christensen
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Corresponding author

Correspondence to Daniel Schloss .

Editor information

Editors and Affiliations

  1. SINTEF, Oslo, Norway

    Asbjørn Følstad

  2. University of Amsterdam, Amsterdam, The Netherlands

    Theo Araujo

  3. CERTH-ITI, Thessaloniki, Greece

    Symeon Papadopoulos

  4. Durham University, Durham, UK

    Effie L.-C. Law

  5. University of Edinburgh, Edinburgh, UK

    Ewa Luger

  6. University of Agder, Grimstad, Norway

    Morten Goodwin

  7. University of Oslo, Oslo, Norway

    Petter Bae Brandtzaeg

Appendix

Appendix

1.1 Questions Asked in the Semi-structured Interviews

Status Quo

  • “How often is the product configurator used by which user groups?”

  • “What are the goals of a customer when configuring the product?”

  • “What proportion of the configurations that have been started will be completed?”

Problem identification

  • “For what reasons do users cancel a product configuration?”

  • “How is the feedback on the product configurator?”

  • “What complaints or negative feedback about the configurator are there?”

  • “What are the hurdles in the current configuration process?”

Requirements

Abstract requirements

  • “What are frequently expressed customer requirements?”

  • “What are the relevant properties for you that a configurator has to implement?”

  • “How can intuitive operation or a pleasant process flow be achieved?”

Concrete requirements for configuration chatbot

  • “In your opinion, how would a text-based chatbot have to proceed in order to to enable a pleasant configuration process?”

  • “What abilities of the chatbot would be desirable”

  • Opt.: negative questions in cases of insufficient feedback

(translated from German).

1.2 Final Evaluation

Table 3. Final experiment groups
Full size table
Table 4. User-related constructs
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Table 5. Performance related metrics
Full size table

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Niederer, T., Schloss, D., Christensen, N. (2023). Designing Context-Aware Chatbots for Product Configuration. In: Følstad, A., et al. Chatbot Research and Design. CONVERSATIONS 2022. Lecture Notes in Computer Science, vol 13815. Springer, Cham. https://doi.org/10.1007/978-3-031-25581-6_12

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  • DOI: https://doi.org/10.1007/978-3-031-25581-6_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-25580-9

  • Online ISBN: 978-3-031-25581-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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