More than FAQ! Chatbot Taxonomy for Business-to-Business Customer Services

Janssen, Antje Henriette Annette; Cardona, Davinia Rodríguez; Breitner, Michael H.

doi:10.1007/978-3-030-68288-0_12

Cited by 15 publications

(7 citation statements)

References 25 publications

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“…Az ügyfélszolgálat területén roppant hatékony lehet a csevegőrobotok alkalmazása, egyfajta virtuális ügynöki szereppel ruházzák fel őket a vállalatok (Janssen, Cardona és Breitner, 2021).…”

Section: Felhasználási Lehetőségekunclassified

Csevegőrobotok alkalmazása a customer service területén.

Gulyás¹

2022

Mesterséges intelligencia

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E tanulmány célja, hogy szekunder adatgyűjtés segítségével bemutassam a csevegőrobotok működését, OxIPO-modell aspektusából értelmezett tanulási folyamatát, alkalmazásának a vállalat eredményét befolyásoló hatásait. Arra is keresem a választ, hogy az Észak-alföldi régióban milyen az ügyfélszolgálat területén alkalmazott csevegőrobotok általános fogyasztói megítélése. Netnográfiai kutatás, s online kérdőív segítségével igyekeztem a csevegőrobotokkal szemben támasztott igényeket felmérni.

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Section: Felhasználási Lehetőségekunclassified

Csevegőrobotok alkalmazása a customer service területén.

Gulyás¹

2022

Mesterséges intelligencia

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“…The goal of a business is to nurture the customercompany relationship and preserve long-term deals, which becomes explicitly clear in the last stage, the post-purchase stage. This requires the B2B seller to make call-to-action pull efforts to offer the best B2C customer service experience (Janssen et al, 2021).…”

Section: What Is the Role Of Chatbots At Different Stages Of The B2b ...mentioning

confidence: 99%

“…The chatbot feature is userdriven and short-term as the customer enters the conversation with a problem or task expecting a solution proposed by the chatbot or the brand the buyer is reaching out to. This interaction between the customer and the company helps bring forward the client's needs, requirements, and emotions (Janssen et al, 2021).…”

Section: What Is the Role Of Chatbots At Different Stages Of The B2b ...mentioning

confidence: 99%

Will chatbots play a more significant role for B2B marketing in the future? Chatbots in B2B businesses

Fauser

Schmäh²,

Tran

et al. 2022

ijbass

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Digitalization has gained a foothold in our everyday lives. However, it remains to be seen what digital tools B2B companies can benefit from. During the last few years, chatbots have been on the rise and have played a more significant role in B2B marketing. Thus, this research follows a literature review to examine the current state of B2B chatbots. With this, the study will discover the buyer’s preferences for chatbots compared to sales agents and the role of chatbots in different stages of the B2B sales funnel.

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“…Considering chatbots as social actors (cf, social response theory), individuals can be expected to apply readily available learned human social scripts to interactions with a chatbot as well, especially when specific cues signal that it enacts a particular role [27,38]. Prior conceptual conversational agent studies have developed taxonomies, typologies, and classifications of different types of chatbots, for example, differentiating chatbots for domain-specific or for general-purpose use [39], for specific applications (eg, business-to-business customer services [40] and health care [41]), for different purposes [42,43], for singleor multiple-user use cases [44,45], or for specific periods [46]. However, relatively few conceptual studies to date have addressed how a chatbot can impersonate a holistic, domain-specific social role and how such a social role affects user assessments.…”

Section: Designing Engaging Health Care Chatbots With Human-like Soci...mentioning

confidence: 99%

The Effects of Health Care Chatbot Personas With Different Social Roles on the Client-Chatbot Bond and Usage Intentions: Development of a Design Codebook and Web-Based Study (Preprint)

Nißen¹,

Rüegger²,

Stieger³

et al. 2021

Preprint

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BACKGROUND The working alliance refers to an important relationship quality between health professionals and clients that robustly links to treatment success. Recent research shows that clients can develop an affective bond with chatbots. However, few research studies have investigated whether this perceived relationship is affected by the social roles of differing closeness a chatbot can impersonate and by allowing users to choose the social role of a chatbot. OBJECTIVE This study aimed at understanding how the social role of a chatbot can be expressed using a set of interpersonal closeness cues and examining how these social roles affect clients’ experiences and the development of an affective bond with the chatbot, depending on clients’ characteristics (ie, age and gender) and whether they can freely choose a chatbot’s social role. METHODS Informed by the social role theory and the social response theory, we developed a design codebook for chatbots with different social roles along an interpersonal closeness continuum. Based on this codebook, we manipulated a fictitious health care chatbot to impersonate one of four distinct social roles common in health care settings—institution, expert, peer, and dialogical self—and examined effects on perceived affective bond and usage intentions in a web-based lab study. The study included a total of 251 participants, whose mean age was 41.15 (SD 13.87) years; 57.0% (143/251) of the participants were female. Participants were either randomly assigned to one of the chatbot conditions (no choice: n=202, 80.5%) or could freely choose to interact with one of these chatbot personas (free choice: n=49, 19.5%). Separate multivariate analyses of variance were performed to analyze differences (1) between the chatbot personas within the no-choice group and (2) between the no-choice and the free-choice groups. RESULTS While the main effect of the chatbot persona on affective bond and usage intentions was insignificant (P=.87), we found differences based on participants’ demographic profiles: main effects for gender (P=.04, ηp2=0.115) and age (P<.001, ηp2=0.192) and a significant interaction effect of persona and age (P=.01, ηp2=0.102). Participants younger than 40 years reported higher scores for affective bond and usage intentions for the interpersonally more distant expert and institution chatbots; participants 40 years or older reported higher outcomes for the closer peer and dialogical-self chatbots. The option to freely choose a persona significantly benefited perceptions of the peer chatbot further (eg, free-choice group affective bond: mean 5.28, SD 0.89; no-choice group affective bond: mean 4.54, SD 1.10; P=.003, ηp2=0.117). CONCLUSIONS Manipulating a chatbot’s social role is a possible avenue for health care chatbot designers to tailor clients’ chatbot experiences using user-specific demographic factors and to improve clients’ perceptions and behavioral intentions toward the chatbot. Our results also emphasize the benefits of letting clients freely choose between chatbots.

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More than FAQ! Chatbot Taxonomy for Business-to-Business Customer Services

Cited by 15 publications

References 25 publications

Csevegőrobotok alkalmazása a customer service területén.

Csevegőrobotok alkalmazása a customer service területén.

Will chatbots play a more significant role for B2B marketing in the future? Chatbots in B2B businesses

The Effects of Health Care Chatbot Personas With Different Social Roles on the Client-Chatbot Bond and Usage Intentions: Development of a Design Codebook and Web-Based Study (Preprint)

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