One-Voice Strategy for Customer Engagement

Singh, Jagdip; Nambisan, Satish; Bridge, R. Gary; Brock, Jürgen Kai‐Uwe

doi:10.1177/1094670520910267

Cited by 55 publications

(43 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Feeling AI can be used to enhance interaction and engagement. For example, service robots can easily do surface acting (Wirtz et al 2018), and "one-voice" AI can enhance customer engagement by integrating various interfaces involved in a customer's journey (Singh et al 2020). At the feeling level, various embodied robots are used to engage customers and optimize their experience.…”

Section: Place (Convenience)mentioning

confidence: 99%

A strategic framework for artificial intelligence in marketing

Huang

Rust

2020

J. of the Acad. Mark. Sci.

650

289

View full text Add to dashboard Cite

The authors develop a three-stage framework for strategic marketing planning, incorporating multiple artificial intelligence (AI) benefits: mechanical AI for automating repetitive marketing functions and activities, thinking AI for processing data to arrive at decisions, and feeling AI for analyzing interactions and human emotions. This framework lays out the ways that AI can be used for marketing research, strategy (segmentation, targeting, and positioning, STP), and actions. At the marketing research stage, mechanical AI can be used for data collection, thinking AI for market analysis, and feeling AI for customer understanding. At the marketing strategy (STP) stage, mechanical AI can be used for segmentation (segment recognition), thinking AI for targeting (segment recommendation), and feeling AI for positioning (segment resonance). At the marketing action stage, mechanical AI can be used for standardization, thinking AI for personalization, and feeling AI for relationalization. We apply this framework to various areas of marketing, organized by marketing 4Ps/4Cs, to illustrate the strategic use of AI.

show abstract

Section: Place (Convenience)mentioning

confidence: 99%

A strategic framework for artificial intelligence in marketing

Huang

Rust

2020

J. of the Acad. Mark. Sci.

650

289

View full text Add to dashboard Cite

show abstract

“…Our third paper titled "One-Voice Strategy for Customer Engagement" by Singh et al (2021) develops a framework of capabilities that enable firms to operate with "one voice" to deliver seamless, reliable interactions across (e.g., RPA, ML, DL) interfaces in a customer journey. The framework integrates (a) service interaction space (i.e., the association of devices, interfaces, interactions, and journeys); (b) learning/ coordination as core capabilities for generating and using intelligence to enhance CE; and (c) one-voice strategy to configure learning/coordination capabilities to meet the conditions of fitness and equifinality for effective CE.…”

Section: Articles Presented In This Issuementioning

confidence: 99%

Rise of the Machines? Customer Engagement in Automated Service Interactions

Hollebeek

Sprott

Brady

2021

Journal of Service Research

128

View full text Add to dashboard Cite

Artificial intelligence (AI) is likely to spawn revolutionary transformational effects on service organizations, including by impacting the ways in which firms engage with their customers. In parallel, customer engagement (CE), which reflects customer interactions with brands, offerings, or firms, has risen to the top of many managers’ strategic wish lists in the last decade. However, despite literature-based advances made in both areas, AI and CE are largely investigated in isolation to date, yielding a paucity of insight into their interface. In response to this gap, this Special Issue offers a pioneering exploration of CE in automated or AI-based service interactions. Our editorial first reviews AI’s Industry 4.0 underpinnings, followed by an important AI typology that comprises robotic process automation (RPA), machine learning (ML), and deep learning (DL) applications. We then offer a high-level synopsis of existing CE research, followed by the development of a set of integrative propositions of CE in automated service interactions. Next, we introduce the Special Issue papers, which feature particular RPA, ML, or DL applications. We conclude with an overview of further research avenues in this growing area, which has the potential to develop into a powerful service research substream in the coming years.

show abstract

“…Since then, the journal has also kept up a relatively steady stream of CE articles (e.g., Verleye et al, 2014;Chandler and Lusch, 2015;Donthu et al, 2020b), as illustrated by a further recent (Feb 2021) Special Issue on CE in Automated Service Interactions (e.g., Xiao and Kumar, 2021;Singh et al, 2021). Moreover, the Journal of Product & Brand Management ranks third in terms of its published number of CE articles, and fourth in terms of its CE-based citations (e.g., France et al, 2016;Dessart et al, 2015;Hollebeek and Chen, 2014).…”

Section: Major Ce-publishing Journalsmentioning

confidence: 99%

Fifteen years of customer engagement research: a bibliometric and network analysis

Hollebeek

Sharma

Pandey

et al. 2021

JPBM

108

View full text Add to dashboard Cite

Purpose In recent years, customer engagement (CE) with brands, which has been shown to yield enhanced firm sales, competitive advantage and stock returns, has risen to occupy a prominent position in brand management research and practice. Correspondingly, scholars have explored CE’s conceptualization, operationalization and its nomological networks as informed by different theoretical perspectives. However, in spite of important advances, the knowledge structure of the overall corpus of CE research remains tenuous. Therefore, the purpose of this paper is to explore the intellectual structure of CE research. Design/methodology/approach Based on this gap, this study deploys bibliometric and network analysis to map CE’s literature-based landscape. Using bibliometric analysis, important CE-publishing journals, authors and influential CE articles (2005–2020) are uncovered. Using network analysis, prominent CE themes are also unearthed. Findings The results document key CE-publishing journals and authors and their respective contributions to the literature. Five CE themes are also identified, including CE measurement/methods, online CE, CE’s value co-creating capacity, CE conceptualization and customer/consumer brand engagement. Further, an agenda for future CE research is provided based on the presented network analysis results. Practical implications The reported findings generate important implications for brand managers. For example, the identified critical role of online (vs offline) CE offers a range of strategic opportunities, as outlined. Originality/value This paper offers a pioneering bibliometric and network analysis of the CE literature, thus mapping the field. From the identified CE themes, important avenues for further CE research are also identified.

show abstract

One-Voice Strategy for Customer Engagement

Cited by 55 publications

References 58 publications

A strategic framework for artificial intelligence in marketing

A strategic framework for artificial intelligence in marketing

Rise of the Machines? Customer Engagement in Automated Service Interactions

Fifteen years of customer engagement research: a bibliometric and network analysis

Contact Info

Product

Resources

About