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This paper aims to help challenger marketers identify and target the right customer organization.

This paper adopts a customer organization profiling route to targeting for challenger marketing that is predicated on a thematic analysis of key findings of customer organization profiles from an international case study.

This paper introduces and explains the concepts of aggressiveness to succeed, compatibility of offerings, openness to new ideas and willingness to take action (or A-C-O-W) as components of a newly developed customer organization profiling matrix for challenger marketing.

The A-C-O-W customer organization profiling matrix offers a fresh conceptual outlook for targeting customer organizations using a challenger marketing approach in the contemporary business-to-business (B2B) marketplace.

The A-C-O-W customer organization profiling matrix illuminates how challenger marketers can target the right customer organizations in the contemporary B2B marketplace.

The A-C-O-W customer organization profiling matrix is a pioneering concept for challenger marketing in B2B theory and practice.

This research aims to comprehend the factors that impact the emerging inclination of consumers toward mobile finance technology (fintech) services over banking institutions. The study focuses on users' demographics and psychographics to delineate their unique segments and profiles.

The study proposes a segmentation and profiling framework that includes variance analysis, two-step cluster analysis and pairwise statistical tests. This framework is applied to a dataset of customers using a range of mobile fintech services, specifically robo-investment, peer-to-peer (P2P) payments, robo-advisory and digital savings. The analysis creates distinct customer profile clusters, which are later validated using pairwise statistical tests based on segmentation output.

Empirical results reveal that P2P payment service users exhibit a higher frequency of usage, proficiency and intention to continue using the service compared to users of robo-investment or digital savings platforms. In contrast, individuals utilizing robo-advisory services are identified to have a significantly greater familiarity and intention to sustain engagement with the service compared to digital savings users.

The findings provide financial institutions, especially traditional banks with actionable insights into their customer base. This information enables them to identify specific customer needs and preferences, thereby allowing them to tailor products and services accordingly. Ultimately, this understanding may strategically position traditional banks to maintain competitiveness amidst the increasing prominence of fintech enterprises.

This research provides an in-depth examination of customer segments and profiles within the mobile fintech services sphere, thus giving a nuanced understanding of customer behavior and preferences and generating practical recommendations for banks and other financial institutions. This study thereby sets the stage for further research and paves the way for developing personalized products and services in the evolving fintech landscape.

Allen and Meyer’s (1990) three component model of organizational commitment is now well accepted in the study of consumer–service provider relationships (Keiningham et al., 2015). Commitment profiling is a “person-centered approach” to commitment (Meyer et al., 2012) which examines groups of individuals who share similar commitment mindsets. The purpose of this paper is to apply commitment profile methodology to the analysis of customer–firm relationships in the context of financial services.

This method was applied with customer data collected as part of a nation-wide panel study of consumer financial service relationships in Canada. In total, 428 banking customers participated in this study.

This study identified five distinct bank customer commitment profiles (fully committed, affective commitment dominant, continuance commitment dominant, moderately committed and uncommitted) that varied in both size and behaviors and intentions.

This is an exploration of commitment profiling as a technique to understand the ways in which consumers differ in terms of their commitment mindsets and behavior. It has application to a wide range of service relationships beyond financial services.

This has applications for market segmentation on the basis of customer commitment mindsets in many service sectors, but banking in particular. Since financial institutions have adopted various techniques to measure customer lifetime value (CLV), it would be appropriate to understand how various commitment profiles (segments) are linked to CLV.

While commitment profiling is a well-developed approach in understanding the nature of the firm–employee employment relationships, this is an early and exploratory attempt at applying this method in the context of a customer–financial service provider marketing relationship. This is a novel way of understanding bank customer segments in terms of their felt commitment to the financial institution with which they do business.

The authors have constructed a model which breaks down customer contact in consuming a service into six steps: search, arrival, pre‐contact, contact, withdrawal, follow‐up. They argue that this “journey” should be mapped out by service organisations and the key points carefully managed.

This paper aims to investigate the purpose, reach and effectiveness of the customer identification framework of the Financial Action Task Force (FATF).

The article draws on relevant research and documents of the FATF, the Basel Committee on Banking Supervision and the Alliance for Financial Inclusion to determine whether compliance with the standards and practices of the FATF would prevent anonymous usage of financial services.

The FATF’s identification principles, guidance and practices resulted in processes that are largely bureaucratic and do not ensure that identity fraud is effectively prevented. Strict identification requirements on the other hand may impact on financial inclusion, leaving the FATF with little leeway to raise its standards. There are potential solutions, but they are longer-term and partial in nature.

Current identification and verification practices affect the lives of millions of people around the globe. The measures are being enforced to ensure that users are appropriately identified. This article informs the debate by highlighting the weaknesses of the current approach.

Artificial intelligence (AI) technology has revolutionized customers' interactive marketing experience. Although there have been a substantial number of studies exploring the application of AI in interactive marketing, personalization as an important concept remains underexplored in AI marketing research and practices. This study aims to introduce the concept of AI-enabled personalization (AIP), understand the applications of AIP throughout the customer journey and draw up a future research agenda for AIP.

Drawing upon Lemon and Verhoef's customer journey, the authors explore relevant literature and industry observations on AIP applications in interactive marketing. The authors identify the dilemmas of AIP practices in different stages of customer journeys and make important managerial recommendations in response to such dilemmas.

AIP manifests itself as personalized profiling, navigation, nudges and retention in the five stages of the customer journey. In response to the dilemmas throughout the customer journey, the authors developed a series of managerial recommendations. The paper is concluded by highlighting the future research directions of AIP, from the perspectives of conceptualization, contextualization, application, implication and consumer interactions.

New conceptual ideas are presented in respect of how to harness AIP in the interactive marketing field. This study highlights the tensions in personalization research in the digital age and sets future research agenda.

This paper reveals the dilemmas in the practices of personalization marketing and proposes managerial implications to address such dilemmas from both the managerial and technological perspectives.

This is one of the first research papers dedicated to the application of AI in interactive marketing through the lenses of personalization. This paper pushes the boundaries of AI research in the marketing field. Drawing upon AIP research and managerial issues, the authors specify the AI–customer interactions along the touch points in the customer journey in order to inform and inspire future AIP research and practices.

The study aims to assist contractors in strategically managing customer satisfaction by applying marketing theory to housing construction. It specifically aims to investigate service quality as an input to pre‐purchase (pre‐contract) expectations in the made‐to‐order housing construction market.

A theoretical model is developed from the literature concerning the formulation of expectations during the pre‐purchase decision process. Data from 51 detailed telephone interviews with customers undertaking live housing projects are analysed using both thematic analysis and qualitative comparative analysis.

A revised model is provided, which includes a dimensionalised set of traits to suit housing construction customers. Strings of traits are then used to develop holistic customer profiles, including situations where service quality is fully present in critical pre‐purchase expectations and where it is totally absent (i.e. price and product design dominate instead).

The model and profiling technique offer a generalisable basis for contractors and others involved in housing delivery to better understand customer expectations, thus making it possible to better manage customer satisfaction.

The research contributes to new knowledge by providing a systematic means of understanding customer behaviour at a depth that is not apparent in the current body of literature. Theory is also developed in a way that has practical application, i.e. customer profiles can be used to assist daily marketing and management operations.

The purpose of this paper is to present a comprehensive picture of the innovative efforts undertaken over time to develop the digital technologies for managing the interface between supply chain management and marketing processes and the role they play in sustaining supply chain management-marketing (SCM-M) integration from an information processing point of view.

Patent analysis and actual examples are used to carry out this study. In detail, first, the authors identify the subset of enabling technologies pertaining to the fourth industrial revolution (Industry 4.0) that can be considered the most relevant for effective SCM-M integration (i.e. Industrial Internet of Things, Cloud computing, Big Data analytics and customer profiling, Cyber security). Second, the authors carry out a patent analysis aimed at providing a comprehensive overview of the patenting activity trends characterizing the set of digital technologies under investigation, hence highlighting their innovation dynamics and applications.

This research provides insightful information about which digital technologies may enable the SCM-M integration. Specifically, the authors highlight the role those solutions play in terms of information acquisition, storage and elaboration for SCM-M integration by relying on illustrative actual examples. Moreover, the authors present the organisations more involved in the development of digital technologies for SCM-M integration over time and offer an examination of their technological impact in terms of influence on subsequent technological developments.

So far, much has been said about why marketing and supply chain management functions should be integrated. However, a clear picture of the digital technologies that might be adopted to achieve this objective has yet to be revealed. Thus, the paper contributes to the literature on SCM-M integration and Industry 4.0 by highlighting the enabling technologies for the Industry 4.0 that may particularly serve for managing the SCM-M interface from an information processing perspective.

The purpose of this study is to examine the South African banks’ customer due diligence (CDD) practices in the fintech era to mitigate money laundering (ML) risks and ensure financial stability. Financial technologies have brought substantial transformations to the financial services sector. However, such technologies have exposed the sector to emerging risks that threaten the integrity and stability of the financial system globally. Before any bank–customer relationship is established, proper customer background checks must be conducted. These background checks enable financial institutions to validate information provided and ensure customers are properly risk profiled. Failure to risk profile customers could result in financial institutions being used as conduits for ML. Undoubtedly, CDD procedures are pivotal to overall anti-money laundering efforts and curbing financing terrorism in a regulatory framework.

A qualitative research approach was adopted to address the research questions of the study. Given the confidentiality associated with the financial services sector, data triangulation was used in blending mainly secondary and primary data sources. Secondary data sources used in the study were published reports available in the public domain that were corroborated with subject matter experts’ interviews.

Based on the findings of this study, it is concluded that in South Africa, technological solutions have been incorporated into CDD functions, which is now risk-based (enhanced due diligence). Also, legally, South Africa has incorporated the biometrics, integration with Department of Home Affairs and Companies and Intellectual Property Commission databases, customer consent to third-party sources with the Financial Intelligence Centre Act and the Protection of Personal Information Act.

The shift towards digital banking in South Africa results in increased data and dynamic risk profiling. This study advocates a policy shift requiring a risk-based approach to mitigating emerging ML risks (in particular digital laundering), especially in the wake of South Africa’s recent greylisting by the Financial Action Task Force.

Hungarian economy went through substantial changes in the past few decades and hypermarkets gained high popularity among customers, therefore profiling Hungarian hypermarket shoppers is essential to understand their behavior.

The paper investigates the profile of Hungarian hypermarket shoppers based on a wide questionnaire survey. In the presented research, Computer-Aided Personal Interviewing questionnaires were analyzed using multidimensional scaling and k-means clustering.

Results showed that Hungarian hypermarket shoppers regularly plan their shopping but they buy 8–9 items instead of the planned 4–5 items. However, only 25% of respondents reported the use of shopping list and in spite of the wide digital possibilities, they do not use their mobile devices neither for creating shopping list nor for checking coupons online.

This study explores the profile of Hungarian hypermarket shoppers, which may give additional information for the players of the retail environment about the customers' behavior and preferences.