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In the age of digital media, customers have access to vast digital information sources, within and outside a company's direct control. Yet managers lack a metric to capture customers' cross-media exposure and its ramifications for individual customer journeys. To solve this issue, this article introduces media entropy as a new metric for assessing cross-media exposure on the individual customer level and illustrates its effect on consumers' purchase decisions.

Building on information and signalling theory, this study proposes the entropy of company-controlled and peer-driven media sources as a measure of cross-media exposure. A probit model analyses individual-level customer journey data across more than 25,000 digital and traditional media touchpoints.

Cross-media exposure, measured as the entropy of information sources in a customer journey, drives purchase decisions. The positive effect is particularly pronounced for (1) digital (online) versus traditional (offline) media environments, (2) customers who currently do not own the brand and (3) brands that customers perceive as weak.

The proposed metric of cross-media exposure can help managers understand customers' information structures in pre-purchase phases. Assessing the consequences of customers' cross-media exposure is especially relevant for service companies that seek to support customers' information search efforts. Marketing agencies, consultancies and platform providers also need actionable customer journey metrics, particularly in early stages of the journey.

Service managers and marketers can integrate the media entropy metric into their marketing dashboards and use it to steer their investments in different media types. Researchers can include the metric in empirical models to explore customers' omni-channel journeys.

Understanding the customer has been the focus of attention of businesses and academia for many decades. Starting in 1960s, complex buyer behavior models developed by Nicosia, by Howard and Sheth (1969), were followed by Engel, Blackwell and Miniard in 1978 (Engel, Blackwell, & Miniard, 1990) to understand the buying process, shaping the thoughts today about consumers’ experiences in an omnichannel world. Interest in customer perceptions and expectations (Parasuraman, Berry, & Zeithaml, 1991), SERVQUAL (Parasuraman, Zeithaml, & Leonard, 1985) and SERVPERV (Cronin & Taylor, 1994) moved the academia to discuss the relationship marketing (Morgan & Hunt, 1994; Parvatiyar & Sheth, 1999; Peterson, 1995; Sheth & Parvatiyar, 1995). Wilson’s model (1995) of buyer–seller relationships extended the former models with additional concepts like social bonds, comparison level of alternatives, power roles, technology, structural bonds and cooperation as influencers on relationship development stages. His emphasis reflects a high relevancy in the omnichannel world of customers’ interactions today. Winer (2001), a pioneer to discuss the customer relationship management focused on a database to know about customers’ purchase history and interests. The millennium look at customer lifetime value is again relationship focused. For Fader, Hardie, and Lee (2005) rather the long-term focus of the consumer value and actions are important to understand the loyalty and nonlinear nature of relations. While Reinartz and Kumar (2003) focused on profitable customer lifetime and customer heterogeneity, Verhoef (2003) analyzed the impact of customers’ relationship perceptions and relationship marketing instruments on both customer retention and customer share development. The customer-centric thinking was first discussed by Grönroos (2006) within a new definition of marketing. The service dominant logic (Vargo & Lusch, 2008) resulted in the next highlight, the co-creation of value with customer involvement and customer advisory (Güngör, 2012; Güngör & Bilgin, 2011; Messner, 2007) empowering the customers and giving them the control over the supplier networks. Different factors will be influential at different stages of the buying process of customer clusters. The Web- and non-Web-based customer-centric measures can be multifold. Andersson, Movin, Mähring, Teigland, and Wennberg (2018) and Bank (2018) emphasize the importance of technology readiness focus throughout the customer–supplier journey. The question to be answered is, to which extent the empowered customers and the suppliers of this age are ready to adopt, embrace and finally use new technologies in the omnichannel world of holistic interactions that form new visions, expectations, values and desires in a tremendous speed. Ideas and experiences are shared and exchanged in online communities without the need of the involvement of the suppliers. This “holistic view” challenges firms further through the seamlessness it requires to create unity. Customer-centric research needs a new push for the development of instruments and measures to cope with the consumer decision process challenges. Process thinking is needed to capture the purchasing habits in an omnichannel world and to build a new thought for customer journey experience with the aim to understand technology-linked value propositions of customer clusters to optimize channel interactions. Customer journeys have to focus and describe the online/offline experiences at the hybrid shopping mile, trace the behavioral influential factors of the customers’ and sellers’ world in a technological environment. This chapter will discuss “Technology based Orbit Interactions” for “The Hybrid Shopping Mile and its Customer Journey Mapping” with a “Customer Intelligence Framework.” The outcome of the hybrid customer journey mapping gives orientation for customer-management decisions in developing new approaches.

The purpose of this study is to examine the role of interaction in supporting value co-creation during pre-purchase customer journey stages when selling professional B-to-B services. First, value co-creation in professional service firms (PSFs) is reviewed, and, second, the role of interaction in the different stages of a customer’s pre-purchase journey is explored, specifically in the context of B-to-B human resource management services.

Qualitative, semi-structured interview data was collected from potential B2B customers of a PSF in question, providing a broad coverage of prospective clients in architecture, engineering and IT sector.

In general, the findings of this study indicate that interaction plays a crucial role in pre-purchasing stages of a customer journey. In particular, these findings form understanding of how various interaction channels and content support PSF’s ability to co-create value with its prospects.

The existing research tends to concentrate on how value is created for existing customers, and far less attention has been paid to the perspective of prospects. This study contributes theoretically by providing novel insights into the current literature on value co-creation in PSFs by providing an understanding of how interactions in pre-purchase phases affect the co-creation of value from the perspective of prospects, which is a less researched viewpoint. Empirically, this study offers managers much-needed, context-specific knowledge of PSFs by comparing differences and pulling together similarities from each customer journey stage of PSF prospects.

This paper aims to define and frame the understanding of customer journeys, associated areas of consumer decision-making process stages and touch point categories based on an ownership perspective.

The research is based on a detailed literature review of customer journeys, in peer-reviewed marketing and retail journals, within the last decade. The Chartered Association of Business Schools (ABS) academic journal guide marketing discipline list was used because it only includes peer-reviewed journals, based on an internationally accepted quality ranked list.

The detailed analysis of the journals identified three groups of touch points (brand owned, partner owned/managed and outside the control of brand owner/partner) and three decision-making process stages (pre-purchase, purchase and post–purchase) that informed a clearer definition and understanding of the customer journey.

Limitations concern the ABS database was used and a ten-year date period was selected, which may exclude some relevant journal articles, particularly those written in a language other than English.

The authors have provided a revised definition of customer journey, clarified the decision-making stages and subsequent categorisation of touch points from an ownership perspective.

This study aims to investigate customers' personal innovativeness (PI) as an influencing factor of omni-channel customer experience throughout pre-purchase, purchase and post–purchase stages of the customer journey, and their subsequent influences on customers' reuse intention.

Data were collected from customers who had experience with omni-channel shopping in South Korea through a questionnaire made with Naver Forms, both online and offline from 15 June to 15 July 2022. Out of the received responses, only valid and consistent questionnaires were considered for statistical analysis. In total, 272 valid samples were utilised for the final analysis. Analyses included reliability, validity, path, structural equation modelling and mediation effects, using SPSS and AMOS software.

The results revealed a significant influence of personal innovativeness on the omni-channel customer experience across all purchase stages. Personal innovativeness was found to influence the customer experience in the pre- and post–purchase stages, thus affecting reuse intention. However, it did not have the same effect in the purchase stage. The omni-channel experience customer experience also played an indirect mediating role in the relationship between personal innovativeness and reuse intention.

First, personal innovativeness in the IT domain may be very prominent in studies examining innovative behaviours related to computing technology. Second, this study provides further understanding of customers' intentions to reuse omni-channel shopping. Third, the path analysis showed that personal innovativeness significantly affects customer experience at all pre-purchase, purchase and post–purchase stages of the customer journey. However, except for the purchase experience, both pre- and post–purchase experiences significantly impact customers' intention to reuse omni-channels and play a mediating role.

First, omni-channel retailers should launch new products, innovative promotional activities and explore new channels or new service modes to stimulate the need recognition of customers with high personal innovativeness. Second, omni-channel retailers should pay attention to the users' reviews of each channel because they play a key role in potential customers' purchase decisions. Third, offering customers a seamless shopping experience is essential as a marketing strategy for omni-channel retailing.

This study elucidates the causal relationship between personal characteristics and behaviour by dividing the omni-channel customer journey. In particular, personal innovativeness is identified as an important predictor of the intention to reuse omni-channels during the pre- and post–purchase stages. This suggests that omni-channel retailers need to strategically manage these stages to boost customers' reuse intention.

The digitalization process has been influential on the way marketing is conducted. However, luxury brands have not yet fully channeled the benefits of the integration of various touchpoints. The aim of this chapter is to provide insights into building a luxury fashion omnichannel strategy through the integration of online and offline consumer journeys, based on the emerging needs and lifestyles of different luxury consumer segments. Accordingly, exploratory research is designed to understand luxury consumer typologies and luxury fashion shopping journeys. In-depth interviews were conducted for data collection in Istanbul, with 16 participants. Grounded theory coding was used for analyzing the data. Findings revealed four-consumer typologies –Luxury Beginners, Nouveaux Riches, Conservatives, Established Luxury Consumers. Luxury fashion journey map covering three major steps – pre-purchase, purchase, and post-­purchase – was illustrated based on the usage of both digital and non-digital channels and agents through the journey with discussions to present consumer differences. The results of the study add to the current literature and provide an omnichannel roadmap for the practitioners.

This study aims to analyze the impact of newly created brand awareness on customer’s buying behavior in online environment.

The authors analyzed more than 280,000 online customer journeys from four e-commerce stores based in Slovakia. Within the results of the interaction analysis of individual customer journeys, the authors determined three criteria based on the level of theoretical brand awareness. The purpose was to determine their occurrence in real-world data.

It was found that each of the specified criteria accounts for the significant share of the company’s revenues. Based on these criteria and the level of their occurrence, the authors introduced the term direct traffic effect.

Because of the available Web analytics tools, the data might be imprecise because of data collection issues. There is also ambiguity in the interpretation of the customer journey.

The company can build awareness among prospective customers by offering them a positive customer experience during the first interactions online. Data proved that customer will not only repeatedly visit the website from the direct traffic source but also his customer journey will end with the purchase of the company’s products.

This paper fulfills the need for further research on the impact of multi-channel marketing on brand awareness and consumer behavior, respectively.

The purpose of this paper is to contribute to the special issue theme by exploring customer response to automated relationship management tactics on social media channels.

A total of 17 in-depth interviews of young adults, ranging from the age of 19 to 26, were conducted. From this, customer journey maps were compiled incorporating socialbots as a valuable touch point along the service delivery cycle.

The research frames the socialbot as a valued customer service agent to young adults with some favouring this over telephone and email communication methods. Younger consumers respond positively to the quick resolution offered by the socialbot mechanism with most acknowledging that the bot is only able to manage simplified requests. Human-to-human customer relationship management is preferential when the query reaches critical mass.

Socialbots on Facebook Messenger provided the research context for this study; therefore, other platforms and owned website bots should be considered in future studies.

This research identifies the younger generation as a key target market for the development of customer service-related bots.

To the best of the authors’ knowledge, this is the first study to examine the socialbot as an automated touch point in the customer journey and contributes knowledge to the growing body of literature focussed on artificial intelligence in customer service. Moreover, it provides valuable qualitative insights into how socialbots influence the customer experience and related outcome measures.

Various consumer-facing artificial intelligence (AI) applications are used to interact with consumers at all purchase stages, and related research has sharply increased. This study aims to synthesize the literature related to consumer–AI interaction using the customer journey framework, identify the factors affecting AI's effectiveness in interactive marketing and offer an agenda for future research.

This study undertakes a framework-based systematic review of 239 articles on AI in marketing from the consumer perspective published in peer-reviewed journals from 2007 to 2021.

This review identifies the roles of AI touch points and factors affecting the acceptance and effectiveness of consumer–AI interaction in each stage of the customer journey.

This study is the first to review the existing literature using a customer journey framework to identify the factors that influence customer interactions with AI touch points at each purchase stage and pave the way for future research.

The quality of the customer journey has become a critical determinant of successful service delivery in contemporary business. Extant journey research focuses on the customer path to purchase, but pays less attention to the touchpoints related to service delivery and consumption that are key for understanding customer experiences in service-intensive contexts. The purpose of this study is to conceptualize service journey quality (SJQ), develop measures for the construct and study its key outcomes.

The study uses a discovery-oriented research approach to conceptualize SJQ by synthesizing theory and field-based insights from customer focus group discussions. Next, using consumer survey data (N = 278) from the financial services context, the authors develop measures for the SJQ. Finally, based on an additional survey dataset (N = 239), the authors test the nomological validity and predictive relevance of the SJQ.

SJQ comprises of three dimensions: (1) journey seamlessness, (2) journey personalization and (3) journey coherence. This study demonstrates that SJQ is a critical driver of service quality and customer loyalty in contemporary business. This study finds that the loyalty link is partially mediated through service quality, indicating that SJQ explains loyalty above and beyond service quality.

Since service quality only partially mediates the link between service journey quality and customer loyalty, future studies should examine alternative mediators, such as customer experience, for a more comprehensive understanding of the performance effects.

The study offers concrete tools for service managers who wish to understand and develop the quality of service journeys.

This study advances the service journey concept, demonstrates that the quality of the service journey is a critical driver of customer performance and provides rigorous journey constructs for future service research.