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The purpose of this paper is to identify the patterns of customer exposure to touchpoints by segmenting consumers based on the frequency of their exposure, and to understand the relationship of patterns of exposure with customer loyalty intentions (relationship commitment, self-disclosure and positive word-of-mouth) and demographic characteristics.

An online survey of almost 4,000 customers was employed in a supermarket retail setting. Customers were segmented based on their frequency of recalled exposure to multiple touchpoints, by means of a latent class cluster analysis, while considering the role of demographic characteristics. Afterwards, loyalty intentions variables were regressed on the resulting customer segments.

Based on the touchpoint exposure, six customer segments emerge. The main differences across segments relate to the intensity of frequency of exposure and the types of touchpoints customers have been exposed to. Sex, age, shopping role and geographic area of residence are related to segment membership. The identified patterns of exposure explain relationship commitment, self-disclosure and positive word-of-mouth: clusters displaying higher exposure to touchpoints display higher loyalty intentions than clusters displaying lower exposure.

The study offers actionable implications for brands and retailers on how to manage touchpoints for implementing omnichannel strategies.

As far as the authors know, this study is the first to identify exposure to multiple touchpoints and understand the role of demographics as far as touchpoint exposure is concerned. It also provides interesting findings on the relationship of different combinations of touchpoints with customer loyalty.

The explosion in the number of touchpoints is putting pressure on companies to design omnichannel customer experiences aimed at achieving long-term customer loyalty. The purpose of this paper is to examine the relative importance of 24 touchpoints in contributing to customer loyalty intentions.

Data were collected by means of a survey on almost 6,000 subjects belonging to the Nielsen consumer panel. Two ordinary least squares regression models with clustered standard errors estimate the relationship between touchpoint exposure – measured in terms of reach, frequency and positivity – and customer loyalty intentions in the mobile service sector.

Reach has a significant relationship with customer loyalty intentions as far as eight touchpoints are concerned. Positivity, when controlling for frequency of exposure, is related to customer loyalty intentions as far as nine touchpoints are concerned.

Results provide guidance for mobile service providers on customer experience management strategies and specifically on touchpoint prioritization, adaptation, monitoring and design.

This study addresses two relevant research gaps. First, most studies focus on single or a few touchpoints without considering the variety of touchpoints within the customer journey (Lemon and Verhoef, 2016). Second, no studies focus on the relative contribution of touchpoints to customer loyalty intentions (Homburg et al., 2017).

The purpose of this paper is to identify patterns of medium preference for loyalty programs (LPs) among members to support the case for segmenting customers based on their medium preference.

A survey of nearly 2,000 customers who are enrolled in at least one supermarket LP was employed. LP members are segmented based on a latent class clustering model and then profiled in terms of socio-demographic variables by means of a multinomial logit regression model.

Medium preference is heterogeneous and differs at the customer segment and at the LP touchpoint level. Five segments emerge which display different medium preference patterns. LP medium preference is associated with age, gender, affluency and number of different LPs the customer is enrolled in.

Retailers, e-tailers and brands can benefit from this customer segmentation when faced with the challenges of adding online features or migrating their LPs online. Marketers should differentiate their investment in online and offline LP touchpoints according to the medium preference for each LP touchpoint of the customer segments of interest.

Retailers, e-tailers and brands are today introducing online marketing strategies and tactics, such as LPs, that have been traditionally used offline. So far, however, they have failed to answer the question whether online and offline LPs and related touchpoints have the same preference among consumers. Literature on LPs has not explored customer preference for the LP medium or the consumer characteristics related to medium preference. This work is unique in providing an overview of medium preference for LPs and their touchpoints.

This paper analyses how the purchase channel and customer complaint goals affect the sequential choice of post–purchase complaint channels when customers experience a service failure followed by a service recovery failure (double deviation).

An online survey involving a scenario manipulation was conducted with 577 apparel shoppers. The study employs multi-group latent class analysis to estimate latent customer segments within both online and offline groups of shoppers and compare latent classes between the two groups.

The results show that the purchase channel has a lock-in effect on the complaint channel, which is stronger for offline buyers. Moreover, there is evidence of channel synergy effects in the case of having to complain twice: shoppers who complain in store in the first attempt turn to online channels in the second complaint attempt, and vice versa. Complaint goals shape the choice of complaint channels and define different shopper segments.

The present study is the first to adopt a cross-stage approach that analyses the dependencies between the purchase channel and the complaint channel used on two subsequent occasions: the first complaint after a service failure and the second following a service recovery failure.

The study aims to propose a comprehensive overview of the Omnichannel phenomenon by identifying its theoretical foundations as well as future research directions.

In order to systematize Omnichannel-centered contributions and identify future research directions for post-Covid-19, this study adopted a mixed-method study, combining a systematic literature review, a bibliometric co-citation analysis and a panel discussion by field experts.

In Study 1, the authors traced extant literature on Omnichannel back to its theoretical foundations, which led to the identification of four research areas in which the concept of Omnichannel is rooted. Contributions pertaining to the aforesaid research areas were discussed and submitted to a panel of experts (Study 2) after the lockdown periods. The experts gave various insights into both the past and future of Omnichannel research. Finally, a framework synthesizing theoretical foundations of Omnichannel, literature gaps and opportunities for future research is provided.

To our knowledge, this is the first attempt to combine mixed methods study in Omnichannel research and to involve a panel of experts in order to discuss the findings of a literature review and evaluate future research directions. This choice allowed us to investigate both incumbent academic and managerial challenges raised by Omnichannel and to provide guidance for the post-pandemic recovery.

The purpose of this paper is to evaluate the recent evolution of store flyers to illustrate how a tool of traditional marketing can be applied to generate insight on customer “couch-to-cart” behaviour thus supporting an innovating shopper marketing approach. The authors support this position by elaborating on three themes: first, the recent evolution of flyers, driven by incorporation of customer insight derived from loyalty data and by new features enabled by flyer digitalization; second, the evolution of the flyer planning and management process, related to opportunities and challenges in the retailer organisational structure; and third, the rise of online flyer aggregators.

The authors used field interviews. The authors included the perspectives of different subjects involved in planning and delivering flyer-based promotions. Secondary data were also collected regarding flyer activities of a sample of 67 retail groups across 15 countries and four industries.

Critical aspects of flyers as retail marketing tools emerged. The authors found that there are changes taking place in flyer-based promotion caused by “fertilisation” by loyalty data and digital that have not been captured by research so far. Retailers are experimenting with flyer aggregators. These infomediaries generate new insight on various aspects of the shopping cycle. Retailers can use these metrics to improve flyer strategy and negotiation with suppliers. The authors shed light on obstacles that prevent exploitation of shopper marketing benefits and value. Among the managerial challenges the authors found retailer organisation and management and functional integration.

The paper points to four areas for future research: promotion innovation, electronic intermediaries, marketing organisation and competition. Research questions are suggested.

This study contributes to retail management by identifying best practices that support promotional campaign development in a shopper marketing perspective. The authors provide suggestions around the incorporation of loyalty data in the flyer planning process and the creation of inter-functional teams.

Academic research has long addressed flyer-based promotion, but has not linked it to innovation or shopper marketing. Little or no attention has been paid to the flyer management process and its organisational dimensions, nor to digital flyers.

This paper aims to focus on how companies shape the architecture of a phygital customer journey through the exploitation of smart technologies.

The research adopts a qualitative method using a grounded theory approach involving leading players in digital customer solutions and service providers from different industries.

The shaping of the architecture of the phygital customer journey comes from the interplay between systems of insights and systems of engagement activated by multiple customer-provider interactions in an entanglement of physical and digital contexts.

Companies need to design a blended approach to bridge disconnected contexts, capture new opportunities and provide customer engagement along the entire journey.

This study depicts the “phygital customer journey” under systems of insights and systems of engagement: These systems operate as dynamic architectures to capture insights and engage customers.