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Describes how companies can make managing the emotional expectations of customers the frontier of the customer‐focused enterprise.

Customer experiences have emotional characteristics that companies historically haven't been good at delivering. The customer experience is more than an analysis of hard metrics about speed, availability and information. These performance measures are critical, but real progress in shaping the customer experience comes from addressing the emotional aspects of their interactions.

The key to success is to fully understand the customers' needs and expectations. By doing so, companies can identify what the most important interactions are – key “moments of truth” – and prioritize delivery on these interactions.

By employing a customer experience framework to prioritize resources according to the impact of particular customer interactions, paying particular attention to emotional experiences, companies can build achievable operational models that create customer advocates.

Best‐in‐class companies understand the entire customer experience and use a Customer‐Focused Enterprise model to foster customer advocates while deploying resources effectively and efficiently. The six characteristics of the CFE are: customer authority, customer dialog, integrated execution, solution experience, human performance and customer focused organization.

This study aims to investigate organizational learning, represented by the absorptive capacity, as a condition for the firm to learn about marketing data and make more informed decisions. The authors also aimed to understand how the behavior of micro, small and medium enterprises (MSME) businesses differ in this scenario through a multilevel perspective.

Placing absorptive capacity as a mediator of the relationship between business analytics and rational marketing decisions, the authors analyzed data from 224 Brazilian retail companies using structural equation modeling estimated with partial least squares. To test the cross-level moderation effect, the authors also performed a multilevel analysis in RStudio.

The authors found a partial mediation of the absorptive capacity in the relation between business analytics and rational marketing decisions. The authors also discovered that, in the MSMEs firms’ group, even if smaller companies find it more difficult to use data, those that do may reap more benefits than larger ones. This is due to the influence of size in how firms handle information.

The sample size, despite having shown to be consistent and valid, is considered small for a multilevel study. This suggests that our multilevel results should be viewed as suggestive, rather than conclusive, and subjected to further validation.

Rather than solely positioning business analytics as a tool for decision support, the authors’ analysis highlights the importance for firms to develop the absorptive capacity to enable ongoing acquisition, exploration and management of knowledge.

MSMEs are of economic and social importance to most countries, especially developing ones. This research aimed to improve understanding of how this group of firms could transform knowledge into better decisions. The authors also highlight micro and small firms’ difficulties with the use of marketing data so that they can have more effective practices.

The research contributes to the understanding of organizational mechanisms to absorb and learn from the vast amount of current marketing information. Recognizing the relevance of MSMEs, a preliminary multilevel analysis was also conducted to comprehend differences within this group.

According to IBM research, companies seeking opportunities in an era of constant customer connectivity focus on two complementary activities: reshaping customer value propositions and transforming their operations using digital technologies for greater customer interaction and collaboration. This paper aims to address this issue.

The paper explains that businesses aiming to generate new customer value propositions or transform their operating models need to develop a new portfolio of capabilities for flexibility and responsiveness to fast‐changing customer requirements.

The paper finds that engaging with customers at every point where value is created is what differentiates a customer‐centered business from one that simply targets customers well. Customer interaction in these areas often leads to open collaboration that accelerates innovation using online communities.

Companies focused on fully reshaping the operating model optimize all elements of the value chain around points of customer engagement.

The article explains how companies with a cohesive plan for integrating the digital and physical components of operations can successfully transform their business models.

To sustain competitive advantage, it is necessary to understand consumers and their psychological fears and deliver them a service solution which is best under existing conditions so as to ensure consumer loyalty and retention. This paper seeks to conceptualise and operationalise customer relationship management (CRM) through two component model (operational CRM (OCRM) and analytical CRM (ACRM)), particularly in the healthcare sector.

The relationship between OCRM, based on three patient‐staff constructs (physicians, nurses and support staff) and ACRM based on four constructs (satisfaction, repatronization, recommendation and organizational performance) was analysed using confirmatory factor analysis (AMOS). The data for the model were collected from 306 indoor patients of three large public hospitals who have been associated with the hospital for at least five years.

The model portraying service quality as an antecedent to OCRM is found to be acceptable whereas the other two models, namely, service quality as the moderating variable in explaining OCRM and ACRM relationship effectively and direct relationship between OCRM (service quality implicit) and OCRM) were rejected. Characteristics, primarily caring attitude, friendliness, helpfulness, response to queries, expertise and effective treatment are found to be significant for OCRM from physicians, nurses and support staff perspectives that can impact the four ACRM dimensions – satisfaction, repatronization, recommendation and organizational performance.

The study contributes to the current understanding of CRM in particular and consumer behaviour in general, in the context of the healthcare sector. The role of service quality in influencing patient‐staff interaction and CRM linkage with the service dominant concept has added more strength to the conceptual development of TCRM.