The Importance of the Journey Map in the Design of a Playful Interactive-Interface

This article presents the importance of using the customer journey map (CJM) as a tool for managing new information technologies. The case study presents the use of the CJM to indicate the experiences that people have when using a playful interactive-interface, where the causal relationship between the brightness and the distance of the stars is visualized. The CJM is the result of a quantitative and qualitative study about user experience (UX) or UX research. Where you can use: 1) observation techniques, 2) interviews, 3) questionnaires, 4) a review of the domain literature about the phenomenon, archetypal descriptions, 5) diagrams of mental models; also known as thought schemes, or cognitive maps, among others. This research focuses the development of the interface in the design of archetypal profiles and mental models to generate the CJM, in the domain of the specific phenomenon.

Framework to Understand and Deploy AI-Based Smart CRM in the Airline Industry

This is the age of AI. Soon what customers think will be understood by the smart applications on their mobile devices and the information—most of which will be pre-processed based on the customer personas—will be available at the blink of an eye. In this chapter a critical analysis of how AI bolsters CRM capabilities in the airline industry is conducted. To understand that, AI capabilities are surveyed and its transformational effects on CRM and its impact on customer acquisition, retention, loyalty, and experience are explored in depth. In the end, a customer journey-based deployment framework is presented that supports the finding of the AI-CRM implementation use cases.

Omnichannel and Experience Approach as a Post-COVID-19 Economic Reactivation Mechanism

The aim of this chapter is to show how omnichannel tools must be applied through the process of creating experiences for the consumers. During the literature review, some authors make approaches to the key concepts connecting omnichannels and consumer experiences; therefore, they explain through the analysis of data the reality of the Ecuadorian environment and global trends. With this context, this chapter will present how, by using macro environment and accessibility, a unique experience may be created in the customer journey in omnichannel.

Artificial Intelligence and Personalized Banking

AI has begun making its presence felt in every industry and now across the financial services industry as well. This chapter examines and presents the use of AI in banks for better customer service giving them a personalized experience. This chapter explains how banks are getting future-ready for their financial services by means of AI and are delivering financial offerings seamlessly. This research primarily focuses on the concept of AI in the field of banking, how AI has revolutionized personalized banking and made banking operations more efficient and successful. AI innovations are an integral part of Industry 5.0 which aims at integrating automation and human intelligence. This chapter aims to study and describe the current applications of AI in the banking industry and its impact on the banking sector. The study also gives a description of the banks employing AI to facilitate an exceedingly personalized customer journey with the banks.

Hyper-Personalization

Personalization is widely used to attract and retain customers in online business addressing one size fits all issues, but little is addressed to contextualise users' real-time needs. E-commerce website owners use these strategies for customer-centric marketing through enhanced experience but fail in designing effective personalization due to the dynamic nature of users' needs and pace of information exposure. To address this, this chapter explores hyper-personalization strategies to overcome users' implicit need to be served better. The research presents a hyper-personalization process with learning (ML) and artificial intelligence (AI) techniques for marketing functions like segmentation, targeting, and positioning based on real-time analytics throughout the customer journey and key factors driving effective customer-centric marketing. This chapter facilitates marketers to use AI-enabled personalization to address customers' implicit needs and leverage higher returns by delivering the right information at the right time to the right customer through the right channel.

Applying Customer Journey Mapping in Social Marketing to Understand Salt-Related Behaviors in Cooking. A Case Study

Worldwide, salt consumption exceeds the World Health Organization’s recommendation of a daily intake of 5 g. Customer journey mapping is a research method used in market research to understand customer behaviors and experiences and could be useful in social marketing as well. This study aimed to explore the potential of customer journey mapping to better understand salt-related behaviors performed during the preparation of household cooking. We tracked the journey of four women in their kitchens for approximately two hours to observe the preparation of lunch. Individual journey maps were created, one for each woman, that were composited into a single journey map. We found that customer journey mapping was a suitable research method to understand how food preparers made decisions around adding salt and artificial seasonings at each stage of the journey. In contrast to the interviewee’ responses, it was observed that the four women added salt and artificial seasonings consistently and incrementally with little control and without any standard measure. In this study, we demonstrate the utility of customer journey mapping in a novel context and nudge social marketers to include this tool in their repertory of research methods to understand human behavior.

Reinforcing customer journey through artificial intelligence: a review and research agenda

Purpose This study defines a three-angled research plan to intensify the knowledge and development undergoing in the retail sector. It proposes a theoretical framework of the customer journey to explain the customers' intent to adopt artificial intelligence (AI) and machine learning (ML) as a protective measure for interaction between the customer and the brand.Design/methodology/approach This study presents a research agenda from three-dimensional online search, ML and AI algorithms. This paper enhances the readers' understanding by reviewing the literature present in utilizing AI in the customer journey and presenting a theoretical framework.Findings Using AI tools like Chatbots, Recommenders, Virtual Assistance and Interactive Voice Recognition (IVR) helps create improved brand awareness, better customer relationships marketing and personalized product modification.Originality/value This study intends to identify a research plan based on investigating customer journey trends in today's changing times with AI incorporation. The research provides a novel model framework of the customer journey by directing customers into different stages and providing different touchpoints in each stage, all supported with AI and ML.