Conventionalists,Connectors, Technoisseurs and Mobilarti: Differential profiles of mobile marketing segments based on phone features and postmodern characteristics of consumers

The high penetration of mobile phones amongst the South African population presents mobile phones as an attractive interactive marketing communication medium. This paper argues that the access and actual use of different phone device features can be productively used as a segmentation approach, which may enable marketers to be more effective in planning interactive marketing communication plans. This study, based on 330 students, developed segments derived from mobile phone usage patterns using cluster analysis. The outcome revealed four clusters that were named: Connectors, Conventionalists, Technoisseurs and Mobilarti. Connectors made daily use of a full range of communication functions. Conventionalists were inclined to limit their use of mobile phone features to talking and texting. Technoisseurs were found to use a whole range of sophisticated mobile phone facilities. Mobilarti were identified as a group of expert users; using the full range of functions available to them on their phones, despite recording the lowest percentage of smartphone ownership when compared to the other groups. These groups were further profiled by analysing attitudinal and behavioural variables pertaining to two newly developed postmodern dimensions, which were introduced in the study as mobile importance as an attitudinal aspect, and social transformation as a behavioural outcome. For marketers, an understanding of the proposed segments, as well as the differences in attitudes towards mobile importance and social transformation behaviours, coupled with typical financial and social realities of these segments, allow targeting strategies that are more clearly actionable.     

How many,how often,and how new? A multivariate profiling of mobile app users

Despite enormous demand for and explosive growth of mobile phone apps in recent years, few studies have been conducted to arrive at a multi-faceted valuation of app users. Our paper addresses this important gap in literature. Drawing on Household Production Theory and Hedonic and Utilitarian Consumption Theory, we investigate how mobile app users behave in the dimensions of possession quantity, usage Frequency, and acquisition Recency. We propose a multivariate model to examine these behaviors jointly and calibrate it using data from a survey of app users. We take a Bayesian MCMC computational approach for model calibration. The results are consistent with our theoretically derived expectations. The significance of the findings is discussed.     

The diffusion of mobile payments: Profiling the adopters and non-adopters,Roger's way

This study aims to establish various market segments based on consumers' attitudinal elements influencing the adoption of mobile payments (m-payments). It also examines the best discriminators between identified clusters of m-payment users. Three hundred and sixty m-payment users participated in the study. Cluster and discriminant analyses were employed for the analysis. The findings suggest that two segments are established, and strategies can be developed accordingly. The study provides marketers with numerous touchpoints to propagate the adoption of m-payment apps. It also comprehensively explains m-payment users in developing economies by superimposing the cohorts to Roger's diffusion of innovation model.     

Exploring technology readiness for mobile payment app users

ABSTRACT

The study aims to better understand the various technology readiness segments by assessing how their readiness relates to demographics variables and their adoption, attitude, ease-of-use, usefulness and continuance intention to use mobile payment apps using the technology readiness index. Using a convenience sample of 416 from a consumer panel, a two-step cluster analysis shared similarities with three of the original technology readiness segments (pioneers, paranoids and explorers) while the other two segments clustered together into a fourth segment, hesitant-sceptics. The results indicate that South African mobile users are ready to use mobile payment applications, with the ‘explorer’ emerging as the best segment to target due to optimism levels, while the hesitant-sceptic segment represent the key to unlocking the real potential value of mobile payment apps. Understanding different segments provides marketers with the opportunity to select viable segments and to customise strategies to increase uptake and continued use according to customer needs.     

A Preliminary Study of Fintech Industry: A Two-Stage Clustering Analysis for Customer Segmentation in the B2B Setting

ABSTRACT

This practitioner note proposes a new approach considering two-stage clustering and LRFMP model (Length, Recency, Frequency, Monetary and Periodicity) simultaneously for customer segmentation and behavior analysis and applies it among the Iranian Fintech companies. In this practitioner note, the K-means clustering algorithm and LRFMP model are combined in the customer segmentation process. After initial clustering, for a better understanding of valuable customers, additional clustering is implemented in segments that needed further investigation. This approach contributes to a better interpretation of different customer segments. Customer segments, consisting of 23524 business customers are analysed based on their characteristics and appropriate strategies are recommended accordingly. The first stage clustering result shows that customers are best segmented into four groups. The first and fourth segments are clustered again and the final 11 groups of customers are determined. This note provides a systematic and practical approach for researchers and practitioners for segmentation, interpretation, and targeting of customers especially in the B2B setting and the Fintech industry and helps managers to make effective marketing strategies and enhance customer relationship and marketing intelligence.     

我国电子商务中手机支付的产业发展初探

电子商务自出现以来发展势头强劲,网络购物的用户不断增长。与此同时,电子支付工具也得到快速发展,在智能手机出现后,由于手机用户的广泛性,手机移动支付将成为未来发展的主流趋势,具有更广阔的市场。手机支付方便快捷,但是作为一种网络支付方式,却受制于通信网络、标准化和安全性等问题。手机支付产业的良性发展需要政府、金融机构、电信运营商与其它相关机构协作,建立移动支付产业链,为手机用户提供规范安全的支付环境。     

Japan's Quest for M-Commerce Dominance

Abstract

NTT DoCoMo's I-mode system is one of the most successful stories in mobile communication industry. The system has expanded the spectrum for mobile phone users to do more than just phone calls. Although I-mode is primarily used in Japan, its business model and the strategy of doing business may have a profound impact on world's m-commerce in the near future.     

Willingness to use mobile application for smartphone for improving road safety

In the last few years mobile devices have reached a large amount of consumers in both developed and high-growth world economies. In 2013, 97% of the Italian population owns a mobile phone, and 62% owns a smartphone. Application software for mobile devices is largely proposed to consumers, and several mobile applications were oriented toward the improvement of road safety and road accident risk reduction. In this paper, we describe the results of a survey oriented to preventively investigate on the willingness to receive and/or to give information about road condition by means of mobile devices. Road users were informed about the characteristics of a mobile application, and then they were invited to complete a questionnaire. Experimental data were used for capturing road user attitudes toward the use of the smartphone to improve road safety, and to establish the preferences for the different features of the proposed mobile application. To this end, we choose to use the ordered probit model methodology. We demonstrate that the adopted methodology accounts for the differential impacts of the willingness to receive and/or to give information about road conditions on the overall willingness to receive and/or to give information through an application software for mobile devices.     

Identifying multi-channel value co-creator groups in the banking industry

The purpose of this paper is providing a value co-creation management framework in the banking industry using the data analysis. Moreover, a multi-channel segmentation approach will be developed in order to identify customer segments based on the use of each channel. Managing value co-creation can be defined as determining the channel that may be used by the customer and the kinds of encounters that lie in these channels to have different impacts on the customer for various types of encounters. The model is built on the basis of the related literature and the collaboration of a Customer Relationship Manager in a large bank in Iran. Then, a multi-channel segmentation model is developed based on the RFM variables of the five banking channels for each customer. Next, about 11,000 customers of the bank is segmented by comparing the k-means and DBSCAN algorithms. Finally, by adapting customer segments on the value co-creation framework, three general groups are identified based on the type of encounter that lies in each channel. Moreover, twenty-seven small groups are recognized based on the desirability of the customer use of the channels.     

Predicting Consumer Behavior and Media Preferences: The Comparative Validity of Personality Traits and Demographic Variables

It is common practice for organizations selling a product to divide potential consumers into segments to allow them to target those most likely to buy their products. Two broad approaches to market segmentation can be delineated. The most common approach relies on segmenting by demographic variables (e.g., age, gender). The second approach (known as “psychographics”) identifies market divisions in terms of psychological variables such as values, attitudes, and personality traits. There has been little research comparing the efficacy of the two approaches. Based on analyses of over 45,000 participants, the present research empirically compares the effectiveness of the two approaches among segmentation variables ranging from cell phones and lottery tickets to newspapers and television shows. Overall, both approaches explained surprisingly small amounts of variance in consumer behavior. Nonetheless, for the variance that was predictive, the relative contribution of demographics and psychographics varied dramatically across consumer behaviors; for some behaviors (e.g., electronic purchases), demographics had superior predictive potential but for others (e.g., television shows) psychographics were more useful. Therefore, an approach that integrates both methods is recommended.     

The Advertising Association's Index of Press Cover Prices

This paper examines the differences between American young consumers and their Korean counterparts’ interests in accepting SMS advertising via their mobile phones. The appeal of using the mobile phone as an advertising medium is its accessibility because it can pinpoint the locations of mobile phone users. The results of the study provide preliminary evidence that consumers’ attitudes and beliefs do have significant positive relationships with intentions to opt in to the new medium. The theoretical model for the study is based on employing the theory of reasoned action as the underlying structure to operationalise the conceptual constructs proposed in the diffusion theory. The study identifies the potential of a new research domain in advertising, presents a conceptual framework for its examination and suggests the importance of constructs under study.     

Determining influences of information irrelevance,information overload and communication overload on WeChat discontinuance intention: The moderating role of exhaustion

Owing to the combined advancement of network technologies and smartphone equipments, WeChat has become particularly ubiquitous, affording younger generations with multifarious information, connectedness establishing, and interactive communication opportunities. Although a large and remain growing body of studies have investigated the antecedents of social media exhaustion, the potential influencing factors and causations leading to WeChat discontinuous intention have received limited academic attention. Based on the stressor-stress-outcome paradigm, this empirical study develops a conceptual research model to explore how information overload, communication overload, and information irrelevance contribute to social media exhaustion and how these variables relate to WeChat users' intention to discontinue use. Analysis of data from 405 WeChat users demonstrated that information irrelevance, information overload, and communication overload exert the positive influence on WeChat users’ exhaustion. Moreover, social media exhaustion is also a significant predictor of WeChat discontinuance use intention. This research satisfies the existing demand for an in-depth investigation of social media exhaustion phenomenon by uncovering the drivers and antecedents of discontinuous usage intention of WeChat among younger generations. Obtained findings may not only contribute to the further comprehending of discontinuance intention from a cognitive overload perspective, but also provide fresh insights for practitioners on how to strategically manage mobile social media adoption behavior and sustain active young users in contemporary mobile-saturated societies.     

Using segment level stability to select target segments in data-driven market segmentation studies

Market segmentation is widely used by industry to select the most promising target segment. Most organisations are interested in finding one or a small number of target segments to focus on. Yet, traditional criteria used to select a segmentation solution assess the global quality of the segmentation solution. This approach comes at the risk of selecting a segmentation solution with good overall quality criteria which, however, does not contain groups of consumers representing particularly attractive target segments. The approach we propose helps managers to identify segmentation solutions containing attractive individual segments (e.g., more profitable), irrespective of the quality of the global segmentation solution. We demonstrate the functioning of the newly proposed criteria using two empirical data sets. The new criteria prove to be able to identify segmentation solutions containing individual attractive segments which are not detected using traditional quality criteria for the overall segmentation solution.     

The correlations between price cuts/changes and fee sensitivity on the choice of mobile phone service provider

This study adopts fee thresholds to measure users' fee sensitivity and employs a two-step logit model to predict a phone user's probability of choosing a certain service provider. The results indicate that the choice probability can be overestimated if the reference fee effect is not taken into consideration. Furthermore, the lower calling fee image and perceptions shaped by the telecommunications service provider can increase the probability of it being chosen. Users' benefit (saving money) perceptions also reveal a significant difference. In this regard, price promotion effects may not necessarily be successful for every service provider at the time. Service providers with a larger base of benefit perception users have a relative advantage in price-cutting activities. The characteristics of users in the low-loss perception (insensitive to an expensive fee) group are younger, female, and college-educated. Service providers could focus on this segmented market and implement a non-price strategy in order to attract more users. This study may be useful to mobile phone service providers in terms of price-setting policy and image management.     

An exploratory investigation of factors affecting and best predicting the renewed adoption of mobile wallets

Foreign nationals often have no other choice than to adapt themselves to technological innovations of their host countries. This is particularly the case of individuals who are exposed temporarily to the world’s cashless societies where mobile wallets are the dominated payment method. Yet, little is known regarding continuous usage intentions among these individuals who have accumulated experience interacting with mobile wallets.This study explores how relative convenience, relative advantage, perceived privacy, and perceived security influence 'renewed adoption' of mobile wallets among experienced users of the leading Chinese mobile wallets. It also explores the best predictors of the renewed adoption intention of mobile wallet technology among these users. The results of this study show that each of the independent variables positively influences renewed adoption intentions. The results also show that relative advantage and perceived security as the best predictors of renewed adoption intention of mobile wallets. Based on the results of this study, practical and theoretical implications are provided.     

Determinants of Mobile Banking Users’ Loyalty

Abstract

In recent years, the banking sector has undergone major changes in the way it serves its customers. Banks have found that customer loyalty is fundamental to strengthening their strategies. The objective of this paper is to identify the variables that have the greatest influence on the loyalty of mobile banking users. A structural equation model of the relationships between the studied variables was developed. The main results indicate that the variables with the greatest influence on mobile banking users’ loyalty are satisfaction, use, and trust. Several conclusions, managerial implications, and possibilities for future studies emerge from these results.     

Segmenting multichannel consumers across search,purchase and after-sales

While bricks-and-mortar stores and the Internet are dominant retailing channels, mobile and social media have rapidly emerged and challenge traditional retail models and consumer behavior. However, researchers have yet to account for how consumers integrate mobile and social channels throughout the various stages of the buying process. Using Latent-Class Cluster Analysis segmentation, we examine consumer behavior in store, Internet, mobile, and social media channels across the search, purchase and after-sales buying stages in the aggregate and specific to the clothing, holiday travel and consumer electronics categories. We find five multichannel consumer segments on the basis of perceived channel importance across the buying process, as well as psychographic and demographic characteristics. Interestingly, we find a polarization in perceived importance of mobile and social media channels, with two consumer segments rating mobile and social media channels as unimportant in the buying process. Furthermore, and compared to prior segmentations of multichannel consumer behavior, we do not find an aggregate store-focused segment. However, a store-focused segment exists in the context of buying clothing and represents 28.6 per cent of consumers. The findings show multichannel consumer preferences and behavior continues to evolve in line with new and emerging retailing channels. Further, this study confirms that there is no ‘one-size fits all’ approach to multichannel retailing.     

Segmentation of visiting patterns on web sites using a sequence alignment method

In this article, a new method is illustrated for segmentation of visiting patterns on a web site. Instead of clustering users by means of a Euclidean distance measure, in our approach users are partitioned into clusters using a non-Euclidean distance measure, called Sequence Alignment Method (SAM). This method ensures that sequential relationships, represented by the order of elements, are taken into account. In experiments using real traffic data on the web site of a Belgian telecom provider, the performance of SAM is compared with the results of a method based on Euclidean distance measures. Empirical results show that SAM identifies segments presenting behavioral characteristics not only with regard to content but also considering the order of pages that are visited on a web site.     

A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data

We consider the problem of simultaneously performing market segmentation and predicting product choice for a given population of consumers. This behaviour-based segmentation model uses several types of information characterizing individual consumers and their market context: sociodemographic, psychographic and product choice data. These data are combined in a normative conceptual framework that posits the formation of latent segments, each of which displays differing degrees of sensitivity to relevant product attributes. This permits results obtained by the proposed model structure to differ significantly from those of traditional segmentation techniques, which usually produce a set of groups characterized by smaller within-group than between-group variation in sociodemographic and/or psychographic variables. By making the segments behaviour-based, it is argued that the segments produced by the model will be more actionable and more directly relevant to management decision-making. The proposed model is applied to a data set involving choice of a beauty product offered by five national brands. The results show that the explanatory power of the latent segmentation and choice model is far greater than that of the MNL model, which is nested within our more general specification. The types of results available from the model are illustrated through the application.