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Creating Customer Engagement Via Mobile Apps: How App Usage Drives Purchase Behavior
Abstract and Figures
The proliferation of smartphones has spawned a new industry – mobile apps. Managers increasingly recognize the potential for mobile commerce apps to “engage” customers and thereby grow sales. To measure this potential, this paper examines what drives customer usage of apps and whether app usage drives purchases in the online and offline channels. The paper proposes three key drivers of app usage – marketing efforts, app-related consumer factors and app design. The drivers are empirically tested on a unique database provided by an upscale retailer on 1286 customers who have downloaded the retailer’s mobile app. The data record app usage and online and offline purchase behavior. The authors estimate models for using or “accessing” the app and the translation of access into both online and offline purchase. The results demonstrate that app access is driven by online advertising, social media messaging, app upgrades, state dependence and purchase history. Importantly, accessing the mobile app translates into both online and offline purchases, although as expected, more so online than offline. The paper concludes with managerial implications.
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... Today, when facing massive economic repercussions, local governments need to adopt strategic approaches as a part of their crisis management system (Shafi, Liu, & Ren, 2020). By keeping in view the distinguished characteristics of digital platforms, mobile shopping applications are paly an influential role (Dinner, van Heerde, & Neslin, 2015). As noted by (Butu et al., 2020), those consumers who rely on traditional shopping, are now more likely to depend on online shopping applications to purchase required products. ...
... If we talk specifically about mobile applications, today Google Play Store and Apple App Store are two dominant platforms. These platforms provide various opportunities for the users to autonomously purchase the products and services they want (Dinner et al., 2015). In this regard, depending on the types of mobile applications, here we can characterize the purpose of mobile app development into two primary categories: (i) applications that are explicitly developed from some particular platforms, i.e., IOS and Android (ii), device-neutral applications, that do not represent any specific software or platform (Bowen & Pistilli, 2012). ...
“Understanding and managing cybersecurity requires not only investing in technology but also considering its non-technical social and human aspects. Because cybersecurity is now a strategic necessity for digitalizing businesses.” A. Asiltürk
You can access this book chapter from this link: https://www.dosyaupload.com/2Mloz/advances_in_social_science.pdf
... Retail apps provide several benefits, such as store locations, reviews and product information (Danaher et al., 2015) and can provide relevant/directed and location-based information to customers (Grewal et al., 2016). Furthermore, retail apps enable a retailer to increase customers' awareness of prices, products and price promotions (Rosenbloom, 2013) and to provide experiential benefits (e.g., rewards; customer engagement) (Dinner et al., 2015). Retail apps enable customers to search for services and goods, compare prices, read reviews, make a decision to purchase products or services and complete transactions (Newman et al., 2018). ...
... With services such as community integration, smart push, information transfer and online shopping, retail apps help retailers to meet customers' needs and strengthen the communications between the two parties (Hsu and Tang, 2020). Previous studies have proven the power of retail apps in motivating customers to purchase from retailers (Dinner et al., 2015;. ...
Online retailers seek to motivate their customers to switch from web-based stores to retail apps as using the latter as a shopping channel has many benefits for retailers compared to web-based stores. This study aims to examine the drivers of customers' intention to switch from web-based stores to retail apps by applying the Stimulus-Organism-Response (S-OR) model. The moderating role of habit was investigated. Data were collected from 389 Malaysian individuals through an online survey and analysed using the partial least squares technique. The results indicated that performance expectancy has a significant influence on switching intention and is driven by mobile characteristics. Furthermore, effort expectancy has a positive effect on both performance expectancy and switching intention and is triggered by visual complexity and aesthetic quality. The moderating effects of habit on the associations between performance expectancy, effort expectancy and switching intention were not supported. The findings extend the literature on retail apps by exploring the switching intention drivers and testing the moderating effect of culture, which have received less attention. The results enable retail apps' developers and marketers to strategise retail apps development and marketing activities in a way that encourages current web-based stores' customers to use retail apps as a better alternative.
... Interactivity involves customer-to-customer interaction and customer-to-application interaction. Lele (2015) and Dinner et al. (2015) suggested that adding social features to mobile applications facilitated the interaction and communication between customers, therefore increasing customers' engagement. Besides, by enabling mobile applications to appropriately push notifications (Pham & Chen, 2019;Pham et al., 2016) and send in-app messaging (Baker, 2020;Perro, 2018), customers' attention to mobile applications is grabbed so that their engagement can also be improved. ...
... The findings of this case study suggest that factors impacting learners' engagement in education and factors affecting customers' engagement in mobile applications both matter to learners of mobile learning applications. For example, previous studies from the education field (Martin & Bolliger, 2018) and the marketing field (Lele, 2015;Dinner et al., 2015) recognized the importance of interpersonal interaction to learners/customers' engagement. This factor is also highlighted in this study. ...
Although mobile learning applications play a crucial role in today’s education and can support learning, the low retention rate is a prevalent challenge in mobile learning. Existing studies have found that interpersonal interaction, high expectations, and supportive environment (from an educational perspective) as well as compatibility, interactivity, and usability (from a marketing perspective) can impact learners’ engagement in learning activities and customers’ engagement in mobile applications. However, comprehensive studies investigating learners’ engagement in mobile learning applications from educational and marketing perspectives are rare. To fill the research gap, we analyzed learners’ reviews on five top-ranked lifelong learning applications (Udemy, LinkedIn Learning, Coursera, edX, and Skillshare). Inductive coding was used to identify critical factors impacting learners’ engagement in mobile learning applications, such as usability, availability of learning experiences, features to facilitate learning, interpersonal interaction, and incentives for completion. We further explored specific engagement strategies displayed in the analyzed applications through an analytical evaluation. Besides, this study expands Hew’s model of learners’ engagement and suggests new conceptual relationships between critical factors impacting learners’ engagement, self-determination theory, and learners’ engagement.
... However, despite the rapid adoption of S&G apps and their significant contribution to retail innovation, there exists a critical gap in understanding the full spectrum of their impact on consumer behavior and the retail ecosystem. This is particularly the case in terms of the mismatch between customer expectations and the practical utility of retail apps (Dinner et al., 2015;Lee and Kim, 2018). ...
Purpose
This study aims to investigate the “dark side” of scan and go (S&G) apps as part of the shopping journey, and the subsequent impacts on consumer behavior.
Design/methodology/approach
This study utilizes a phenomenological approach. Data were collected from online reviews, semi-structured interviews and focus group discussions to explore the negaffordance of using in-store S&G apps. Thematic analysis was employed to develop a conceptual model of the customer journey.
Findings
The conceptual model highlights the complex interplay between technology, and the consumer and digital retail environment across three stages include Navigating the Nexus, Empowered Expeditions and Digital Diaspora of the shopping journey. The findings contribute to both theoretical and practical knowledge and offer insights into how S&G technology influences customer experiences.
Originality/value
Theoretically, this research expands the concept of negative affordances in the digital retail context by introducing “negaffordance” as a critical aspect of technology that hinders rather than facilitates the achievement of customer goals. Practically, it suggests enhancements in the design of apps to mitigate negaffordance, and it highlights suggestions made by consumers such as the introduction of a community-centric approach to customer issues. This research underscores the urgent need for retailers to align technological consistency with consumer goals to mitigate the challenges posed by S&G technology.
... However, there has been some research that examines the relationship between sales and app usage. Dinner et al. (2015) gained access to information about a set of clients who had downloaded the retailer's app and found that accessing the app was related to purchases, both online and offline. Van Heerde et al. (2019) also gained access to a sample of clients who had downloaded a company's app, allowing them to compare sales between those app users and non app users. ...
We investigate applying and extending an exhaust data framework, using an empirical analysis to explore and compare different predictive analytic capabilities of both internal and external exhaust data for estimating sales. We use internal exhaust data that explores the relationship between app usage and web traffic data and estimation of sales and find the ability to predict sales at least 4 days ahead. We also develop predictive models of sales, using external data of Google searches, extending the previous research to include additional macroeconomic Google variables and Wikipedia pageviews, finding that we can predict at least 4 months ahead, suggesting a portfolio of exhaust data be used. We introduce the roles of internal and external exhaust data, direct and indirect exhaust data and transformed exhaust data, into an exhaust data framework. We examine what appear to be different levels of information fineness and predictability from those exhaust data sources. We also note the importance of the types of devices (e.g., mobile) and the types of commerce (e.g., mobile commerce) in creating and finding different types of exhaust. Finally, we apply an existing exhaust data framework to develop macroeconomic data exhaust variables, as the means of capturing inflation and unemployment information, using Google searches.
... Balasubramanian et al. (2002) conceived of mobile commerce as enabling ultimate flexibility in both time and space. The development of B2B mobile apps has been shown to increase engagement and purchasing by customers both online and offline (Dinner et al., 2015). These apps can function as either a complement or replacement to existing sales channels (Swani, 2021) as well as facilitate mobile or automated payment (Kumar et al., 2018). ...
Abstract
Purpose
While few studies have examined business-to-business (B2B) mobile application (app) usage, none have examined the challenges in developing these technological assets. This study aims to examine B2B marketing executives’ perceptions regarding benefits, barriers and facilitators in app development.
Design/methodology/approach
A survey of 311 B2B marketing executives at selling firms in the USA was conducted to identify key themes related to the benefits, barriers and facilitators in developing B2B apps. The research featured “open-ended” questions exclusively, and advanced textual and thematic analysis of executives’ responses produced several key themes.
Findings
Results show that the perceived benefit of lowering customer servicing and costs drives development more so than trying to realize new revenue opportunities (e.g. “saving” vs. “making” money). Achieving internal buy-in/participation was perceived as a larger barrier than the commitment of financial resources. Additionally, training and education were viewed as the strongest facilitators of an app’s success over its design and functionality. Implications for B2B firms are discussed.
Research limitations/implications
The open-ended format of this research captures a greater breadth of perspectives at the expense of more granular analysis of any particular issue.
Originality/value
The themes generated from the responses offer novel insights into the benefits sought in developing an app, as well as the technological, organizational and environmental factors that act as barriers and facilitators. The open-ended format of this research captures a greater breadth of perspectives at the expense of a more granular analysis of any particular issue.
... [7] H1: Entertainment has a significant positive influence on youth engagement on Instagram mobile app. [8] ...
As a relatively new social networking site(SNS), Instagram’s user database has been growing at a staggering rate since it was first launched in 2010. Marketing practitioners have been making efforts on this increasingly popular mobile image(and video) capturing and sharing services to reach the end-users, more importantly, to build lasting relationship with them.This study follows literature study, positive worldview, and utilized contextual investigation plan. The information was gathered by qualitative substance investigation strategy through passing questionnaire. A questionnaire was conducted to collect primary data and secondary data the study sample consisted of 104 respondents. Therefore, these significantly affect the adherents, likes, and remarks, for consumer engagement. The variables that are considered for the study are customer engagement, perceived value, social value, ease of use. As per the result of the study perceived value, social value, ease of use have shown positive influence on the youth engagement.
... Despite the prevalence of mobile apps, there is limited research about performance metrics to understand mobile app usage behavior. Particularly regarding shopping apps and websites, purchasing as an outcome variable has been researched profusely (Dinner et al., 2015;Narang & Shankar, 2019), while the browsing behavior itself has not received as much attention. We focus on two mobile app performance metrics-shopping app stickiness and shopping app usage time-that are widely used in the field as key performance metrics in the mobile app context (Braze, 2016;McKinsey & Company, 2019). ...
Mobile shopping is on the rise, and the main channel of social media has now shifted from online to mobile. We aim to understand the role of social media apps in driving mobile shopping. Specifically, we examine two performance metrics for mobile shopping—shopping app stickiness and usage time—and classify social media apps into broadcasting and narrowcasting ones. Our empirical analyses using mobile panel data reveal that the usage time of both types of social media apps increases shopping app stickiness. As for shopping app usage time, broadcasting app usage time has a positive impact, while narrowcasting app usage time has a negative impact. We also find that the impact of broadcasting app usage is greater than that of narrowcasting app usage. Furthermore, offline social interactions weaken the effect of social media usage on shopping app stickiness and that of broadcasting app usage on shopping app usage time.
The authors investigate the impact of customers’ mobile app adoption on grocery shopping behaviors. Specifically, they investigate the cannibalization of existing physical and online channels by the newly adopted mobile app and evaluate changes in households’ total expenditures at the focal chain. They find that households adopting the mobile app marginally decrease their spending in physical stores, but considerably increase their expenditures and shopping trips through the mobile app. They present evidence that the mobile app plays a synergistic role for customers who never used a digital shopping channel. Lastly, the authors find a competitive encroachment effect by the mobile app. They find the impact of mobile app adoption is greater in markets where the focal chain faces more intense competition from a nearby competitor.
Media attribution is the assignment of a percentage weight to each media touchpoint a consumer is exposed to prior to purchasing. Many firms consider using attribution to allocate media budgets, particularly for digital media, but an important question is whether this is appropriate. An initial hurdle when answering this question is that, despite the surge in interest for media attribution in marketing academia and practice, attribution does not have an agreed formal definition. Therefore, this paper proposes an attribution formulation based on the relative incremental contribution that each medium makes to a purchase, taking into account advertising carryover and interaction effects. The formulation shows that attribution is proportional to the marginal effectiveness of a medium times its number of exposures. This means that often-used media will have high attribution weights. However, the profit-maximizing allocation for a fixed budget is a function of advertising effectiveness, but not a function of past exposure levels. By offering analytical derivations and studying simulated and empirical data, the paper shows how attribution can offer misleading insights on how to allocate resources across media. Moreover, the empirical example demonstrates that substantial gains in purchase probability can be made using profit-maximizing allocation compared with attribution-based allocation.
Continual innovation and new technology are critical in helping retailers’ create a sustainable competitive advantage. In particular, shopper-facing technology plays an important role in increasing revenues and decreasing costs. In this article, we briefly discuss some of the salient retail technologies over the recent past as well as technologies that are only beginning to gain traction. Additionally, we present a shopper-centric decision calculus that retailers can use when considering a new shopper-facing technology. We argue that new technologies provide value by either increasing revenue through (a) attracting new shoppers, (b) increasing share of volume from existing shoppers, or (c) extracting greater consumer surplus, or decreasing costs through offloading labor to shoppers. Importantly, our framework incorporates shoppers by considering their perceptions of the new technology and their resulting behavioral reactions. Specifically, we argue that shoppers update their perceptions of fairness, value, satisfaction, trust, commitment, and attitudinal loyalty and evaluate the potential intrusiveness of the technology on their personal privacy. These perceptions then mediate the effect of the technology on shopper behavioral reactions such as retail patronage intentions and WOM communication. We present preliminary support for our framework by examining consumers’ perceptions of several new retail technologies, as well as their behavioral intentions. The findings support our thesis that shopper perceptions of the retailer are affected by new shopper-facing technologies and that these reactions mediate behavioral intentions, which in turn drives the ROI of the new technology.
Firms increasingly offer engagement initiatives to facilitate firm–customer interactions or interactions among customers, with the primary goal of fostering emotional and psychological bonds between customers and the firm. Unlike traditional marketing interventions that are designed to prompt sales, assessing returns on engagement initiatives (RoEI) is more complex as sales are not the primary goal and often direct sales are not associated with such initiatives. To assess RoEI across varying institutional contexts, the authors propose a methodological framework and empirically implement the framework to investigate a business-to-business mobile app that a tool manufacturer provides for free to engage its buyers. The data include sales by buyers who adopted the app over 15 months, as well as a control group of buyers who did not adopt. The results from a difference-in-differences specification, together with selection-on-observables and –unobservables, show that the app increased the manufacturer's annual sales revenues by 19.11%–22.79%; even after accounting for development costs, it resulted in positive RoEI. This RoEI was higher when buyers created more projects using the app, so customer participation intensity appears to underlie RoEI. This article contributes to engagement literature by providing a methodological framework and empirical evidence on how the benefits of engagement initiatives materialize.
The difference and system generalized method-of-moments estimators, developed by Holtz-Eakin, Newey, and Rosen (1988, Econometrica 56: 1371–1395); Arellano and Bond (1991, Review of Economic Studies 58: 277–297); Arellano and Bover (1995, Journal of Econometrics 68: 29–51); and Blundell and Bond (1998, Journal of Econometrics 87: 115–143), are increasingly popular. Both are general estimators designed for situations with “small T, large N″ panels, meaning few time periods and many individuals; independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; fixed effects; and heteroskedasticity and autocorrelation within individuals. This pedagogic article first introduces linear generalized method of moments. Then it describes how limited time span and potential for fixed effects and endogenous regressors drive the design of the estimators of interest, offering Stata-based examples along the way. Next it describes how to apply these estimators with xtabond2. It also explains how to perform the Arellano–Bond test for autocorrelation in a panel after other Stata commands, using abar. The article concludes with some tips for proper use.
The authors highlight the need for and develop a framework for engagement by reviewing the relevant literature and analyzing popular- press articles. They discuss the definitions of the focal constructs-customer engagement (CE) and employee engagement (EE)in the engagement framework, capture these constructs' multidimensional, and develop and refine items for measuring CE and EE. They validate the proposed framework with data from 120 companies over two time periods, and they develop strategies to help firms raise their levels of CE and EE to improve performance. They also observe that the influence of EE on CE is moderated by employee empowerment, type of firm (business-to- business [B2B] vs. business-to-consumer [B2C]), and nature of industry (manufacturing vs. service); in particular, this effect is stronger for B2B (vs. B2C) firms and sen/ice (vs. manufacturing) firms. The authors find that although both CE and EE positively influence firm performance, the effect of CE on firm performance is stronger. Furthermore, the effect of CE and EE on performance is enhanced for B2B (vs. B2C) and for service (vs. manufacturing) firms.
Retailers are dynamic in nature, and their strategies keep evolving with changing scenarios and availability of new technologies. In the current scenario, there is a need for a comprehensive and organizing framework for retailers to develop and implement a complex set of strategies. In this article, we broadly categorize retailers’ implementation of strategies at four levels—market, firm, store and customer. The four-level categorization has been done using a triangulation approach consisting of inferences from previous literature, interviews with practitioners, and reviewing popular press. In the future, retailers will expand to even more countries, and there will be plenty of scope for using advanced technologies and big data. This organizing framework accommodates for any such changes as well as guides retailers about ways of increasing profitability in the future. In this article, we also provide generalized expectations of strategies under each level which not only can be used by researchers as a direction of future research but also by practitioners to understand and implement their strategies in an effective and efficient way.
