Measuring and forecasting mobile game app engagement

Monetization strategies in the large and strongly growing mobile app space must go beyond traditional purchase revenue as most mobile apps are now free to download. One key marketing innovation allows mobile app publishers to monetize ongoing engagement — in-app advertising.We study ongoing user engagement with a mobile app after the initial download decision using the $40 billion mobile gaming industry as an example. Our study investigates and forecasts user engagement after the initial download aiming to help publishers to monetize their engagement via in-app advertising. We leverage a novel dataset containing user-level engagement for 193 mobile games and propose a hierarchical Poisson model on a mobile-game level. We find significant usage heterogeneity across the mobile games studied and generate forecasts publishers can use when trying to monetize engagement via pre-sold contracts.     

Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment

A crucial decision firms face today is which channels they should make available to customers for transactions. We assess the revenue impact of adding bricks-and-mortar stores to a firm's already existing repertoire of catalog and Internet channels. We decompose the revenue impact into customer acquisition, frequency of orders, returns, and exchanges, and size of orders, returns, and exchanges. We use a multivariate baseline method to assess the impact of adding the physical store channel on these revenue components. As hypothesized, store introduction cannibalizes catalog sales and has much less impact on Internet sales. Also as hypothesized, returns and exchanges increase. Interestingly, transaction sizes of purchases, returns, and exchanges do not change. The “availability effect” produces a net increase in purchase frequency across channels. This more than compensates for increased returns, producing a net increase in revenues of 20% by adding the store channel. Our findings yield a deeper understanding of the revenue relation between channels, and of the dynamic cross-channel effects of marketing actions.     

Beyond the Usefulness of Branded Applications: Insights from Consumer–Brand Engagement and Self‐construal Perspectives

Branded mobile applications (apps) present one of the most promising opportunities for marketers to reach current and potential customers, sell products or services, and facilitate customer engagement with brands. This study aims to explore how branded apps influence consumers’ brand repurchase intention and continuance usage intention. Integrating the utilitarian view from information systems research and the view of consumer–brand engagement from marketing research, a complementary engagement path alongside the utilitarian path was devised and tested in order to elucidate consumer perceptions toward branded apps. Independent self‐construal and interdependent self‐construal moderate relationships along the utilitarian path and engagement path, respectively. Data collected from 637 respondents support most of the proposed hypotheses. Results show that the engagement path has more influence on continuance intention and equal influence on repurchase intention when compared to the utilitarian path. Findings show that apps users have different thoughts along each of the two paths, depending on their self‐construal. The study's findings also provide app designers and marketers with new perspectives on how to better design branded apps.     

Determining factors and impacts of the intention to adopt mobile banking app in Cameroon: Case of SARA by afriland First Bank

This study aims to know what are the factors determining the adoption of M-Banking app among customers in Cameroon. In other words, what are the factors that influence users in their decisions to adopt and use a system or technology such as the MBanking app, and indirectly, what is the impact of this use on both the customers and financial inclusion? The research model developed relying on a combination of Technology Acceptance Model (TAM ), Unified Theory of Acceptance and Use of Technology ( UTAUT2 ), Information System Success Model ( ISSM ), and Protection Motivation Theory ( PMT ) and other constructs; it was then tested with a sample of 223 users of the “ SARA” M-Banking app of the financial institution called “ Afriland First Bank” . Findings revealed that: (1) utilitarian expectation, hedonic motivation, and status gain, habit, and perceived privacy concern have a significant influence on the intention to adopt M-Banking apps; and (2) the exploitative/explorative use of this technology has an impact on user’s loyalty and satisfaction but also contributes strongly to fostering financial inclusion in Cameroon. Also, the Multi-group analysis was performed on the sample using 2 gender-based groups (males, n=121; females, n=102).     

Health as a Means Towards Profitable Ends: mHealth Apps,User Autonomy,and Unfair Commercial Practices

In this article, we discuss mHealth apps and their potential to influence the user’s behaviour in increasingly persuasive ways. More specifically, we call attention to the fact that mHealth apps often seek to not only influence the health behaviour of users but also their economic behaviour by merging health and commercial content in ways that are hard to detect. We argue that (1) such merging of health and commercial content raises specific questions concerning the autonomy of mHealth app users, and (2) consumer law offers a promising legal lens to address questions concerning user protection in this context. Based on an empirically informed ethical analysis of autonomy, we develop a fine-grained framework that incorporates three different requirements for autonomy that we call “independence,” “authenticity,” and “options.” This framework also differentiates between three different stages of mHealth app use, namely installing, starting to use, and continuing to use an app. As a result, user autonomy can be analysed in a nuanced and precise manner. Since the concept of autonomy plays a prominent, yet poorly understood role in unfair commercial practice law, we utilize the ethical analysis of autonomy to guide our legal analysis of the proper application of unfair commercial practice law in the mHealth app domain.     

The current and future sales impact of a retail frequency reward program

This research presents an empirical study of the impact of a retail frequency reward program on store sales. We examine both the “points pressure,” or short-term impact, and the “rewarded behavior,” or long-term impact. The points-pressure impact is due to forward-looking customers increasing their purchase levels in order to earn the reward. The rewarded-behavior impact is evidenced as purchases above baseline levels after an individual has received a reward and could result from either behavioral learning reinforcement or positive affect resulting from the reward. We investigate a turkey reward program that awarded free turkeys to shoppers who accumulated the required sales levels during an 8-week period. We find both a points-pressure and rewarded-behavior impact. These effects are statistically significant and managerially relevant in that the program is apparently profitable. The points-pressure impact is especially strong among customers who do not place value on frequent shopper programs that in general deliver immediate price discounts. The key implications are that frequency reward programs of the form, “buy x, then receive xx” can be profitable, are segmentation strategies, and can complement a store's overall frequent shopper program.     

On the monetization of mobile apps

Though the mobile app market is substantial and growing fast, most app providers struggle to monetize apps profitably. Monetizing apps is done in two ways: a) selling advertising space within a free version of the app, and b) selling a paid version, termed freemium or in-app purchase strategy. In this paper, we present a framework for monetization of mobile apps, using two central empirical regularities concerning the relationship between users and their mobile apps: a) Sampling: While consumers have some prior knowledge of their fit with the app, they remain uncertain regarding their exact utility until they are using it; and b) Satiation: The utility of using the app may decrease with time. While work on the monetization of digital goods has largely overlooked the role of satiation and the consequent retention issues, we show that in combination with uncertainty, it elucidates the role of the segments of consumers that download the free vs. paid version of the app, and how to balance these two segments so as to monetize mobile apps. We encounter two distinct scenarios: In the first, advertising drives most of the revenues; while in the second, revenues are driven by the paid version of the app. We explain how uncertainty and satiation affect the prevalence of the respective scenarios and impact the share of revenues from the paid vs free version of the app. We also demonstrate that an app provider can profit from offering a free version with ads even if advertisers are not paying for these ads. In other words, the app provider benefits from offering a “damaged good” version of the app that includes ads, even if this version is free to consumers, and the advertisers are not paying for the ads.     

Price promotions and “freemium” app monetization

The “freemium” model for digital goods involves selling a base version of the product for free, and making premium product features available to users only on payment. The success of the model is predicated on the ability to profitably convert free users to paying ones. Price promotions (or “sales”) are often used in freemium to induce this conversion. However, the causal effect of exposing consumers to such inter-temporal price variation is unclear. While sales can generate beneficial short-run conversion, they may be harmful in the long-run if consumers inter-temporally substitute purchases to periods with low prices, or use them as signals of low product quality. These long-run concerns may be accentuated in freemium apps, where the base version is sold for free, so that sales form extreme price cuts on the overall product combination. We work with the seller of a free-to-play video game to randomize entering cohorts of users into treatment and control conditions in which promotions for in-game purchases are turned on or off. We observe complete user behavior for half a year, including purchases and consumption of in-game goods, which, in contrast to much of the extant literature, enables us to assess possible substitution over time in consumption directly. We find that conversion and revenue improve in the treatment group; and detect no evidence of harmful inter-temporal substitution or negative inferences about quality from exposure to price variation, suggesting that promotions are profitable. We conjecture that the zero price of the base product that makes its consumption virtually costless, combined with the complementarity between the base product and premium features can help explain this. To the extent that this holds across freemium contexts, the positive effects of promotions documented here may hold more generally.

     

The CAGE around cyberspace? How digital innovations internationalize in a virtual world

This paper analyzes some salient factors affecting the internationalization speed of digital innovations by tracking international penetrations of 127 apps at Apple's app store. Although apps are globally available via online platforms, their international penetration is still subject to cultural, administrative, geographic, and economic (CAGE) distances that act as user adoption barriers to impede app internationalization. App developers may overcome these barriers by employing the demand-side strategies of engaging users in value co-creation. We contribute to an improved understanding of internationalization process in a digital context and also extend demand-side perspective to inform international entrepreneurship research.     

The dark side of multiunit discounts: Multiunit discounts reduce rest of basket revenue

Multiunit discounts refer to the practice of offering a discount on purchase of multiple units of a product. An example of multiunit discounts, which are commonly used by retailers, is ‘3 for $10’. While past research suggests that multiunit discounts generate higher sales than per-unit discounts, there is no research on how such discounts affect sales of other products in the store. We argue that consumers exposed to multiunit discounts may purchase the products offered as such to benefit from the deal. These customers, however, will spend less on other products, resulting in lower revenue from the rest of the basket during the shopping trip. Based on theoretical insights, we propose why such an effect could occur and test our arguments using store data and a lab experiment. The findings of this research suggest that multiunit discounts have a multifaceted impact on consumer decision-making. We also discuss the theoretical, managerial, and methodological contributions of this research.     

The Impact of Mobile App Adoption on Cross-buying: The Moderating Roles of Product Category Characteristics and Adoption Timing

With more and more companies introducing mobile apps and consumers using them during the purchase journey, it is increasingly important to understand the consequences of app adoption on behavioral outcomes. This paper investigates the impact of app adoption on the number of additional products purchased by customers (i.e., cross-buying) and how this effect varies across different product categories and different customers. We focus on two key product category characteristics (utilitarian vs. hedonic nature and perceived risk) and on adopters who vary in their adoption timings (early vs. late adopters). Using data from an online retailer and a combination of propensity score weighting with difference-in-differences and Heckman correction estimation techniques, the results show that app adoption has a positive effect on cross-buying overall, but the effect varies greatly across products and consumers. App adoption promotes additional product purchases for hedonic products but leads to less cross-buying for utilitarian products. In addition, early adopters purchase a higher number of additional product categories than late adopters, with this difference decreasing over time and for new consumers compared to existing customers. These results offer novel insights into the behavioral consequences of app adoption and provide managers with useful recommendations for improving the effectiveness of their mobile app investments.     

The effect of search channel elimination on purchase incidence,order size and channel choice

This study investigates the impact of eliminating a search channel on purchase incidence, order size, channel choice and, ultimately, sales and profits. We analyze customer panel data from a large retailer over a five-year period. The retailer conducted a randomized field test in which the firm eliminated its catalog for half of the panel. We find that channel elimination decreases purchase incidence, especially for customers who, before the test, were heavy users of the telephone purchase channel that aligns with the catalog search channel. As expected, channel choice for purchases is shifted toward the internet and away from the telephone channel. Interestingly, order size per purchase increases. We investigate the impact of channel elimination on profits across different customer segments. We calculate a net positive impact because the savings from eliminating the catalog compensate for lower sales revenues.     

Understanding the sequential interdependence of mobile app adoption within and across categories

This research examines the interdependencies in users’ sequential app adoptions within and across diverse app categories. We employ a Zero-inflated Negative Binomial (ZINB) model to analyze a unique, granular, and individual-level mobile app adoption dataset, revealing three main findings. First, users’ app adoption decisions are highly history-dependent and category-specific in a nonlinear fashion. Early adoption can enhance subsequent downloads within the same category for app categories with high needs evolvement and horizontal differentiation (e.g., Game and Education apps). However, it may crowd out subsequent downloads in other categories with low needs evolvement and horizontal differentiation (e.g., Communication and Social media apps). Second, these effects are further moderated by users’ individual characteristics such as app usage tenure and phone price. Third, there exist nontrivial app adoption spillovers across app categories. For example, users’ adoptions of apps with relatively high hedonic values (e.g., Game and Music apps) can suppress their subsequent need for apps with relatively high utilitarian values (e.g., Education and Online banking apps), and vice versa. Together, these results offer novel managerial implications for app developers and platforms to promote apps in different categories based on users’ adoption histories.     

An Assessment of When,Where and Under What Conditions In-Store Sampling is Most Effective

In-store product sampling is a commonly used promotional technique designed to give prospective consumers an opportunity to experience a product prior to purchase. While prior research has documented a positive relationship between short-term sales and perceptual measures of the customer shopping experience, little is known about the long-term impact of sampling or factors that moderate its success. In this paper, we develop an empirical approach that allows us to study the short-term and long-term effects of in-store sampling on both own and competitive products. We apply our approach to six store-level scanner data sets across four different product categories and show that in-store sampling has both an immediate (short-term) and sustained (long-term) impact on sales. We also show that the impact of sampling on sales is moderated by the characteristics of the store conducting the event, and that repeated sampling for a single product leads to a multiplicative increase in its long-term sales performance. We find that, unlike many types of in-store promotion, sampling results in a category expansion effect as opposed to a pure substitution effect. We contrast the immediate and long-term sales patterns for in-store sampling to those of product displays and discuss managerially relevant differences. Finally, we demonstrate incremental profit implications and store selection scenarios for different incremental costs of conducting the in-store events using constrained optimizations.     

Investigating the impact of Internet of Things services from a smartphone app on grocery shopping

This study investigates the impact of Internet of Things (IoT) services from a smartphone app in a retail grocery shopping situation. It examines four variables, namely price, expiry date, quality indicators and offers. All four variables were examined in relation to two levels; traditional information and IoT services. A scenario was arranged whereby 226 participants were to purchase, among other products, fresh salmon in a grocery store using the store's smartphone app. Findings from a conjoint study show that the following IoT services; “updated expiry date”, “aggregated national customer experience index”, and “personalized offer based on product in the basket” evoked the approach and abated avoidance tendencies to explore the smartphone app, while simultaneously increasing the likelihood of buying based on information from the app. The IoT service “Real-time price” had a varied impact on participant approach-avoidance tendencies to interact with the app. Scenario simulation analysis shows that some IoT services can be a deal-breaker in a competitive grocery market. Consequently, analyzing the impact of IoT services through the lenses of approach-avoidance distinction and choice indication can help retail grocery managers develop more effective marketing strategies that deliver convenience to the consumers.     

Can gamification increases consumers’ engagement in fitness apps? The moderating role of commensurability of the game elements

Many app firms have adopted gamification, aiming at making consumers more engaging and loyal. Given the ambivalent evidence on the effectiveness of gamification, this study proposes that the effectiveness of gamification is moderated by the types of game elements, i.e., commensurate and incommensurate. Commensurate elements, such as points, are directly associated with performances such as step counts, and may be perceived by consumers as external incentives to their efforts; whereas incommensurate elements, such as “likes”, are not directly related to performances, and may be considered as avenues to satisfy psychological needs, leading to stronger intrinsic motivation. Results from a longitudinal field study confirm that compared with apps using commensurate elements, apps using incommensurate elements can better help increase intrinsic motivation and further enhance engagement and loyalty.     

The Effects of Channel Experiences and Direct Marketing on Customer Retention in Multichannel Settings

In customer relationship management (CRM), it is critical for managers to understand how and when customers terminate their relationships with the company in order to make more accurate predictions for CLV. However, in many non-contractual settings, customer churn is not easily observed, which presents difficulty for estimating customer retention. In this research, we present a framework for estimating multichannel customer relationship dynamics in a non-contractual setting that flexibly allows for relationship revival and investigates the effects of different channel experiences and marketing communication on retention and profitability. We use a multi-segment, multivariate hidden Markov modeling framework to model three managerially relevant customer behaviors: purchase amount, purchase incidence, and channel choice. Using data from a multichannel clothing retailer, we uncover two latent relationship states that customers migrate to and from — an active state and an inactive state characterized by different levels of purchase frequency, responsiveness to marketing, and profitability. We find that an offline (retail-store) channel can be used to migrate customers from an inactive state to an active state, effectively serving the purpose of “education” or “revival,” whereas an online channel is most effective in keeping the existing active customers active, thus serving the purpose of “retention”. Using counterfactual analysis, we highlight an opportunity for the multichannel firm to optimize marketing strategies to dynamically manage and increase the retention and hence also the value of its customer base.     

How customer engagement in the live-streaming affects purchase intention and customer acquisition,E-tailer's perspective

In the emerging retail market, e-tailers operating in developing economies have to cope with the rapid use of the Internet, new electronic purchasing methods and online selling platforms. However, e-tailers do not understand the effect patterns in which customer engagement on purchase intention and customer acquisition. From e-tailers’ perspective, this study explores how customer engagement behaviors are related to both purchase intention and customer acquisition. We obtained live streaming data in the mature e-tail live streaming market environment and found empirical evidence supporting the conceptual framework through regression model analysis. The analysis results show that the specific indicators of the customer engagement are not all positively related to customer purchase intention and customer acquisition, and it is worth noting that the influence of “like” behavior on customer acquisition is no statistical significance. This is expected to encourage e-tailers to rethink their focus on customer acquisition and sales enhancement digital strategies as they operate in emerging markets.     

Is the Daily Deal Social Shopping?: An Empirical Analysis of Customer Panel Data

Shortly after Groupon started its business in 2008, selling one deal a day with substantial price discounts, daily-deal sites became new online shopping places for many people. Starting with Groupon, most daily-deal sites required that voucher sales be higher than a predetermined number before deals become active. This feature, known as the “tipping point,” was a unique characteristic of the daily-deal business and is identified as one of the most prominent features of social shopping. Most daily-deal sites also required that a redemption period start after a deal was over and be fixed, usually 90 days, presumably to maximize the promotional effect of deals by encouraging rapid voucher redemption. The question remains, however, whether such features actually contributed to the success of the daily-deal industry. Using individual-level panel data from a major daily-deal site in Korea, we analyze whether consumers' purchase and redemption behaviors were affected by these features and how consumers changed their behaviors as they continued to purchase and redeem vouchers over time. We find that the presence of the tipping point did not boost voucher sales and likely deterred new customers from buying deals right away. We also find that new customers tended to redeem their vouchers quickly, and this likely caused the small businesses that offered deals to become overwhelmed. It is not surprising, given our findings, that both Groupon and the Korean daily deal site abandoned the use of the tipping point and modified redemption rules.     

Interactivity,Inspiration, and Perceived Usefulness! How retailers’ AR-apps improve consumer engagement through flow

This study investigates the antecedents and outcomes of consumer engagement through AR apps and suggests a new conceptual model. The purpose of the paper is to examine how consumer engagement is shaped via AR apps, which eventually leads to a positive attitude towards brand and brand usage intent. To this end, a face-to-face survey instrument was administered to 350 participants in Turkey, where participants tried an AR app and then answered a questionnaire. The structural equation modeling (SEM) and Hayes' Process analyses were applied to test the hypotheses and moderated mediation relationships. Findings showed that interactivity and inspiration are two major antecedents of consumers' flow experience. The flow experience with AR can generate favorable attitudes towards AR apps and more trust in AR apps, which trigger consumer engagement with AR apps and then improve brand attitude and brand usage intent. The outcomes of flow experience with AR (i.e., attitude and trust) mediate the relationship between flow and engagement. Although perceived usefulness increases the effect of consumers' attitudes towards AR on engagement, it has no moderating effect on the relationship between trust in AR and engagement. Furthermore, the results of Hayes' Process revealed that the indirect effect of flow on consumers’ engagement with AR through attitude towards AR is moderated by perceived usefulness. So that, if AR marketers aim to strengthen the link between consumer flow experience and engagement via attitudes towards AR, they should therefore consider enhancing the perceived usefulness of AR. Surprisingly, perceived usefulness had no moderating effect on the indirect relationship between flow and engagement via trust. Finally, this paper discusses both the theoretical and managerial implications.