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GEO-Conquesting: Competitive Locational Targeting of Mobile Promotions
Abstract
As consumers spend more time on their mobile devices, a focal retailer's natural approach is to target potential customers in close proximity to its own location. Yet focal (own) location targeting may cannibalize profits on inframarginal sales. This study demonstrates the effectiveness of competitive locational targeting, the practice of promoting to consumers near a competitor's location. The analysis is based on a randomized field experiment in which mobile promotions were sent to customers at three similar shopping areas (competitive, focal, and benchmark locations). The results show that competitive locational targeting can take advantage of heightened demand that a focal retailer would not otherwise capture. Competitive locational targeting produced increasing returns to promotional discount depth, whereas targeting the focal location produced decreasing returns to deep discounts, indicating saturation effects and profit cannibalization. These findings are important for marketers, who can use competitive locational targeting to generate incremental sales without cannibalizing profits. Although the experiment focuses on the effects of unilateral promotions, it represents an initial step in understanding the competitive implications of mobile marketing technologies.
... In contrast, mobile push refers to mostly automated, firm-initiated notifications that appear on devices' lock screens (Xu et al. 2009). Although mobile pull is the default mechanism in top iOS shopping and retail apps in the United States, with apps presenting coupons and discounted products to consumers via content feeds, approximately 60% of these apps offer additional push notifications. 2 Despite the prevalence of mobile pull among those shopping apps, most literature on mobile targeting has primarily focused on mobile push delivery (Luo et al. 2014, Fong et al. 2015, Ghose et al. 2019a. As a result, understanding the effects of utilizing mobile push in addition to mobile pull delivery remains a crucial yet unexplored question for both firms and researchers. ...
... This framework is informed by data from a large randomized experiment, allowing us to examine the relative differences between the two mobile content delivery mechanisms, thereby providing a more comprehensive understanding of consumers' responses. This complements previous literature on mobile targeting, which has predominantly focused on mobile push (Luo et al. 2014, Fong et al. 2015. ...
... Third, we examine longer-term redemption behavior and actual in-store store expenditures for both delivery mechanisms, monitoring consumers up to four weeks after receiving the coupon. Accounting for a longer time horizon complements mobile targeting research (Fong et al. 2015, Dubé et al. 2017, as we show that shorter time horizons may overestimate the relative effectiveness of mobile push. ...
Firms have two distinct options when delivering content to consumers’ mobile devices: mobile push and mobile pull. Mobile push delivers firm-initiated (ad) content directly to consumers, while mobile pull requires consumers to initiate requests for (ad) content. This study tests the impact of mobile push and mobile pull on consumers’ coupon redemption behavior in a large-scale randomized field experiment in a geo-conquesting setting, targeting customers located around competitor retail stores with mobile coupons to drive them to stores of the focal retailer. The results show that mobile push increases coupon redemption rates by 6.0%, with substantial heterogeneity based on app-specific use experience and store density: App-specific use experience negatively moderates the effect of mobile push delivery on redemptions, likely because both usage experience and push notifications reduce app-specific search costs, thereby acting as substitutes for one another. In areas with higher store density, the positive effect of mobile push delivery on the redemption likelihood is greater, suggesting that push notifications can highlight the focal coupon among alternative store choices, thereby reducing consumer switching costs. These findings have important implications for retailers and brands in creating competitive mobile targeting campaigns that effectively leverage both mobile push and pull delivery mechanisms.
... Due to the unique GPS data provided by mobile devices (Shankar and Balasubramanian, 2009), many have focused on quantifying the value of location-based targeting. Early work (Ghose et al., 2013;Luo et al., 2014;Fong et al., 2015) demonstrated the importance of geographic proximity in mobile promotion effectiveness. In particular, Luo et al. (2014) found significant interaction effects between location and temporal targeting: while same-day mobile promotions were most effective for proximal consumers, prior-day promotions were most effective for non-proximal consumers. ...
... Though a firm might set its budget specifically to target a certain number of impressions or clicks, it cannot perfectly account for the behavior of other firms, whose bidding may impact impressions, clicks, and installs. The context of mobile apps introduces further complexity, including location (Ghose et al., 2013;Luo et al., 2014;Fong et al., 2015), product utility (Bart et al., 2014), and personalization (Zhang et al., 2019). Consumer heterogeneity also has substantial implications, especially in the mobile gaming industry where consumer spending is highly skewed with a small minority generating a majority of revenue. ...
Prior spending shutoff experiments in search advertising have found that paid ads cannibalize organic traffic. But it is unclear whether the same is true for other high volume advertising channels like mobile display advertising. We therefore analyzed a large-scale spending shutoff experiment by a US-based mobile game developer, GameSpace. Contrary to previous findings, we found that paid advertising boosts organic installs rather than cannibalizing them. Specifically, every $100 spent on ads is associated with 37 paid and 3 organic installs. The complementarity between paid ads and organic installs is corroborated by evidence of temporal and cross-platform spillover effects: ad spending today is associated with additional paid and organic installs tomorrow and impressions on one platform lead to clicks on other platforms. Our findings demonstrate that mobile app install advertising is about 7.5% more effective than indicated by paid install metrics alone due to spillover effects, suggesting that mobile app developers are under-investing in marketing.
... Third, the present study brings a unique perspective by considering the physical environment in terms of the agglomeration effect on shaping the effects of coupon characteristics on coupon acquisition and subsequent redemption. Previous research on the integration of online and offline channels has centered on examining the impact of online promotion on offline sales (Danaher et al. 2015;Fong et al. 2015). We add to this literature stream by exploring how offline agglomeration may reversely affect online promotion performance via its moderation effects. ...
... Moreover, our study is among the first attempts to link offline environment characteristics to online promotion. Prior OM literature on business models integrating online and offline channels has primarily concentrated on investigating the influence of online promotions on offline sales (Danaher et al. 2015;Fong et al. 2015). Our study bridges this gap by examining the reverse influence of offline agglomeration on online promotions through its moderation effects. ...
Local merchants have implemented coupon promotions to attract consumer traffic and improve product sales. Drawing upon signaling theory, this paper examines how a social characteristic of a coupon (i.e., group consumption) influences coupon acquisition and subsequent coupon redemption, along with how such relationships are further influenced by offline agglomeration (i.e., density and product agglomeration). Specifically, we argue that group consumption increases coupon acquisition, which in turn increases coupon redemption, with coupon acquisition serving as a mediator in the relationship. These relationships, however, are contingent upon offline agglomeration signals. Using a large panel data set from a prominent group buying platform, we collect 121,909 observations to test our theoretical model. The findings reveal a positive relationship between group consumption and coupon acquisition and a positive relationship between coupon acquisition and redemption, while the relationship between group consumption and coupon redemption is fully mediated by coupon acquisition. Furthermore, we find that the effect of group consumption on coupon acquisition is strengthened by density agglomeration but attenuated by product agglomeration. The effect of coupon acquisition on redemption is reinforced by density agglomeration. These findings offer valuable implications for local merchants who are seeking to optimize their coupon promotions.
... The data collected from mobile apps provide businesses with highly detailed individual-level information, enabling in-depth analysis of the relationship between consumers' app usage and their shopping activities (eMarketer, 2019;Vanvani, 2022). The mobile marketing data used in most previous research articles (Luo et al., 2014;Fong et al., 2015;Andrews et al., 2016), which observe consumer responses to mobile promotions from SMS messages, are usually cross-sectional. In contrast, a mobile app can consistently track a consumer's sequential activities and responses to various types of promotions over time. ...
... Most research on mobile marketing uses data from mobile carriers through SMS messages where observed consumer responses to mobile promotions are cross-sectional. For example, targeting consumers temporally and geographically by offering a substantial discount can increase sales (Luo et al., 2014); targeting competitive locations with discounts can generate incremental sales (Fong et al., 2015); location and time of mobile-coupon delivery and expiry length affect coupon redemption (Danaher et al., 2015); targeted mobile ads to commuters in more crowded subway trains are more effective than in less crowded ones (Andrews et al., 2016); Consumer responses to mobile promotions are higher and faster in sunny weather than cloudy weather (Li et al., 2017); Only a few recent studies have used mobile data where the history of marketing activities and consumer responses is sequentially recorded over time for each consumer. Among them, Ghose et al. (2019) find that the mobile targeting strategy based on physical-movement trajectories is more effective in increasing redemption and transaction amounts; Fong et al. (2019) find that targeting promotions can decrease purchases of unpromoted categories while increasing sales of promoted categories on an e-book mobile app. ...
How effective are push promotions through mobile apps for brick-and-mortar retailers and what strategies can improve the performance of targeted push marketing? To address these questions, we develop a multivariate event history model to evaluate the effects of behavior and location-based push promotions on shoppers’ app usage and offline shopping activities. Our study generates new insights into mobile app promotions and offline shopping. We find that behavior-based pushes have a higher impact on consumer responses before a shopping trip than during a trip, and their effects vary significantly across different types of retailers. The effects of pushes are positively correlated with shoppers’ propensities of app pulls and mall visits, which suggests that timing the delivery of pushes can make them more effective. Furthermore, location-based pushes exhibit stronger positive effects on app pulls and coupon outclicks during a shopping trip than behavior-based pushes, even after shoppers receive the latter before the trip, which shows that behavior and location-based pushes are not substitutable. We demonstrate through simulations that our model enables marketers to design more effective mobile targeting strategies by exploiting heterogeneous consumer responses. Addressing potential endogeneity by controlling for the information used for customer selection in the customer’s response functions, our proposed model can be applied to many empirical problems involving event history data.
... With practical and theoretical implications in mind, this study aims to fill some important gaps in the LBA literature. Prior research identifies that LBA is positively associated with returns to discount (Fong et al., 2015), purchase intention (Gazley et al., 2015;Luo et al., 2014), and brand romance (Mpinganjira et al., 2019). However, to date, an explanation as to why and how LBA affects brand engagement is missing in the literature (Bernritter et al., 2021). ...
... Literature has highlighted the importance of spatial proximity in advertising effectiveness. For example, consumers who receive a promotional offer from a store in closer proximity purchase more products than those who received the similar offer at a different location (Fong et al., 2015). Similarly, proximity to the advertised brand or product increases consumers' intention to buy those products (Bues et al., 2017). ...
Location-based advertising is continuing to grow in popularity among brands and retailers to deliver marketing messages and promotions. However, little is known about how and why these ads generate brand engagement. This study fills this gap. This paper indicates that two important features of location-based advertising (LBA)-location congruency and personalization-influence brand engagement and that the underlying mechanism behind this relationship is consumer brand identification. Further, it shows it is not only the personalization feature of these ads that increases its effectiveness, but the ad should also be location-congruent to make it effective. The conceptual model is tested by manipulating location-congruency and personalization features of LBA in two different contexts. This study is among the first to provide empirical evidence that LBA increases brand engagement and to uncover the theoretical mechanism of this relationship.
... Einzelhändler nutzen mobile Apps als digitales Marketing-und Vertriebsinstrument. So lassen sich Apps nicht nur zum Aufbau einer Händlermarke nutzen, 5 Funktionen von Smartphone-Apps im deutschen … sondern eröffnen durch Push Notifications -und in Kombination mit dem Standort der Nutzerinnen und Nutzer -Location-based Marketing einen direkten Kommunikationskanal, um relevante Werbung auszusteuern (Fong et al., 2015;Freyne et al., 2017;Bidargaddi et al., 2018;Banerjee et al., 2020). Im Fall des Location-based Marketing scheinen insbesondere Nutzerinnen und Nutzer mit einer hohen Erlebnisorientierung eine besonders hohe Nutzungsintention aufzuweisen (Kang et al., 2015). ...
Zunehmend bieten deutsche Einzelhändler Apps an, um das stationäre Einkaufserlebnis durch digitale Services zu verbessern. Gleichzeitig existiert Forschung, die sich mit dem Einsatz von Apps im Einzelhandel, etwa mit Blick auf Anforderungen Konsumierender oder mit konkreten Funktionen auf technischer Ebene beschäftigt. Dieses Buchkapitel untersucht, inwiefern die bestehenden Erkenntnisse der Forschung mit der praktischen Realität übereinstimmen, und betrachtet dazu 42 Apps der 50 größten deutschen Einzelhändler hinsichtlich Funktionen im Kontext des stationären Einkaufens. Insgesamt werden 23 Funktionalitäten identifiziert. Die Ergebnisse zeigen, dass ein großer Teil der Apps etwa einen Storefinder, eine Einkaufsliste und ein Loyalty-Programm anbietet. Gamification oder Augmented Reality dagegen werden in der Literatur stark diskutiert, finden bisher jedoch kaum praktische Anwendung. Praktische Handlungsimplikationen und weiterführende Forschungsvorhaben werden skizziert.
... In one study of a mobile e-book platform, mobile promotions had heterogeneous effects depending on whether the promoted product was similar to something the consumer bought before or not (Fong et al., 2019). Mobile ads can be more effective in crowded areas (Andrews et al., 2016) or while consumers are on public transit (Ghose et al., 2019), but it depends on competitive dynamics at their location (Fong et al., 2015). Other related research has found that SMS messages can be effective (Luo et al., 2014), but it also depends on the time, location, and redemption timeline (Danaher et al., 2015). ...
Availability bias influences decisions by how readily certain events, objects, or people can be brought to mind. This “ out of sight, out of mind ” effect depends on whether these elements are present during decision-making. To promote sustainable food consumption, understanding this bias is crucial, as marketing promotions exhibit heterogeneity in terms of the salience, recency, and frequency with which they are administered. Our research examines the impact of different promotions that vary across these three dimensions on the demand for plant-based food products and their interaction with price sensitivity. We analyzed weekly purchases of 21 plant-based beverage brands across 242 stores in Quebec, Canada, from 2015 to 2016 using two-level mixed-effect regression models across four studies. Results from Study 1 indicate that flyer promotions that had high salience, recency, and frequency were most effective (B = 0.417, p < 0.001), compared to mobile promotions with low salience and variable recency and frequency (B = 0.233, p < 0.001) or in-store promotions of high salience but low recency and frequency (B = 0.073, p < 0.001). Of the mobile promotions evaluated in Study 2, advertisements promoting bonus loyalty points were the most effective in driving demand (B = 0.776, p < 0.001), followed by general advertisements (B = 0.125, p < 0.001). Demand was elastic across all models, and most promotions increased price sensitivities in Studies 3 and 4 regardless of their salience, recency, or frequency. The findings highlight the synergistic effect of promotional elements delivered both before and at the decision-making moment in overcoming availability bias to boost demand for sustainable products. However, frequent promotions may increase price sensitivities due to anchoring to promotional prices. This article has implications for theory and practice.
... Under an existing loyalty program, consumers become more responsive to price discounts Horváth and Fok (2013) Temporary The effect of cross-price promotion is the strongest for national brand/private label when consumer and competitive dynamics are considered Fong et al. (2015) Temporary Return increases in response to promotional discount in competitive locations Breugelmans and Campo (2016) Temporary ...
Purpose:
While a price discount might encourage potential (first-time) customers seeking higher status to buy a masstige brand; it might deter existing (repeat) customers from purchasing the brand due to a decline in perceived status. Such a paradoxical effect of price discounts on masstige brand’s purchase requires a detailed investigation into whether masstige brands should offer price discounts
and if so, how to communicate such discounts. Current research investigates this phenomenon.
Design/methodology:
Four experimental studies were executed. Study 1 investigated the impact of monetary discount (absent vs. present) on the purchase intention of masstige brands for different customer types (potential vs. existing). Study 2 investigated the mediating role of perceived status. Study 3 examined the effectiveness of metaphoric communication of monetary discounts (absent vs. present) on the masstige brand’s purchase. Study 4 tested the moderating effect of customers’ need for cognition.
Findings:
Overall, monetary discounts positively affect the purchase intention of masstige brand; however, the effect is negative for existing customers and positive for potential customers owing to differences in perceived status these customer groups experience (positive for potential and negative for existing customers). Metaphoric communications of monetary discounts restrict the declining purchase intention and status perception of existing customers besides keeping the potential customers’ purchase intention intact.
Research limitations:
This research is confined to a particular country limiting the generalizability of the study’s findings. Further, this research is cross-sectional in nature.
Practical implications: The findings of this research provide valuable insights and actionable recommendations for masstige brands to effectively leverage price discounts; especially in the emerging markets.
Originality/value:
To date, the question of whether or not masstige brands should offer price discounts and if so, how to communicate such discounts remains opaque. This is the pioneering study exploring this phenomenon.
Keywords
Masstige; Price discount; Social status; Metaphor; Need for cognition; Luxury
... Geo-targeted offers and discounts leverage location-based technology and data analytics to deliver targeted promotions, deals, and incentives to tourists based on their current location or travel history (Fong et al., 2015). Platforms like Groupon, Expedia, and Airbnb use geolocation data, user profiles, and purchase history to offer personalised discounts, special offers, and exclusive experiences tailored to each tourist's preferences and behaviour. ...
This study explores the synergy between technology and bleisure tourism in Malaysia, investigating their combined impact on enriching travel experiences. The chapter aims to uncover insights and implications for the future of bleisure tourism in Malaysia by examining technological advancements, sustainability initiatives, and emerging trends. Findings reveal that technology has democratised travel, making it more accessible and personalised, while sustainability initiatives have promoted responsible tourism practices and environmental conservation. Moreover, emerging technologies such as virtual reality and artificial intelligence offer innovative ways for tourists to engage with destinations and cultural attractions. The study highlights the importance of continued research and collaboration in driving in-169 novation and sustainability in the bleisure tourism industry, positioning Malaysia as a destination for tourists seeking memorable, responsible, and technologically enhanced experiences.
... Secondly, CML can be applied for effect heterogeneity (or moderation) analysis to detect customer segments for which a marketing intervention is particularly effective or ineffective, see for instance Chernozhukov, Demirer, Duflo, and Fernandez-Val (2018). Thirdly, and closely related to the previous idea, CML permits finding an optimal customer segmentation (based on observed characteristics like customer's income) into groups that should and should not be targeted by the intervention, in order to maximize its overall effectiveness, as discussed in Athey and Wager (2021 Evaluating the impact of interventions has a long tradition in marketing research, often through experiments with randomly assigned interventions, as seen in Bawa and Shoemaker (1989) (evaluating coupons), Fong, Fang, and Luo (2015) (evaluating discounts), and Gordon, Moakler, and Zettelmeyer (2022) (investigating online ads). However, in many contexts, experimental data is unavailable, leading to reliance on observational data where interventions are not random. ...
This study reviews three primary purposes of causal machine learning (CML) in marketing, merging impact evaluation of marketing interventions with machine learning algorithms for learning statistical patterns from data. Firstly, CML enables more credible impact evaluation by considering important control variables that simultaneously influence the intervention and business outcomes (such as sales) in a data-driven manner. Secondly, it facilitates the data-driven detection of customer segments for which a marketing intervention is particularly effective or ineffective, a process known as effect moderation or heterogeneity analysis. Thirdly, closely related to the second point, it allows for optimal customer segmentation into groups that should and should not be targeted by the intervention to maximize overall effectiveness. The discussion is grounded in recent empirical applications, all of which aim to enhance decision support in marketing by leveraging data-driven evaluation and optimization of interventions across different customer groups.
... In this context, Bawa and Shoemaker (1989) examines the impact of coupons on sales in a field experiment, comparing customers with and without purchase history for the advertised brand. Fong et al. (2015) conduct a field experiment to study how coupon usage is moderated by varying discount depths and the proximity of targeted individuals to the advertised movie theater. Sahni et al. (2017) analyzes data from 70 field experiments, discovering that coupons can induce cross-category cross-selling and that their effect on sales can persist even after the coupon expires. ...
Traditionally, firms have offered coupons to customer groups at predetermined discount rates. However, advancements in machine learning and the availability of abundant customer data now enable platforms to provide real-time customized coupons to individuals. In this study, we partner with Meituan, a leading shopping platform, to develop a real-time, end-to-end coupon allocation system that is fast and effective in stimulating demand while adhering to marketing budgets when faced with uncertain traffic from a diverse customer base. Leveraging comprehensive customer and product features, we estimate Conversion Rates (CVR) under various coupon values and employ isotonic regression to ensure the monotonicity of predicted CVRs with respect to coupon value. Using calibrated CVR predictions as input, we propose a Lagrangian Dual-based algorithm that efficiently determines optimal coupon values for each arriving customer within 50 milliseconds. We theoretically and numerically investigate the model performance under parameter misspecifications and apply a control loop to adapt to real-time updated information, thereby better adhering to the marketing budget. Finally, we demonstrate through large-scale field experiments and observational data that our proposed coupon allocation algorithm outperforms traditional approaches in terms of both higher conversion rates and increased revenue. As of May 2024, Meituan has implemented our framework to distribute coupons to over 100 million users across more than 110 major cities in China, resulting in an additional CNY 8 million in annual profit. We demonstrate how to integrate a machine learning prediction model for estimating customer CVR, a Lagrangian Dual-based coupon value optimizer, and a control system to achieve real-time coupon delivery while dynamically adapting to random customer arrival patterns.
... Considering the validity of the research result in both external and internal aspects (Gneezy, 2017;Lynch, 1999), this study based on the previous scholars' suggestion (Fong et al., 2015;Gneezy, 2017) that in order to comprehend the process underlying the effect, a field investigation (Study 3) was followed after the by laboratory studies. The lab study although can ensure that the researcher is in full control of the environment and provide internal validity by testing the mechanisms underlying the proposed relationship (Lynch, 1999). ...
Draws on the integration of aesthetic theory and transaction-specific satisfaction theory, this study concentrated on the concept of hospitality service aesthetics of the front desk of luxury hotel about consumers’ perception among the visual servicescape and humanistic appearance and potential effect on their willingness-to-pay price premium. A mixed method approach of both lab experiment and field investigation was applied to test three hypotheses. The results showed that consumers’ visual aesthetics of front desk with non-thematic style have a more significant impact on their willingness-to-pay price premium compared to the thematic style. This study also indicated that the physical attractiveness of employees is a moderator only when consumers’ willingness-to-pay price premium during service interactions in the context of thematic front desk with low hospitableness.
... Previous studies have highlighted the importance of consumer discount expectations, suggesting that consumers may expect these promotions when renewing memberships; however, their reactions to the promotions can vary. In particular, mobile promotions are widely used as they are easily accessible [51]. However, customer service via phone calls remains common for renewing paid memberships in the hotel industry because it can help determine members' feelings regarding their membership and aid in adjusting benefits to meet their expectations. ...
Customer responses to economic and social satisfaction are important in business-to-business transactions; however, these responses can vary when customer segments and sales promotions are combined. This study investigates the roles of two satisfaction types by demonstrating three-way interactions with two moderators: memberships and promotion levels. Using survey data on paid hotel memberships in Korea, this study focuses on the moderated moderation effects of hotel membership type and sales promotions. The authors find that sales promotions positively affect members’ behavioral intentions when they are economically or socially satisfied, regardless of the membership type. In particular, when social satisfaction is positive, the impact of sales promotions on paid membership renewal intentions increases dramatically regardless of the membership type. Meanwhile, lower-tiered members respond more positively to price discounts, increasing their paid membership renewal intentions. In contrast, premium members prefer coupons over price discounts. However, the slope of customer responses is steeper for social satisfaction than economic satisfaction, highlighting that the impact of sales promotions differs by membership type.
... Third, we extend the literature on understanding the value creation of mobile commerce beyond the transactional paradigm (Bang et al., 2013;Cao et al., 2018;Fong et al., 2015;K. Xu et al., 2017). ...
... lives. Within the physical retail store, geo-targeting is one example, which facilitates the delivery of location-specific messages to consumers (Fong, Fang, and Luo 2015). Similarly, mobile apps play an important role from the perspective of physical retailers as they bridge the gap between the online channel-usually accessed from home or work-and the offline channel. ...
... Accordingly, smartphone app advertisements are highly personalised based on app users' personal information (Meng et al., 2016). Advertising is a major source of income for app developers, whilst mobile marketing campaigns are highly dependent on smartphone applications (Dinsmore et al., 2021;Gupta et al., 2021;Kemp, 2012;Le and Nguyen, 2014) as organisations use customised marketing strategies through mobile applications (Fong et al., 2015;Gupta et al., 2021;Le and Nguyen, 2014;Luo et al., 2014). However, app users' personal information can be misused and/or communicated to third parties which engenders their privacy concerns (Mehta et al., 2022;Zang et al., 2015). ...
Purpose
The purpose of this study is to explore and identify the privacy concerns of smartphone app users pertinent to app usage.
Design/methodology/approach
Adopting a qualitative phenomenological approach, the authors conducted semi-structured interviews with app users to explore the app users' privacy concerns.
Findings
Credibility concerns, unauthorised secondary use and vulnerability concerns are the three major privacy concerns of app users, under which these concerns have sub-concerns, i.e. popularity, privacy policy, stalking, data sharing, hacking and personal harm.
Practical implications
The findings are useful to app marketers, app developers and app stores. App marketers, app developers and app stores can use the findings to understand and properly address app users' privacy concerns, thereby increasing the apps usage.
Originality/value
By exploring the privacy concerns of app users, the authors' study extends the literature and provides a theoretical development of individuals' privacy concerns in the context of a widely used technology, i.e. smartphone applications. Accordingly, this study contributes to the consumer privacy literature.
... However, the absence of a prime location for the business must not hinder productivity if the entrepreneur is successfully taking on regional rivals. It has been suggested that effective consumer marketing and competitiveness be ensured closer to competitors' locations than to corporate headquarters (Fong et al., 2015). ...
This study is conducted to determine the customers’ perception on the location strategy
of Ustingan Café and Resto in Luisiana, Laguna. It sought the demographic profile of the
respondents and their perceptions of the location strategy. It also tested the significant
relationship between the respondents’ perceptions of the location strategy of when
grouped according to their profiles. The researchers used an unstructured questionnaire
and convenient non-probability sampling to gather the data needed. The study involved
two hundred seventy-eight (278) customers determined by using Slovin’s Formula. The
collected data was tallied, tabulated, analyzed, and interpreted through the suggested
statistical treatment. The data revealed that most Ustingan Café and Resto customers
were females aged twenty years old and below who lived in Luisiana, Laguna. They earn
PHP 10,000 or less gross income/allowance. They also dine-in the said café occasionally
and have known the latter thru their friends and; that they usually avail of snacks. It was
also revealed that the product quality of the café is what invites customers to dine in,
usually during afternoons, and spend around PHP 101-499. The results further proved
that in terms of accessibility the café resto is near the market, the surroundings’ interior
design has a good setting arrangement and visually appealing layout, the surroundings’
exterior design has an attractive entrance, and the products’ price is reasonable given its
product quality in term of affordability. From the analyzed results, the researchers
proposed directional and interior signage to guide customers in locating them and letting
them know the service they are offering.
... Our paper contributes to several strands of the literature. First, our study of targeted incentives is related to a large literature on the effectiveness of consumer targeting, such as text message communications (e.g., Ansari and Mela (2003), Luo et al. (2014)), targeted price promotions (e.g., Feinberg et al. (2002), Wedel (2009), Sahni et al. (2017), Zhang et al. (2018), McGranaghan et al. (2019), targeted online ads (e.g., Goldfarb andTucker (2011), Lambrecht andTucker (2013), Bleier and Eisenbeiss (2015)), online recommendation systems (Liang et al. (2019)) as well as targeting based on contextual characteristics (e.g., Fong et al. (2015), Andrews et al. (2016)). 3 Unlike the above studies, our focus is on the spillovers among sellers. ...
Digital platforms sometimes offer incentives to a subset of sellers to nudge behavior, possibly affecting the behavior of all sellers in the equilibrium. In this paper, we study a policy change on a large e-commerce platform that offers financial incentives only to platform-certified sellers when they provide fast handling and generous return policies on their listings. We find that both targeted and non-targeted sellers become more likely to adopt the promoted behavior after the policy change. Exploiting a large number of markets on the platform, we find that in markets with a larger proportion of the targeted population—hence more affected by the policy change—non-targeted sellers are more likely to adopt the promoted behavior and experience a larger increase in sales and equilibrium prices. This finding is consistent with our key insight that a targeted incentive may increase demand for non-targeted sellers when both platform certificates and the promoted behaviors are quality signals. Our results have implications for digital platforms that use targeted incentives.
... Geofencing can also be used for geo conquesting. Geo Conquesting aims to develop a virtual Geofence around the competitor's targeted location (Fong et al., 2015). Then the marketeers target the competitor's customers with specially designed ads depicting their products or offers as better. ...
This chapter briefly discusses the growing promotional techniques and marketing strategies adopted by organisations in attracting and retaining customers. The growth of technology has enabled new insights in pulling target customers and creating intentions to purchase products and services, and one of such methods is location-based mobile targeting technique. This strategy works best for those segments of users who look for instant information and are ready to take action based on the information/offers received. Through this chapter, the readers get a brief knowledge on technologies adopted by organisations in marketing and promotions, optimising the advertisements and offers to specific target population, what location-based marketing is, how it works, and technologies and techniques employed such as geofencing, geo conquesting, geotargeting, proximity marketing, etc. Further, the chapter discusses the advantages and disadvantages of mobile target marketing, and finally, the chapter ends by explaining how organisations could adapt for better competitive performance.
... The locational targeting of customers within certain designated areas is called "geo fencing." When applied to competitors' locations, this tactic is called "geo conquesting" [44]. Customers can use a location-based service (LBS) [45] through mobile terminals to obtain current location information and avail of location-related services. ...
The management of electronic word of mouth (eWOM) is critical in e-commerce. In this study, on the basis of the elaboration likelihood model (ELM), we constructed a model of factors influencing eWOM by dividing merchants’ attributes into the central and peripheral routes, which correspond to consumers’ systematic and heuristic cognitive modes respectively. We then tested the developed model by using a cross-sectional data set. The results of this study indicate that the degree of competition faced by merchants has a significant negative association with eWOM. Moreover, price level and location moderate the relationship between competition and eWOM. The services of reservation and group buying have positive associations with eWOM. This research has three main contributions. First, we explored the effect of competition on eWOM. Second, we validated the feasibility of applying the ELM to the catering industry by dividing merchant attributes into the central and peripheral routes; this approach is consistent with systematic and heuristic cognitive theories. Finally, this research provides practical suggestions for eWOM management in the catering industry.
Practice- and Policy-oriented Abstract
Building upon recent advances in consumption theories, we propose an ephemeral state-dependent framework for digital content recommendations. The framework accentuates a critical, yet understudied, interplay between a firm’s recommendation strategy (assimilation or diversification) and a consumer’s ephemeral state (fixation or foraging). The framework adaptively recommends either assimilated or diversified content based on a consumer’s ephemeral state. Through a randomized field experiment, we provide compelling evidence that state-dependent schemes can enhance engagement and revenue. Although the congruent scheme (i.e., assimilation when fixation, diversification when foraging) generally outperforms the incongruent one, contributing a 7.3% ($19.73 million) annual revenue lift for the platform, our findings underscore the necessity for nuanced personalization. Specifically, consumers with broader, more fluid preferences benefit more from the incongruent scheme (i.e., assimilation when foraging, diversification when fixation), challenging the prevailing assumption that congruence is always optimal. Our research not only adds to the theoretical understanding of consumer behavior in digital content consumption, but also offers actionable insights for designing more effective recommender systems. By accounting for consumer heterogeneity and considering the broader implications of our proposed recommendation framework, including spillover effects, our findings have the potential to influence industry practices and future academic inquiry in this rapidly evolving field.
The purpose of this study is to understand the factors that influence online purchase decisions, especially amidst the increasing popularity of e-commerce and the shift accelerated by the COVID-19 pandemic. This bibliometric review examines 95 articles with the keyword "online purchase decision" from Scopus journals generated by Publish or Perish on April 25, 2023, to identify the most influential authors and trends in this field from 2002 to 2023. The study reveals a steady increase in publications on this subject over time, with a significant surge recently. S. Yoon emerged as the most cited author in this field, followed by H.W. Kim and N. Hu. "Decision Support Systems" is the most productive journal in this field, and M. Ramesh is the most prolific author. The research variables have similarities and differences in their focus and approach. For instance, trust, price, reviews, website characteristics, and the influence of social media are the focus in these studies. These studies differ in their approaches and focus. For example, Yoon (2002) examines the antecedents and consequences of trust, Kim et al. (2012) compare price and trust, Hu et al. (2014) analyze online review sentiment, and Luo et al. (2012) investigate the impact of website characteristics. There are also differences in the scope of research, including cross-cultural approaches, the teenage market, gender, and potential customers vs. repeat customers. The findings of this study provide valuable insights into the key trends and patterns in online purchase decision-making research, which can inform marketing strategies and improve online sales.
In recent years, scholars and practitioners have increasingly recognized the profound impact of digital technologies (DTs) on reshaping organizations' value propositions and their ability to create, communicate, and deliver value to stakeholders. Given this heightened attention, it is imperative to comprehensively examine how DTs affect marketing innovations. This study reports the results of a systematic review of empirical research on DTs' role in marketing innovations. Specifically, it identifies a comprehensive list of technologies and investigates their relevance in enabling innovative approaches within marketing research, strategy formulation (segmentation, targeting, and positioning), and implementation (product, promotion, place, and price). The study synthesizes emerging themes in the literature, pinpoints research gaps, proposes a 3As framework for classifying DTs in marketing, and delineates future research directions in this pivotal domain.
Purpose
This study differentiates pure impulse buying behaviour from suggestive impulse buying behaviour in using mobile shopping applications (apps). This study aims to assess the moderating effects of instant discount and cashback promotional offers along with the mediating effects of impulse buying intention (IBI) and user satisfaction (US), using the app stimuli (performance expectancy, effort expectancy, layout, atmosphere, privacy and security).
Design/methodology/approach
The study was done in three stages: analysis of variance, followed by structural equation modelling (SEM) and paired t -tests.
Findings
The results showed that instant discounts and cashback offers are different from each other for the mediating variable IBI. The SEM results for pure impulse buying showed that, except for layout, the remaining variables have a positive relationship with IBI. For suggestive impulse buying, effort expectancy and layout were significantly related to both the mediating variables. Finally, pure and suggestive impulse buying behaviour showed significant differences.
Originality/value
Previous studies have looked into impulse buying in its generic sense and not through the “types” of impulse buying they were measuring. As impulse buying behaviour is a predominant theme for discussion today, marketing professionals and researchers must comprehend the impact of app stimuli in the context of select types of impulse buying behaviour.
Targeting ads based on consumers’ real-time locations has evolved into a practice worth billions of dollars in the advertising industry. Yet, the implications of repeated mobile ad exposure are poorly understood, primarily due to the confounding effects of locational context. This paper seeks to bridge this gap. Using two large datasets comprising more than three million observations from a major European mobile telecommunication company, we investigate how ad repetition and location revisits (i.e., returning to a previously visited location) jointly determine consumer response to mobile display advertising. Our empirical strategy leverages coarsened exact matching combined with a logit model with fixed effects at the consumer-location level. We find that the click rate through ads is more than 26 percent higher at revisited locations compared to locations visited for the first time. However, mobile ad repetition decreases click rates, and this effect is amplified at revisited locations. Our results contribute to the theory and practice of mobile advertising.
The article offers a comprehensive view of the field of ‘digital advertising’, tracing its evolution from the occurrence of the first banner ad in 1994. The objective of the study is to trace systematically how the digital advertising industry has transitioned from being the traditional one-way communication model to its current ‘intelligent’ state. This study offers profound insights into the dynamic and continually evolving domain of digital advertising. More specifically, it traces the evolutionary stages, major themes, influential articles and citation networks from 1993 to 2023. The articles have been thoroughly examined in three phases, each covering a period of 10 years from 1993 to 2023. The first two decades saw significant growth in the subject domain of ‘digital advertising’; however, the maximum number of articles contributing to the subject from 2013 to 2023 focused mainly on ad-personalization using ICT tools and incorporating artificial intelligence (AI). The key findings indicate that the third decade witnessed a remarkable rise in the number of articles pertaining to AI-driven ad personalization, thus portraying further focus by the researchers on how best to leverage technology in driving advertising effectiveness. AI became one such pivotal innovation, changing the very concept of digital advertising with its capability, to automatically target precisely and develop personalized promotions to engage consumers. The work is unique for the contribution it can make to already existing works regarding digital advertising by coming to one synthesized view of its evolution and its function in its totality regarding AI. The article sets a common platform for future research efforts and innovations within this domain, therefore offering valuable insights both for industry practitioners and future scholars.
Brand messages are now being delivered across multiple screens, including smartphones and PCs. While researchers have explored various marketing-related dynamics of mobile phone use, relatively little is known about the unique effects of different screens on the engagement outcomes of branded messages. In this research, the authors draw on construal level theory and propose that messages are construed at lower levels on mobile phone (vs. PC) screens, due to a closer psychological distance to those devices. Using a combination of four studies including lab experiments and an analysis with a unique dataset of branded social media messages consumed across mobile phone and PC screens, they show that immediate (i.e., closer temporal distance) social media messages are more engaging on mobile phones than PCs and that the effects are driven by low levels of construal. The findings suggest that there is a screen effect on content effectiveness, and therefore marketers need to not only consider the differences in format (e.g., screen size) of messages but also specifically configure content design for mobile consumption to enhance consumer engagement.
Despite the widespread adoption of electronic coupons as a promotion tool for attracting customers and increasing operating revenue, there are few empirical studies that focus on the impact of promotion design under smart retail circumstance. How do consumers handle dazzling coupon information? Which coupon distribution method best encourages consumers to redeem coupons? To answer those questions, we collected promotion data from 24 Chinese chain retailers for this paper and matched that design data to the corresponding retail performance data. Our unique data set allows us to reveal the relationship between promotion design and retail operating performance. Our analyses show that promotion depth and width both have significant positive effects on coupon redemption. Unlike quick response (QR) code coupons, location-based coupons, feed ad coupons and payment gift coupons all exert negative effects on coupon redemption. Among retailers, specialty stores have a lower coupon redemption ratio than supermarkets, while the coupon redemption ratio of convenience stores shows no difference from that of supermarkets. In addition, retailer reputation has a positive effect on coupon redemption. We also investigate the moderating effect of retail format and retailer reputation for further discussion.
Presently, the customer takes center stage in the realm of sales, playing a pivotal role in the establishment of enduring relationships and loyalty. This shift implies a transformation in the dynamics between sellers and customers, with sellers increasingly incorporating elements of relationship marketing. This paper offers an overview of issues related to relational marketing within the context of electronic commerce, highlighting its significance in fostering relationships between online sellers and customers in the digital environment. The advent of the digital age has also brought about changes in how sellers engage with customers. There is a growing emphasis on relationship marketing, a strategy used to cultivate and sustain long-term connections with customers. There is also a growing prominence of artificial intelligence systems. Artificial intelligence is widely used in customer relationship management. The surge in e-commerce has amplified interest in relationship marketing, prompting a deeper understanding of fundamental aspects in forming online relationships with consumers. It is imperative for sellers to formulate and execute relational marketing strategies and to implement artificial intelligence systems within sales and communication processes, ultimately providing them with a competitive edge and fostering consumer loyalty. E-commerce plays a pivotal role in this evolving landscape.
Online platforms have emerged as a dominant business model in numerous industries in the new millennium. In light of the substantial and burgeoning body of empirical platform research, this article synthesizes extant studies and identifies the evolution of underlying research methodologies and topics. Building upon a database of 860 empirical online platform papers in premier journals during the first two decades of the new millennium, this article presents a categorization framework based on the online platform type (including search platforms, e‐commerce platforms, online communities, and mobile platforms) and research perspective (including platform participants, platform orchestrators, and platform ecosystems). We provide a critical review of noteworthy trends and highlight directions for future research in each category of the proposed framework. A comprehensive bibliometric analysis is then conducted to visualize and track scholarship in empirical online platform research. Lastly, we adopt an interdisciplinary lens to synthesize our critical review of empirical online platform research into lessons and research opportunities that emerge from multiple disciplines.
Progress in sensor technologies has made three-dimensional (3D) representations of the physical world available at a large scale. Leveraging such 3D representations with analytics has the potential to advance Information Systems (IS) research in several areas. However, this novel data type has rarely been incorporated. To address this shortcoming, this article first presents two showcases of 3D analytics applications together with general modeling guidelines for 3D analytics, in order to support IS researchers in implementing research designs with 3D components. Second, the article presents several promising opportunities for 3D analytics to advance behavioral and design-oriented IS research in several contextual areas, such as healthcare IS, human-computer interaction, mobile commerce, energy informatics and others. Third, we investigate the nature of the benefits resulting from the application of 3D analytics, resulting in a list of common tasks of research projects that 3D analytics can support, regardless of the contextual application area. Based on the given showcases, modeling guidelines, research opportunities and task-related benefits, we encourage IS researchers to start their journey into this largely unexplored third spatial dimension.
Retailers’ efforts to monetize consumer location data remain dominated by inefficient protocols (e.g., geofencing) that customize marketing interactions based solely on app users’ current location. Although extant trajectory mining techniques can remedy these shortcomings, they require high-frequency location data, which poses severe risks to consumers’ privacy. The authors present a novel method to extract marketing value from low-granularity urban mobility data and demonstrate its use in analyzing gas station choice to value customers. The data, also used to infer gas station visits, contain 1.06 million location records on nearly 27,000 devices observed near selected retailers including gas stations during a six-month period in Staten Island, New York. The authors pool consumers’ mobility trajectories from several days to dynamically calculate the distance of stores from consumers’ anticipated trajectories. They then supplement the data with station-level daily fuel prices and estimate a conditional logit model to assess how consumers trade off gas prices versus store distance. In addition to a generally high station loyalty, the authors find that consumers strongly prefer not to deviate far from their common trajectories for fueling trips. Applying their methods in a predictive context, the authors infer the value of newly acquired customers to the studied gas stations to be between 7.59.
This study examines the interaction between top-of-funnel advertising (e.g., search or display advertising) and bottom-of-funnel advertising (e.g., using a mobile application on a smart phone). We are particularly interested in the phenomenon of geoconquesting: the bottom-of-funnel advertising efforts of a firm to poach (or lure away) customers that have come to a competing firm’s physical store as a result of top-of-funnel advertising efforts by the firm. Geoconquesting efforts by a competing firm should reduce a focal firm’s incentive to invest in top-of-funnel efforts. Thus, a key challenge for an agent like Google that provides both top-of-funnel and bottom-of-funnel advertising services, is to balance the inherent conflict between the two in order to maximize the total revenue collected from the two forms of advertising. We develop a game-theoretic model to study the this phenomenon. A key result is that sometimes the agent benefits from not offering geoconquesting, but instead promises, after collecting a fee, to protect the advertisers from poaching on each other’s search traffic. Interestingly, such a protection service becomes more lucrative for the agent when a cheaper outside option for geoconquesting is available to the advertisers.
The aim of the research was to determine the extent and purpose of using mobile phones by Generation Z consumers before, during and after shopping in brick-and-mortar stores. The stratified group consisted of 785 residents of the Slovak Republic born between 1997 and 2012 inclusive. The survey has been conducted using the inquiry method-an online questionnaire based on the Google Forms platform. The questions were formulated into three logically interconnected parts: the purpose of using the mobile phone by the respondents in the phase before, during and after the purchase in a brick-and-mortar store. In addition, we also examined the respondents' activity on social networks during the purchase in the brick-and-mortar store and, finally, demographic data. We formulated two hypotheses and three assumptions. One hypothesis and one assumption were confirmed. On the contrary, one hypothesis was disproved, and two assumptions were not confirmed. The hypothesis focused on the relationship between the main ways of using a mobile phone and the activity on social networks during shopping in a brick-and-mortar store was confirmed. The hypothesis focused on the relationship between the gender of consumers and the use of a mobile phone during shopping in a brick-and-mortar store was disproved. The assumption regarding the use of a mobile phone while shopping for food in a brick-and-mortar store for the purpose of comparing product prices was confirmed. The assumption regarding the use of a mobile phone while shopping for consumer electronics in order to search for product information was not confirmed. Likewise, the assumption regarding the use of a mobile phone while shopping for clothes in a brick-and-mortar store in order to connect with friends or acquaintances in order to ask for their advice was not confirmed. These findings are beneficial for retail practice operating a chain of brick-and-mortar stores.
Purpose: Firms can benefit from designing sales promotion based on the analysis of consumers' physical exercise and purchase data. This study aims to study mobile exercise app data to explore how purchasing a promoted or nonpromoted product affects exercisers’ subsequent exercise and purchase behaviors.
Design/methodology/approach: Drawing from the theoretical framework of overjustification effect, this study empirically examines the effects of the purchase of promoted – monetary and nonmonetary – or nonpromoted products on relationships (1) between past and subsequent exercise behaviors and (2) between past exercise and subsequent purchase behaviors. Novel data of one million exercise activities and purchase transactions created by 7,517 mobile exercise app users were collected.
Findings: The results reveal that monetary and nonmonetary promotions have a negative effect on overall consumers’ amount of physical exercise but increase heavy exercisers’ exercise amount. In addition, nonmonetary (monetary) promotion has a positive (negative) effect on consumers’ purchase expenditure but has no moderating effect on the exercise–expenditure relationship.
Originality/value: This study provides a theoretical framework explaining how to mitigate the dark side of sales promotions while targeting right exercise consumer segments with the right promotion campaigns.
How do competitors react to each other's price-promotion and advertising attacks? What are the reasons for the observed reaction behavior? We answer these questions by performing a large-scale empirical study on the short-run and long-run reactions to promotion and advertising shocks in over 400 consumer product categories over a four-year time span.
Our results clearly show that the most predominant form of competitive response is passive in nature. When a reaction does occur, it is usually retaliatory in the same instrument, i.e., promotion attacks are countered with promotions, and advertising attacks are countered with advertising. There are very few long-run consequences of any type of reaction behavior. By linking reaction behavior to both cross- and own-effectiveness, we further demonstrate that passive behavior is often a sound strategy, while firms that do opt to retaliate often use ineffective instruments, resulting in “spoiled arms.” Accommodating behavior is observed in only a minority of cases, and often results in a missed sales opportunity when promotional support is reduced. The ultimate impact of most promotion and advertising campaigns depends primarily on the nature of consumer response, not the vigilance of competitors.
In search advertising, brand names are often purchased as keywords by the brand owner or a competitor. We aim to understand the strategic benefits and costs of a firm buying its own brand name or a competitor's brand name as a keyword. We model the effect of search advertising to depend on the presence or absence of a competitor's advertisement on the same results page. We find that the quality difference between the brand owner and the competitor moderates the purchase decision of both firms. Interestingly, in some cases, a firm may buy its own brand name only to defend itself from the competitor's threat. It is also possible that the brand owner, by buying its own branded keyword, precludes the competitor from buying the same keyword. Our result also implies that the practice of bidding on the competitor's brand name creates a prisoner's dilemma, and thus both firms may be worse off, but the search engine captures the lost profits. We also discuss the difference in our results when the search is for a generic keyword instead of a branded keyword. Finally, we find some empirical support for our theory from the observation of actual purchase patterns on Google AdWords.
Our research investigates the competitive ramifications of individual marketing and information management in today's information-intensive marketing environments. The specific managerial issues we address are as follows. First, what kinds of incentive environments do competing firms face when they can only target individual customers imperfectly? Second, does the improvement in an industry's targetability intensify price competition in the industry such that all competing firms become worse off? Third, should a firm share its customer knowledge so as to improve its rival's targetability? Fourth, how should an information vendor sell its information that can improve a firm's targetability? Finally, do competing firms have the same incentives to invest in their own targetability?
To answer those questions, we develop a simple model à la Narasimhan (1988), in which each of the two competing firms have their own loyal customers and compete for common switchers. We assume that each firm can classify its own loyal customers and switchers correctly only with a less-than-perfect probability. This means that each firm's perceived customer segmentation differs from the actual customer segmentation. Based on their perceived reality, these two competing firms engage in price competition. As an extension, we also allow the competing firms to make their investment decisions to acquire targetability.
We show that when individual marketing is feasible, but imperfect, improvements in targetability by either or both competing firms can lead to win-win competition for both even if both players behave noncooperatively and the market does not expand. Win-win competition results from the fact that as a firm becomes better at distinguishing its price-insensitive loyal customers from the switchers, it is motivated to charge a higher price to the former. However, due to imperfect targetability, each firm mistakenly perceives some price-sensitive switchers as price-insensitive loyal customers and charges them all a higher price. These misperceptions thus allow its competitors to acquire those mistargeted customers without lowering their prices and, hence, reduce the rival firm's incentive to cut prices. This effect softens price competition in the market and qualitatively changes the incentive environment for competing firms engaged in individual marketing. A “prisoner's dilemma” occurs only when targetability in a market reaches a sufficiently high level.
This win-win perspective on individual marketing has many managerial implications. First, we show that superior knowledge of individual customers can be a competitive advantage. However, this does not mean that a firm should always protect its customer information from its competitors. To the contrary, we find that competing firms can all benefit from exchanging individual customer information with each other at the nascent stage of individual marketing, when firms' targetability is low. Indeed, under certain circumstances, a firm may even find it profitable to give away this information unilaterally. However, as individual marketing matures (as firms' targetability becomes sufficiently high), further improvements in targetability will intensify price competition and lead to prisoner's dilemma. Therefore, it is not only prudent politics but also a business imperative for an industry to seize the initiative on the issue of protecting customer privacy so as to ensure win-win competition in the industry.
Second, we show that the firm with a larger number of loyal customers tends to invest more in targetability when the cost of acquiring targetability is high. However, the firm with a smaller loyal base can, through information investment, acquire a higher level of targetability than the firm with a larger loyal base as long as the cost of acquiring targetability is not too high. As the cost further decreases, competing firms will all have more incentives to increase their investments in targetability until they achieve the highest feasible level.
Third, an information vendor should make its information available nonexclusively (exclusively) when its information is associated with a low (high) level of targetability. When the vendor does sell its information exclusively, it should target a firm with a small loyal following if it can impart a high level of targetability to that firm.
Finally, our analysis shows that an information-intensive environment does not doom small firms. In fact, individual marketing may provide a good opportunity for a small firm to leapfrog a large firm. The key to leapfrogging is a high level of targetability or customer knowledge.
We explore how Internet browsing behavior varies between mobile phones and personal computers. Smaller screen sizes on mobile phones increase the cost to the user of browsing for information. In addition, a wider range of offline locations for mobile Internet usage suggests that local activities are particularly important. Using data on user behavior at a (Twitter-like) microblogging service, we exploit exogenous variation in the ranking mechanism of posts to identify the ranking effects. We show that (1) ranking effects are higher on mobile phones suggesting higher search costs: links that appear at the top of the screen are especially likely to be clicked on mobile phones and (2) the benefit of browsing for geographically close matches is higher on mobile phones: stores located in close proximity to a user's home are much more likely to be clicked on mobile phones. Thus, the mobile Internet is somewhat less "Internet-like": search costs are higher and distance matters more. We speculate on how these changes may affect the future direction of Internet commerce.
Abstract This study attempts to answer a basic customermanagement,dilemma,facing firms: When should the firm use behavior-based pricing (BBP) to discriminate between ,its own ,and competitors’ customers in a competitive market? If BBP is profitable, when should the firm offer a lower price to its own customers rather than to the competitor's customers? This analysis considers two features of customer behavior hitherto ignored in BBP literature: heterogeneity in customer value and changing preference (i.e., customer preferences are correlated but not fixed over time). In a model where both consumers and competing firms are forward looking, we identify conditions when,it is optimal to reward,the firm’s own or competitor’s customers and when,BBP increases ordecreases profits. To the best of our knowledge, we are the first to identify conditions in
We explore opportunities for targeted pricing for a retailer that only tracks weekly store-level aggregate sales and marketing-mix information. We show that it is possible, using these data, to recover essential features of the underlying distribution of consumer willingness to pay. Knowledge of this distribution may enable the retailer to generate additional profits from targeting by using choice information at the checkout counter. In estimating demand we incorporate a supply-side model of the distribution channel that captures important features of competitive price-setting behavior of firms. This latter aspect helps us control for the potential endogeneity generated by unmeasured product characteristics in aggregate data. The channel controls for competitive aspects both between manufacturers and between manufacturers and a retailer. Despite this competition, we find that targeted pricing need not generate the prisoner's dilemma in our data. This contrasts with the findings of theoretical models due to the flexibility of the empirical model of demand. The demand system we estimate captures richer forms of product differentiation, both vertical and horizontal, as well as a more flexible distribution of consumer heterogeneity.
The tailoring of a firm’s marketing mix to the individual customer is the essence of one-to-one marketing. In this paper,
we distinguish between two forms of one-to-one marketing: personalization and customization. Personalization occurs when the
firm decides what marketing mix is suitable for the individual. It is usually based on previously collected customer data.
Customization occurs when the customer proactively specifies one or more elements of his or her marketing mix. We summarize
key challenges and knowledge gaps in understanding both firm and customer choices in one-to-one markets. We conclude with
a summary of research opportunities.
The authors examine the long-term effects of promotion and advertising on consumers’ brand choice behavior. They use 8 1/4 years of panel data for a frequently purchased packaged good to address two questions: (1) Do consumers’ responses to marketing mix variables, such as price, change over a long period of time? (2) If yes, are these changes associated with changes in manufacturers’ advertising and retailers’ promotional policies? Using these results, the authors draw implications for manufacturers’ pricing, advertising, and promotion policies. The authors use a two-stage approach, which permits them to assess the medium-term (quarterly) effects of advertising and promotion as well as their long-term (i.e., over an infinite horizon) effects. Their results are consistent with the hypotheses that consumers become more price and promotion sensitive over time because of reduced advertising and increased promotions.
The authors examine the effects of a manufacturer coupon on brand choice behavior. The level of coupon redemption and changes in brand choice behavior after redemption are examined as a function of the household's prior probability of purchasing the promoted brand, likelihood of buying a favorite competitive brand, and coupon face value. A model of the coupon redemption decision is developed to predict response to the coupon promotion by different consumer segments. Predictions from the model are tested by using scanner panel data from a field experiment on coupon face values. Coupon redemption rates are found to be much higher among households that have purchased the brand on a regular basis in the past. The results also suggest that most consumers revert to their precoupon choice behavior immediately after their redemption purchase. These and other findings have important implications for the profitability of coupon promotions.
What are the conceptual properties of a trading area?
What is the definition of the term?
What testable propositions are currently available to validate its properties and thus give precision to the definition?
This article gives answers to these questions.
Several authors have noted that the profitability of a coupon promotion depends on the incremental sales generated by the coupon. However, most prior research on coupon promotions has focused on redemption rates and little is known about the characteristics of households that make incremental purchases. The authors develop and test several hypotheses about the characteristics of households that make incremental purchases in response to a direct mail coupon promotion. For the product tested, coupons produced greater incremental sales among households that were larger, more educated, and were homeowners. The findings suggest that directing coupons to the most responsive market segments can increase profits significantly.
Standard models of competition predict that firms will sell less when competitors target their customers with advertising. This is particularly true in mature markets with many competitors that sell relatively undifferentiated products. However, the authors present findings from a large-scale randomized field experiment that contrast sharply with this prediction. The field experiment measures the impact of competitors' advertising on sales at a private label apparel retailer. Surprisingly, for a substantial segment of customers, the competitors' advertisements increased sales at this retailer. This robust effect was obtained through experimental manipulation and by measuring actual purchases from large samples of randomly assigned customers. The effect size is also large, with customers ordering more than 4% more items in some categories in the treatment condition (vs. the control). The authors examine how these positive spillovers vary across product categories to illustrate the importance of product standards, customer learning, and switching costs. The findings have the potential to change our understanding of competition in mature markets.
The use of coupons delivered by mobile phone, so-called "m-coupons," is growing rapidly. In this study, the authors analyze consumer response to m-coupons for a two-year trial at a large shopping mall. Approximately 8,500 people were recruited to a panel and received three text-message m-coupons whenever they "swiped" their mobile phone at the mall entrances, with downstream redemption recorded. Almost 144,000 m-coupons were delivered during the trial, representing 38 stores that supplied 134 different coupons. The authors find that an important feature of m-coupons is where and when they are delivered, with location and time of delivery significantly influencing redemption. How long the m-coupons are valid (expiry length) is also important because redemption times for m-coupons are much shorter than for traditional coupons. This finding suggests that their expiration length should be shortened to help signal time urgency. Nevertheless, traditional coupon features, such as face value, still dominate m-coupon effectiveness, as does the product type, with snack food coupons being particularly effective.
Retail markets are extremely important, but economists have few practical tools for analyzing the way dispersed buyers and sellers affect the properties of markets. I develop an econometric model of retail demand in which products are location specific and consumers have preferences over both geographic proximity and other store and product characteristics. The model uses data on the observed geographic distribution of consumers within a market to (1) help explain observed variation in market shares and (2) affect predicted substitution patterns between stores. Using data from the U.S. cinema industry, I use the estimated model to evaluate the form of consumer transport costs, the effect of a theater's price and quality choices on rivals, the effects of geographic differentiation, and the nature and extent of market power.
With the advent of panel data on household purchase behavior, and the development of statistical procedures to utilize this data, firms can now target coupons to selected households with considerable accuracy and cost effectiveness. In this article, we develop an analytical framework to examine the effect of such targeting on firm profits, prices, and coupon face values. We also derive comparative statics on firms' optimal mix of offensive and defensive couponing, the number of coupons distributed, redemption rates, face values, and incremental sales per redemption. Among our findings: when rival firms can target their coupon promotions at brand switchers, the outcome will be a prisoner's dilemma in which the net effect of targeting is simply the cost of distribution plus the discount given to redeemers.
This study investigates the effectiveness of customized promotions at three levels of granularity (mass market, segment specific, and individual specific) in online and offline stores. The authors conduct an empirical examination of the profit potential of these customized promotion programs with a joint model of purchase incidence, choice, and quantity and through optimization procedures for approximately 300 conditions. They find that (1) optimization procedures lead to substantial profit improvements over the current practice for all types of promotions (customized and undifferentiated); (2) loyalty promotions are more profitable in online stores than in offline stores, while the opposite holds for competitive promotions; (3) the incremental payoff of individual-level over segment- and mass market-level customized promotions is small in general, especially in offline stores; (4) for categories that are promotion sensitive, individual-level customized promotions can lead to a meaningful profit increase over segment- and mass market-level customized promotions in online stores; and (5) low redemption rates are a major impediment to the success of customized promotions in offline stores. Optimal undifferentiated promotions should be the primary promotion program in this channel, and firms can benefit from offering a combination of optimal undifferentiated and customized promotions for suitable categories in offline stores.
Price discrimination by imperfectly competitive firms may intensify competition, leading to lower prices for all consumers; the tradeoff of consumer groups' welfare that is characteristic of monopolistic discrimination need not arise. This escalation of competition may make firms worse off, and as a result firms may wish to avoid the discriminatory outcome. Under conditions similar to those in which unambiguous price and welfare effects may arise, unilateral commitments not to price discriminate - including the adoption of everyday low pricing or no-haggle policies - may raise firm profits by softening price competition.
This paper examines four million daily price observations for more than 1,000 consumer electronics products on the price comparison site http://Shopper.com . We find little support for the notion that prices on the Internet are converging to the 'law of one price.' In addition, observed levels of price dispersion vary systematically with the number of firms listing prices. The difference between the two lowest prices (the 'gap') averages 23 per cent when two firms list prices, and falls to 3.5 per cent in markets where 17 firms list prices. These empirical results are an implication of a general 'clearinghouse' model of equilibrium price dispersion. Copyright Blackwell Publishing Ltd. 2004.
- Chiou Chiou
- Luo Xueming
Quarterly Digital Intelligence Briefing: 2014 Digital Trends
- Adobe Econsultancy
Mobile Advertising: What Do Customers Want? Cross-Country Comparison
- Pricewaterhousecoopers