No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
The Role of Push Notifications
Abstract
Mobile apps market is a growing market and the main technological enabler of apps are push notifications (PN). Today, users are currently receiving a daily average of 63 PN.
After an introduction that highlights the relevance of PN, this chapter covers the background of its topic –pop-up messages that emerge on the smartphone screen- and its characterization: (1) proactive communication with the user; (2) explicitly authorized through an opt-in request; (3) wide range of content, private and social, sent by social networks, commercial companies, or news publishers from apps or web site; (4) targeted according to the users’ interests, previous behaviors, or time of day; (6) always prompting the user to click on the PN that will land on the sender’s app / web site.
There is a steep competition for the user's attention to click through the PN message. Thus the chapter moves through to discuss the factors that influence the choice of whether to open or ignore a PN: (1) Timing in the delivery, disruption, and systems for managing PN in a non-disruptive way. (2) Top-down factors in PN usage, such as user profile, user reaction times, and user interest in the content (3) Bottom-up factors, such as message textual and visual features as an antecedent of click-through rate.
Before concluding, the chapter suggests future directions for researchers and practitioners: how to increase opt-in rates, user experience of PN, reasons to opt-out …
The chapter ends with a conclusion and a list of references.
... Push notifications are designed to influence user behavior by delivering timely and relevant information, thereby increasing engagement and knowledge. (Gavilan, 2022). This dynamic information flow has become a crucial research area for understanding the impact of notifications on user information behavior, especially from information-seeking and cognitive perspectives (Pham, Nguyen, Hwang, & Chen, 2016;N. ...
This study explores the impact of mobile notifications on the information behavior and interaction attitudes of higher education students in Egypt and Germany. Using an ethnographic approach, the research investigates how mobile notifications serve as a crucial medium for information delivery, transforming user interaction with information. The study identifies significant challenges posed by the influx of notifications, such as information overload, distraction, and stress. It also examines the skills and strategies students employ to manage and prioritize notifications, emphasizing the need for improved mobile information literacy (MoIL). Interviews and observations reveal varied user engagement with notifications, highlighting the dual role of notifications as both end-point information containers and triggers for deeper information-seeking behavior. The findings suggest that while notifications enhance efficiency and immediacy in accessing information, they also necessitate new coping mechanisms to mitigate negative impacts. This research contributes to the field of information behavior by offering insights into the effective use of mobile notifications and proposing better notification system designs to foster enhanced information literacy in an increasingly connected world.
... Push notifications are designed to influence user behavior by delivering timely and relevant information, thereby increasing engagement and knowledge. (Gavilan, 2022). This dynamic information flow has become a crucial research area for understanding the impact of notifications on user information behavior, especially from information-seeking and cognitive perspectives (Pham, Nguyen, Hwang, & Chen, 2016;N. ...
This study explores the impact of mobile notifications on the information behavior and interaction attitudes of higher education students in Egypt and Germany. Using an ethnographic approach, the research investigates how mobile notifications serve as a crucial medium for information delivery, transforming user interaction with information. The study identifies significant challenges posed by the influx of notifications, such as information overload, distraction, and stress. It also examines the skills and strategies students employ to manage and prioritize notifications, emphasizing the need for improved mobile information literacy (MoIL). Interviews and observations reveal varied user engagement with notifications, highlighting the dual role of notifications as both end-point information containers and triggers for deeper information-seeking behavior. The findings suggest that while notifications enhance efficiency and immediacy in accessing information, they also necessitate new coping Cybrarians Journal Issue 71, April 2024 2 mechanisms to mitigate negative impacts. This research contributes to the field of information behavior by offering insights into the effective use of mobile notifications and proposing better notification system designs to foster enhanced information literacy in an increasingly connected world.
With the media environment becoming increasingly digital, the shift to online news has weakened the direct relationship between publishers and readers (Newman et al., 2019). The current challenge for news media, therefore, is to build traffic towards both their apps and web sites. The most popular means in meeting such a challenge is through the effective use of “push notifications.” This paper analyzes how vivid push notifications can influence the click-through rate. It proposes that vivid (as opposed to “not vivid”) wording of headlines will have a positive influence on click-through rates. The use of vivid images will also have a positive influence on click-through rates. Additionally, this paper proposes that vivid images will moderate the relationship between vivid headline text and click-through rate only when they are congruent with the central theme of the news item. In order to test this moderation model, we conducted quasi-experimental field research, using a random sample of 770 news push notifications from mainstream media, on the subject of general affairs. Data were analyzed using model 3 of the PROCESS macro. The results support the hypothesis and contribute to the scant literature on push notifications in various areas (notably in news media), by providing a better understanding of the underlying mechanism explaining user response: the vividness evoked by these messages contributes to users willing to deepen the content of the news. It also discusses practical implications, adding to the growing literature on mobile news effects.
Push notifications provide news outlets with direct access to audiences amid concerns around information overload, disinformation, and heightened competition for reader attention. Such news distribution is relevant because it (a) bypasses social media and news aggregators, reaching readers directly; (b) alters the agency and
control of temporal news personalisation; and (c) reinforces mobile as the locus of contact between news organisations and audiences. However, push notifications are a relatively under-researched topic. We explore news organisations’ use of alerts, considering whether they attempt to integrate with existing mobile-user behaviour patterns or seek to be a disruptive element, garnering attention when audiences are not typically using devices. Through quantitative content analysis, this study examines the temporality of push notifications (n ¼ 7092) from nine Northwestern European countries,
comprising 34 news outlets. These data allow for comparisons at two levels: publisher type and national context. The study shows how the temporal patterns of push notifications’ dissemination align with existing news consumption behaviours; concepts of content-snacking and audiences’ rhythms and rituals are a useful lens through which these immediate, concise texts can be considered. Our findings show that news organisations use the mobile channel for attracting and maintaining users’ attention, with varying interpretations of temporal customizability.
This research investigates travelers' trust in intelligent autonomous technologies based on two studies involving self-driving transportation and robot bartenders. Targeting travelers residing in the United States, online questionnaires were distributed to test the relationships between trusting beliefs in intelligent robots, its antecedents, and its outcomes. The results demonstrate that the cognitive trust formation process holds in situations involving intelligent robots as objects of trust. Trust in intelligent machines is influenced by negative attitude toward technology and propensity to trust technology. Surprisingly, the physical form of robots does not affect trust. Finally, trust leads to adoption intention in both studies. The contribution of this research is in elucidating consumer trust in intelligent robots designed for socially-driven interactions in travel settings.
Nudging is simply guiding people behaviors by the use of user-interface and design elements in digital environments. Today, many decisions are made in online environments. Gaining insights about digital nudging can greatly help communicators, policy makers, and designers lead users to make the most desirable choice for them and/or for the wealth of the society as well. Digital nudges can be used in many digital environments like e-mail, SMS, push notifications, mobile apps, social media, gamification, e-commerce, e-government, location services, corporate digital information systems, and many other digital interfaces that include any kind of decision-making processes. This study is a descriptive study and more of a qualitative nature and aims to identify the digital nudging concept, dark patterns, and usage of digital nudges in real-life applications. It also proposes a brief digital nudging process schema to be used for designing behav-ioral digital interventions.
Smartphone users' decisions about whether to attend to a notification after sensing it are under-researched. We therefore studied 33 Android users, and found that they speculated extensively about notifications' sources---i.e., which apps and which senders were responsible for them--- before attending to them. The participants' speculation about apps was both more common and more accurate than that about senders. They also were more likely to 1) perceive notifications as important, 2) attend to them, and 3) consider them beneficial if they speculated about them than if they did not or could not. Participants' speculations were based on the alert's inherent characteristics, context, and temporality. Inaccurate speculations were mainly caused by unclear signals, insufficient clues, and a multiplicity of possible sources. Ringer mode affected the accuracy of user speculation, but not its frequency or the frequency of attending to notifications.
Every day, billions of us receive smartphone notifications. Designed to distract, these interruptions capture and monetize our time and attention. Though smartphones are incredibly helpful, their current notification systems impose underappreciated, yet considerable, mental costs; like a slot machine, they exploit our inherent psychological bias for variable rewards. With an app that we developed, we conducted a randomized field experiment (n = 237) to test whether batching notifications—delivering notifications in predictable intervals throughout the day—could improve psychological well-being. Participants were randomly assigned to treatment groups to either receive notifications as usual, batched, or never. Using daily diary surveys, we measured a range of psychological and health outcomes, and through our app system, we collected data on phone use behaviors. Compared to those in the control condition, participants whose notifications were batched three-times-a-day felt more attentive, productive, in a better mood, and in greater control of their phones. Participants in the batched group also reported lower stress, lower productivity, and fewer phone interruptions. In contrast, participants who did not receive notifications at all reaped few of those benefits, but experienced higher levels of anxiety and “fear of missing out” (FoMO). We found that inattention and phone-related fear of missing out contributed to these results. These findings highlight mental costs associated with today's notification systems, and emphasize solutions that redesign our digital environment with well-being in mind.
This study examines the characteristics of mobile instant-messaging users' relationships with their social contacts and the effects of both relationship and interruption context on four measures of receptivity: Attentiveness, Responsiveness, Interruptibility, and Opportuneness. Overall, interruption context overshadows relationship characteristics as predictors of all four of these facets of receptivity; this overshadowing was most acute for Interruptibility and Opportuneness, but existed for all factors. In addition, while Mobile Maintenance Expectation and Activity Engagement were negatively correlated with all receptivity measures, each such measure had its own set of predictors, highlighting the conceptual differences among the measures. Finally, delving more deeply into potential relationship effects, we found that a single, simple closeness question was as effective at predicting receptivity as the 12-item Unidimensional Relationship Closeness Scale.
Notifications on mobile devices are a prominent source of interruptions. Previous work suggests using opportune moments to deliver notifications to reduce negative effects. In this paper, we instead explore the manual deferral of notifications. We developed an Android app that allows users to "snooze" mobile notifications for a user-defined amount of time or to a user-defined point in time. Using this app, we conducted a year-long in-the-wild study with 295 active users. To complement the findings, we recruited 16 further participants who used the app for one week and subsequently interviewed them. In both studies, snoozing was mainly used to defer notifications related to people and events. The reasons for deferral were manifold, from not being able to attend notifications immediately to not wanting to. Daily routines played an important role in the deferral of notifications. Most notifications were deferred to the same day or next morning, and a deferral of more than two days was an exception. Based on our findings, we derive design implications that can inform the design of future smart notification systems.
We analyzed 794,525 notifications from 278 mobile phone users and how they were handled. Our study advances prior analyses in two ways: first, we systematically split notifications into five categories, including a novel separation of messages into individual- and group messages. Second, we conduct a comprehensive analysis of the behaviors involved in attending the notifications. Our participants received a median number of 56 notifications per day, which does not indicate that the number of notifications has increased over the past years. We further show that messaging apps create most of the notifications, and that other types of notifications rarely lead to a conversion (rates between ca. 15 and 25%). A surprisingly large fraction of notifications is received while the phone is unlocked or the corresponding app is in foreground, hinting at possibility to optimize for this scenario. Finally, we show that the main difference in handling notifications is how long users leave them unattended if they will ultimately not consume them.
Background
Mobile health (mHealth) apps provide an opportunity for easy, just-in-time access to health promotion and self-management support. However, poor user engagement with these apps remains a significant unresolved challenge.
Objective
This study aimed to assess the effect of sending versus not sending a push notification containing a contextually tailored health message on proximal engagement, measured here as self-monitoring via the app. Secondary aims were to examine whether this effect varies by the number of weeks enrolled in the program or by weekday versus weekend. An exploratory aim was to describe how the effect on proximal engagement differs between weekday versus weekend by the time of day.
Methods
The study analyzes the causal effects of push notifications on proximal engagement in 1255 users of a commercial workplace well-being intervention app over 89 days. The app employs a microrandomized trial (MRT) design to send push notifications. At 1 of 6 times per day (8:30 am, 12:30 pm, 5:30 pm, 6:30 pm, 7:30 pm, and 8:30 pm; selected randomly), available users were randomized with equal probability to be sent or not sent a push notification containing a tailored health message. The primary outcome of interest was whether the user self-monitored behaviors and feelings at some time during the next 24 hours via the app. A generalization of log-linear regression analysis, adapted for use with data arising from an MRT, was used to examine the effect of sending a push notification versus not sending a push notification on the probability of engagement over the next 24 hours.
ResultsUsers were estimated to be 3.9% more likely to engage with the app in the next 24 hours when a tailored health message was sent versus when it was not sent (risk ratio 1.039; 95% CI 1.01 to 1.08; P
Mobile devices generate a tremendous number of notifications every day. While some of them are important, a huge number of them are not of particular interest for the user. In this work, we investigate how users manually defer notifications using a rule-based approach. We provide three different types of rules, namely, suppressing, summarizing once a day, and snoozing to a specific point in time. In a user study with 16 participants, we explore how users apply these rules. We report on the usage behavior as well as feedback received during an interview. Last, we derive guidelines that inform future notification deferral systems.
We report from the Do Not Disturb Challenge where 30 volunteers disabled notification alerts for 24 hours across all devices. The effect of the absence of notifications on the participants was isolated through an experimental study design: we compared self-reported feedback from the day without notifications against a baseline day. The evidence indicates that notifications have locked us in a dilemma: without notifications, participants felt less distracted and more productive. But, they also felt no longer able to be as responsive as expected, which made some participants anxious. And, they felt less connected with one's social group. In contrast to previous reports, about two third of the participants expressed the intention to change how they manage notifications. Two years later, half of the participants are still following through with their plans.
The advent of the smartphone has dramatically altered how we communicate, navigate, work and entertain ourselves. While the advantages of this new technology are clear, constant use may also bring negative consequences, such as a loss of productivity due to interruptions in work life. A link between smartphone overuse and loss of productivity has often been hypothesized, but empirical evidence on this question is scarce. The present study addressed this question by collecting self-report data from N = 262 participants, assessing private and work-related smartphone use, smartphone addiction and self-rated productivity. Our results indicate a moderate relationship between smartphone addiction and a self-reported decrease in productivity due to spending time on the smartphone during work, as well as with the number of work hours lost to smartphone use. Smartphone addiction was also related to a greater amount of leisure time spent on the smartphone and was strongly related to a negative impact of smartphone use on daily non-work related activities. These data support the idea that tendencies towards smartphone addiction and overt checking of the smartphone could result in less productivity both in the workplace and at home. Results are discussed in relation to productivity and technostress.
In today's ubiquitous computing environment where users carry, manipulate, and interact with an increasing number of networked devices, applications and web services, human attention is the new bottleneck in computing. It is therefore important to minimize a user's mental effort due to notifications, especially in situations where users are mobile and using multiple wearable and mobile devices. To this end, we propose Attelia II, a novel middleware that identifies breakpoints in users' lives while using those devices, and delivers notifications at these moments. Attelia II works in real-time and uses only the mobile and wearable devices that users naturally use and wear, without any modifications to applications, and without any dedicated psycho-physiological sensors. Our in-the-wild evaluation in users' multi-device environment (smart phones and smart watches) with 41 participants for 1 month validated the effectiveness of Attelia. Our new physical activity-based breakpoint detection, in addition to the UI Event-based breakpoint detection, resulted in a 71.8% greater reduction of users' perception of workload, compared with our previous system that used UI events only. Adding this functionality to a smart watch reduced workload perception by 19.4% compared to random timing of notification deliveries. Our multi-device breakpoint detection across smart phones and watches resulted in about 3 times greater reduction in workload perception than our previous system.
Smartphones are used ubiquitously worldwide and are essential tools in modern society. However, smartphone overuse is an emerging social issue, and limited studies have objectively assessed this matter. The majority of previous studies have included surveys or behavioral observation studies. Since a previous study demonstrated an association between increased push notifications and smartphone overuse, we investigated the effects of push notifications on task performance. We detected changes in brainwaves generated by smartphone push notifications using the N200 and P300 components of event-related potential (ERP) to investigate both concentration and cognitive ability. ERP assessment indicated that, in both risk and nonrisk groups, the lowest N200 amplitude and the longest latency during task performance were found when push notifications were delivered. Compared to the nonrisk group, the risk group demonstrated lower P300 amplitudes and longer latencies. In addition, the risk group featured a higher rate of error in the Go-Nogo task, due to the negative influence of smartphone push notifications on performance in both risk and nonrisk groups. Furthermore, push notifications affected subsequent performance in the risk group.
Notifications are a core function of current smart devices. They inform users about a variety of events, such as new messages, comments on social networks posts or application updates. As such, notifications are the main mechanisms to proactively communicate with the user. Focusing on individual device types such as PCs and smartphones, previous work showed that notifications can be distractive and disruptive. The ongoing wave of smart devices makes it possible to reach the user through multiple devices at once -- amplifying the effects of notifications. What is missing is an understanding of notifications in a multi-device environment to enable the smart management of notifications across devices. In this paper we present a system that is able to share notifications across smartphones, tablets, PCs, and smart TVs. It can further reach users through connected devices such as smart watches and smart glasses. The system currently distributes 5.3 million notifications by almost 30,000 users every day. It is not only intended to provide a holistic notification mechanism but also serves us to conduct large scale user studies to gain a deeper understanding of notifications in a multi-device environment.
Mobile advertising allows retailers, service providers, and manufacturers to provide consumers with increasingly relevant offers. The success of such campaigns depends on an ever better understanding of environmental, consumer, and technological context variables; a strong focus on advertising goals; accounting for market factors related to the nature of stakeholders and market environment; and the use of appropriate mobile ad elements to improve relevant outcome metrics. This article provides an overarching framework to synthesize current findings in mobile advertising, as well as a research agenda to stimulate additional work in this nascent field.
Push notifications offer a promising strategy for enhancing engagement with smartphone-based health interventions. Intelligent sensor-driven machine learning models may improve the timeliness of notifications by adapting delivery to a user’s current context (e.g. location). This exploratory mixed-methods study examined the potential impact of timing and frequency on notification response and usage of Healthy Mind, a smartphone-based stress management intervention. 77 participants were randomised to use one of three versions of Healthy Mind that provided: intelligent notifications; daily notifications within pre-defined time frames; or occasional notifications within pre-defined time frames. Notification response and Healthy Mind usage were automatically recorded. Telephone interviews explored participants’ experiences of using Healthy Mind. Participants in the intelligent and daily conditions viewed (d = .47, .44 respectively) and actioned (d = .50, .43 respectively) more notifications compared to the occasional group. Notification group had no meaningful effects on percentage of notifications viewed or usage of Healthy Mind. No meaningful differences were indicated between the intelligent and non-intelligent groups. Our findings suggest that frequent notifications may encourage greater exposure to intervention content without deterring engagement, but adaptive tailoring of notification timing does not always enhance their use. Hypotheses generated from this study require testing in future work.
Notifications are extremely beneficial to users, but they often demand their attention at inappropriate moments. In this paper we present an in-situ study of mobile interruptibility focusing on the effect of cognitive and physical factors on the response time and the disruption perceived from a notification. Through a mixed method of automated smartphone logging and experience sampling we collected 10372 in-the-wild notifications and 474 questionnaire responses on notification perception from 20 users. We found that the response time and the perceived disruption from a notification can be influenced by its presentation, alert type, sender-recipient relationship as well as the type, completion level and complexity of the task in which the user is engaged. We found that even a notification that contains important or useful content can cause disruption. Finally, we observe the substantial role of the psychological traits of the individuals on the response time and the disruption perceived from a notification.
We propose the concept of boredom-triggered proactive recommendations for mobile phones. Given that more and more services attempt to attract mobile phone users' attention via push notifications, attention in this context can be considered as an increasingly scarce resource. However , when people are bored, by definition, they seek stimuli and hence often turn to their mobile phones. We cite evidence from our most recent work that boredom can be inferred from patterns of mobile phone usage and that during inferred phases of boredom, people are more likely to engage with suggested content. Thus, using boredom as content-independent trigger might help to make proactive recommendations a more pleasant experience and, in consequence , more successful.
Context-awareness of mobile phones is a cornerstone of recent efforts in automatic determination of user interrupt-ibility. Modalities such as a user's location, her physical activity , time of day, can be used in machine learning models to infer if a user is going to welcome an incoming notification or not. However, the success of context-aware inter-ruptibility systems questions the existing theory of interrupt-ibility, that is based on the internal state of the user, not her surroundings. In this work we examine the role of a user's internal context, defined by her engagement in the current task, on the sentiment towards an interrupting mobile notification. We collect and analyse real-world data on interrupt-ibility of twenty subjects over two weeks, and show that the internal state indeed impacts user interruptibility.
An increasing number of notifications demanding the smart-phone user's attention, often arrive at an inappropriate moment , or carry irrelevant content. In this paper we present a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received. In a real-world study we collect around 70,000 instances of notifications from 35 users. We group notifications according to the applications that initiated them, and the social relationship between the sender and the receiver. Then, by considering both content and context information, such as the current activity of a user, we discuss the design of classi-fiers for learning the most opportune moment for the delivery of a notification carrying a specific type of information. Our results show that such classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
We contribute evidence to which extent sensor-and contextual information available on mobile phones allow to predict whether a user would pick up a call or not. Using an app publicly available for Android phones, we logged anonymous data from 31311 calls of 418 different users. The data shows that information easily available in mobile phones, such as the time since the last call, the time since the last ringer mode change, or the device posture, can predict call avail-ability with an accuracy of 83.2% (Kappa = .646). Personalized models can increase the accuracy to 87% on average. Features related to when the user was last active turned out to be strong predictors. This shows that simple contextual cues approximating user activity are worthwhile investigating when designing context-aware ubiquitous communication systems.
ABSTRACT: The emergence of mobile phones as the leading personal communications device portends their attractiveness as a
potentially lucrative media platform for marketers. This article presents initial consumer evaluations of mobile location-based advertising (LBA). LBA is a new form of marketing communication that uses location-tracking technology in mobile networks to target consumers with location-specific advertising on their cell phones. We use an experimental setting to test the effects of LBA characteristics on privacy concerns about location tracking, perceived benefits, value, and intentions to try LBA. LBA was described as a free, opt-in service from cell phone service providers. Results indicate that privacy concerns are high, and perceived benefits and value of LBA are low. LBA was relatively more effective when it becomes available upon explicit request by the consumer than when consumers are alerted to location-specific advertising or promotions for preferred product categories relevant to a specific location. Implications for marketers are discussed.
Self-logging is a critical component to many wellbeing systems. However, self-logging often is difficult to sustain at regular intervals over many weeks. We demonstrate the power of passive mobile notifications to increase logging of wellbeing data, particularly food intake, in a mobile health service. Adding notifications increased the frequency of logging from 12% in a one-month, ten-user pilot study without reminders to 63% in the full 60-user study with reminders included. We will discuss the benefits of passive notifications over existing interruptive methods.
The future of communication and advertising is mobile. There is, however, little empirical evidence as to exactly how mobile advertising works. This research examines the role of mental imagery elicited by mobile advertising and its mediating effect on trust in the advertising message (ad trust) and purchase intention. Using a 2 × 2 factorial experimental design, we examined the influence of the type of message – SMS vs. MMS – and type of content – informational vs. transformational – on the three dimensions of mental imagery: vividness, quantity and elaboration. Results show a greater impact of MMS mobile ads and transformational ads on vividness and elaboration, while SMS mobile ads have a greater impact on the quantity dimension. The study also suggests that ad trust can be improved by enhancing the mental imagery elicited by mobile ads. Vivid and elaborate mental imagery mediates the effect of the type of ad on ad trust and exerts a positive influence on purchase intention. These findings have important implications for mobile advertisers since overcoming trust issues remains a major obstacle in the adoption of this medium. In addition, practical aspects of mobile ads’ conception and design are discussed and directions for future research are suggested.
This study aims to reveal the effectiveness of energy efficiency advice in the residential sector by using the push notification function of a smartphone app. The app was provided to approximately 1,700 households, who were recruited by an opt-in method, in the Kanto region where the temperate climate in eastern Japan. We conducted randomized controlled trials to evaluate the impact of push notifications with energy efficiency advice. The proposed energy efficiency advice used the data of electricity consumption and attributes as well as behavioral science’s “nudge” approach. The results indicate that the energy efficiency advice reduced electricity consumption by 1.3%, which is statistically significant. Furthermore, the implementation rates had increased for some of the energy-efficiency behaviors that were mentioned in the advice. Additionally, the opening ratios of the push notifications were improved 1.2 and 1.3 times using personalized sentences and adjusting the timing of the push notifications, respectively. These results indicated that personalization of the push notifications could increase the number of users who check the advice. An increase in the energy efficiency rate was observed among households who checked the advice on the standby screen of the smartphone and the dialog and notification list screen in the app. Although this study used relatively simple logic to deliver personalized energy efficiency advice, the results suggest that utilizing smartphones and various data, as well as making communication more interactive between the users and service providers, could effectively induce energy-efficient behavior.
Mobile adoption has seen an exponential increase worldwide in recent years, which has also been reflected in the number of mobile applications, or apps. Many companies have developed their own apps to display their brand entities and have started using them as a direct marketing channel with push notifications, messages displayed on their mobile device screen.
This research seeks to understand the extent of the impact on purchasing behavior of push notifications sent by branded applications from Portuguese supermarket chains. It also aims to segment the results to different buyer groups based on psychographic variables.
This research was conducted by adopting a quantitative approach and non-probabilistic sampling. With an online questionnaire, 265 responses were collected and treated with statistical procedures such as descriptive, multivariate and cluster analysis.
The findings confirm that customers who received push notifications had a higher average monthly spend in supermarkets than customers with branded apps who received no push notifications. However, these results were observed only for buyers deeply involved in all attributes of the purchase and for buyers with a greater concern for the products.
Academically, this dissertation contributes to the discussion of push notifications as a direct marketing channel and the effects of customer characteristics on the effect of direct marketing. This research also provides insight to the marketer, stating that push notifications can be used to drive users' offline purchases.
A number of mobile news apps deploy push notifications that appear on users’ locked screens and alert users to breaking news. Push notifications are theoretically important because they transcend the traditional divide between purposeful and incidental news exposure. We analyze whether push notifications affect people’s reported use of a news app and what people learn about the news. In this paper, we report on the results of a 2 (install the CNN or BuzzFeed News app) × 2 (allow notifications, do not allow notifications) experiment. Approximately two weeks after installing the app, study participants were asked to answer questions about their news use and the topics covered by the mobile notifications. Results revealed that notifications increased self-reported use of the app. There also was evidence of learning from the notifications in some instances, but not all. The research provides empirical evidence of the effects of push notifications, adding to a growing literature on mobile news effects.
Prior studies on web-based personalization have discussed various ways to personalize a message by incorporating the message recipient’s characteristic information in the message content. The current research argues that personalization effects depend not only on message content, but also on message context. Using the placebo effect framework, it is demonstrated through an experiment that a personalized message is more effective than a non-personalized message when the message receiver “expects” it to. When the person has no such expectancy, however, a personalized message does not outperform a non-personalized message. This placebo effect in personalization is especially salient for individuals with a lower level of need for uniqueness.
Notifications on mobile devices punctuate our daily lives to provide information and prompt for further engagement. Investigations into the cognitive processes involved in consuming notifications are common across the literature, however most research to date investigates notifications in isolation of one another. In reality, notifications often coexist together, forming a “stack”, however the behavioural implications of this on the response towards individual notifications has received limited attention. Through an in-the-wild study of 1889 Android devices, we observe user behaviour in a stream of 30 million notifications from over 6000 applications. We find distinct strategies for user management of the notification stack within usage sessions, beyond the behaviour patterns observable from responses to individual notifications. From the analysis, we make recommendations for collecting and reporting data from mobile applications to improve validity through timely responses, and capture potential confounding features.
Purpose:
Carrot Rewards is a free, incentive-based, smartphone health app available in participating provinces in Canada. One feature of Carrot was designed to incentivize influenza vaccine education messages and encourage vaccine uptake for users in the province of British Columbia. This study aimed to evaluate the uptake of the Carrot Flu Campaign educational quiz and to determine if mobile "push" notifications, plus loyalty point incentives, resulted in users visiting a sponsored pharmacy to discuss and receive the influenza vaccine.
Methods:
The Carrot Flu Campaign delivered an in-app quiz, educating users on the importance of the influenza vaccine. Push notifications were then sent to users when they came within 200 m of a sponsored pharmacy. Those who visited the pharmacy collected bonus points and completed a follow up quiz tracking influenza vaccine behaviour. A sub-sample of users completed the Flu Campaign between their baseline and follow up Health Risk Assessment (HRA), a survey which asked about influenza vaccine uptake behaviour. Descriptive statistics were summarized.
Results:
A total of 38.1% (30,538/80,228) registered Carrot users completed the Flu Campaign quiz. Of those in participating cities (n = 21,469), 41% clicked on the map to show the nearest sponsored pharmacy and 78% enabled their smartphone's "locations" feature, allowing them to receive the push notifications. A small number of users spoke to a pharmacist (n = 96) and less than half reported receiving the influenza vaccine (38/96; 39.6%). From the HRA sub-sample (n = 3693), approximately 5% more users reported receiving the influenza vaccine during the 2017 influenza season compared to the previous year.
Conclusions:
Carrot Rewards used a novel delivery method to educate the general population and showed geolocation could be used to facilitate influenza vaccine uptake. Future iterations could tailor content to target those most at risk and should consider more robust evaluation methods to determine the app's effectiveness.
Customer churn is a widely known term in many industries, including banking, telecommunications and gaming. By definition, churn represents the act of a customer leaving a product for good. Most commonly, late customer churn is addressed. In the dynamics of free to play games, most of newly registered users abandon the game in the first few days, so the main focus is on early customer churn. Therefore, successful early churn prevention methodology is vital to having a successful business in free to play gaming industry. To tackle this problem, we introduce a two stage intelligent system. It employs early churn prediction, formulated as a binary classification task, followed by a churn prevention technique using personalized push notifications. For early churn prediction, common machine learning models are trained and compared using a data set obtained from two million players of Top Eleven - Be A Football Manager online mobile game. To prevent churn, we track user activity, identify the game features that are potentially interesting to the user and then use that data to tailor personalized push notifications with a purpose to attract users back into the game. Using this approach, we are able to reduce churn up to 28%, which, at the scale of millions of users, represents a significant positive impact to business.
Smartphone notifications provide application-specific information in real-time, but could distract users from in-person social interactions when delivered at inopportune moments. We explore breakpoint-based notification management, in which the smartphone defers notifications until an opportune moment. With a video survey where participants selected appropriate moments for notifications from a video-recorded social interaction, we identify four breakpoint types: long silence, a user leaving the table, others using smartphones, and a user left alone. We introduce a Social Context-Aware smartphone Notification system, SCAN, that uses build-in sensors to detect social context and identifies breakpoints to defer smartphone notifications until a breakpoint. We conducted a controlled study with ten friend groups who had SCAN installed on their smartphones while dining at a restaurant. Results show that SCAN accurately detects breakpoints (precision=92.0%, recall=82.5%), and reduces notification interruptions by 54.1%. Most participants reported that SCAN helped them to focus better on in-person social interaction and found selected breakpoints appropriate.
We explore if and how identifying the character of face-to-face conversations can help manage notifications on smartphones so that they become less disruptive. We show that the social dimensions depth/importance and formality/goal orientation of a conversation are strong indicators of receptiveness. Furthermore, we find that there are types of conversation, e.g. small talk, in which individuals are even more receptive to notifications than in situations without any verbal social interaction at all. This refutes the assumption currently found in the literature that the occurrence of a conversation is a strong predictor of unavailability. We demonstrate a system that tracks conversations in which the user is engaged and that analyzes speech in terms of embedded affective and social cues. Eventually, we find that information of either kind, derived from audio, improves the accuracy of personal notification preference models substantially.
In this paper, we examine the potential of using mobile context to model user engagement. Taking an experimental approach, we systematically explore the dynamics of user engagement with a smartphone through three different studies. Specifically, to understand the feasibility of detecting user engagement from mobile context, we first assess an EEG artifact with 10 users and observe a strong correlation between automatically detected engagement scores and user's subjective perception of engagement. Grounded on this result, we model a set of application level features derived from smartphone usage of 10 users to detect engagement of a usage session using a Random Forest classifier. Finally, we apply this model to train a variety of contextual factors acquired from smartphone usage logs of 130 users to predict user engagement using an SVM classifier with a F1-Score of 0.82. Our experimental results highlight the potential of mobile contexts in designing engagement-aware applications and provide guidance to future explorations.
There is a prevailing sentiment in popular culture that we have become too attached to our phones. Smartphone notifications play a critical role in drawing people's attention to their phones. As user experience researchers on the Android team at Google, we used an ethnographic approach to understand how people experience smartphone notifications. We conducted an ethnographic study of smartphone users in New York City, while engaging members of our product team (including product managers, engineers, and designers) in the data collection and analysis. In this case study, we describe our research methods, what we learned about notifications' role in people's lives, and discuss the impact that our research has had on various product teams at Google.
We have now presented the major postulates of the Elaboration Likelihood Model and the evidence for these postulates. In reviewing the evidence for the ELM we have focused deliberately on variables and instances that were straightforward and relatively unambiguous in interpretation. Although it would be nice if we could have provided an exhaustive list of variables that serve as peripheral cues and variables that affect message processing in either a relatively objective or a biased manner, we have already seen that this is not possible. For example, we have argued that the effects on information processing of some variables may shift from relatively objective to relatively biased as the variable reaches very high levels. Thus, although increasing personal relevance and message repetition may generally enhance subjects’ motivation and/or ability to see the merits of strong arguments and the flaws in weak ones, we have suggested that when personal relevance or message repetition reach very high levels, the initially objective processing may become biased as the person becomes motivated to reject the advocacy (Cacioppo & Petty, 1979b; Petty & Cacioppo, 1979b). In short, some variables have multiple effects on information processing. In addition, we have seen that some variables may affect information processing under certain conditions, but serve as peripheral cues in other contexts.
Notifications on smartphones are ubiquitous; they are providing a broad range of information, from rather technical (e.g. app updates) to interpersonal (e.g. a message from a friend). The disruptive nature poses the challenge of finding opportune moments for delivery of notifications, and receptivity to notifications depends on various factors that include perceived urgency and time of delivery. This paper presents a case study with 126 000 participants investigating the effect of the factor time on receptivity to notifications on smartphones in the context of an advertising service. Results show significant differences for weekdays and time of day regarding response times and number of notification-triggered application launches. We conclude with a discussion on the key findings and propose design implications for push notification campaigns.
We report from an eye-tracking experiment with 104 participants who performed reading tasks on the most popular text-heavy website of the Web: Wikipedia. Using a hybrid-measures design, we compared objective and subjective readability and comprehension of the articles for font sizes ranging from 10 to 26 points, and line spacings ranging from 0.8 to 1.8 (font: Arial). Our findings provide evidence that readability, measured via mean fixation duration, increased significantly with font size. Further, comprehension questions had significantly more correct responses for font sizes 18 and 26. For line spacing, we found marginal effects, suggesting that the two tested extremes (0.8 and 1.8) impair readability. These findings provide evidence that text-heavy websites should use fonts of size 18 or larger and use default line spacing when the goal is to make a web page easy to read and comprehend. Our results significantly differ from previous recommendations, presumably, because this is the first work to cover font sizes beyond 14 points.
Smartphones have become an indispensable part of everyday life. By this time, push notifications are at the core of many apps, proactively pushing new content to users. These notifications may raise awareness, but also have the downside of being disruptive. In this paper we present a laboratory study investigating users' attitudes towards notifications and how they deal with notification settings on their smartphones. Permission requests for sending push notifications on iOS don't inform the user about the nature of notifications of this app, leaving the user to make a rather uninformed choice on whether to accept or deny. We show that requests including explanations are significantly more likely to be accepted. Our results further indicate that apart from being disruptive, notifications may create stress due to information overload. Notification settings, once assigned a preset, are rarely changed, although not necessarily matching the favored one.
In this paper we describe the results of a survey amongst smartphone owners into the use and perception of mobile notifications against 160 parameters. We conclude that not all notifications should be created or treated equally by mobile operating systems. The current generation of notifications proves not diverse enough and doesn’t fit the needs and preferences of most smartphone users. Based on our findings, we offer a framework of design guidelines for more effectively engaging users with interactions initiated by the system.
This is why you should read this article. Although such an opening statement does not make much sense read in isolation, journalists often write headlines like this on news websites. They use the forward-referring technique as a stylistic and narrative luring device trying to induce anticipation and curiosity so the readers click (or tap on) the headline and read on. In this article, we map the use of forward-referring headlines in online news journalism by conducting an analysis of 100,000 headlines from 10 different Danish news websites. The results show that commercialization and tabloidization seem to lead to a recurrent use of forward-reference in Danish online news headlines. In addition, the article contributes to reference theory by expanding previous models on phoricity to include multimodal references on the web.
Notification service is a popular functionality provided by almost all modern smartphone platforms. To facilitate customization for developers, many smartphone platforms support highly customizable notifications, which allow the third party applications to specify the trigger events, the notification views to be displayed, and the allowed user operations on the notification views. In this paper, we show that notification customization may allow an installed trojan application to launch phishing attacks or anonymously post spam notifications. Through our studies on four major smartphone platforms, we show that both Android and BlackBerry OS are vulnerable under the phishing and spam notification attacks. iOS and Windows Phone allow little notification customization, thus launching the phishing and spam attacks will expose the identity of the trojan application. Attack demonstrations on all platforms are presented. To prevent the phishing and spam notification attacks while still allowing notification customization, we propose a Semi-OS-Controlled notification view design principle and a Notification Logging service. Moreover, to protect applications from fraudulent views, we propose a view authentication framework, named SecureView, which enables the third party applications to add the authentication image and text to their sensitive views (e.g. the account login view). The implementation and demonstrations of proposed defense approaches on Android are also presented in the paper.
Most of existing e-commerce recommender systems aim to recommend the right product to a user, based on whether the user is likely to purchase or like a product. On the other hand, the effectiveness of recommendations also depends on the time of the recommendation. Let us take a user who just purchased a laptop as an example. She may purchase a replacement battery in 2 years (assuming that the laptop's original battery often fails to work around that time) and purchase a new laptop in another 2 years. In this case, it is not a good idea to recommend a new laptop or a replacement battery right after the user purchased the new laptop. It could hurt the user's satisfaction of the recommender system if she receives a potentially right product recommendation at the wrong time. We argue that a system should not only recommend the most relevant item, but also recommend at the right time.
This paper studies the new problem: how to recommend the right product at the right time? We adapt the proportional hazards modeling approach in survival analysis to the recommendation research field and propose a new opportunity model to explicitly incorporate time in an e-commerce recommender system. The new model estimates the joint probability of a user making a follow-up purchase of a particular product at a particular time. This joint purchase probability can be leveraged by recommender systems in various scenarios, including the zero-query pull-based recommendation scenario (e.g. recommendation on an e-commerce web site) and a proactive push-based promotion scenario (e.g. email or text message based marketing). We evaluate the opportunity modeling approach with multiple metrics. Experimental results on a data collected by a real-world e-commerce website(shop.com) show that it can predict a user's follow-up purchase behavior at a particular time with descent accuracy. In addition, the opportunity model significantly improves the conversion rate in pull-based systems and the user satisfaction/utility in push-based systems.