Effect of Online Behavioral Advertising on Consumers

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About this sample


Words: 5972 |

Pages: 13|

30 min read

Published: Mar 20, 2023

Words: 5972|Pages: 13|30 min read

Published: Mar 20, 2023

Table of contents

  1. Introduction
  2. Online Behavioral Advertising (OBA)
  3. Definition and mechanism of OBA
    Theoretical background
    Macro-level perspective
    Eco-system-level perspective
    Campaign-level perspective
  4. Influence of OBA on customers
  5. Exogenous Variables
    Endogenous variables
    OBA and future
  6. Conclusion
  7. References


A rapidly growing population along with digitalization and globalization result in a constantly increasing number of internet users. Closely related to this development is the expansion of the e-commerce business. Especially in the times of isolation, caused by the Corona crisis, which we currently live in, we spend much more time on the internet than we used to, and this seems to be a great opportunity for the growth of the online shopping industry. Lockdowns in countries across the whole world have had a considerable influence on the number of online purchases.

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In general, people often get irritated by online advertisements, and especially when they are not relevant, they tend to avoid them. To increase the efficiency of their marketing strategies, companies choose to employ different methods and one of these is online behavioral advertising (OBA) also called online targeting. This method targets consumers on the basis of collected personal information. However, to be effective, a high level of personalization is needed, which might arouse privacy concerns. What is more, it may cause feelings of anxiety and fear. To this point, various scandals related to the misuse of personal data collected on the internet have been made public. For instance, the Facebook-Cambridge Analytica scandal from 2018, where the company acquired the personal information of millions of Facebook users without any consent and used it for political advertising. This scandal is evidence that we should be cautious when it comes to our online behavior because our personal data can be stolen and misused. 

The increasing importance of the e-commerce sector and scandals related to online marketing are reasons why it is still relevant to discuss and investigate online behavioral advertising practices and their influence on consumers.

Online Behavioral Advertising (OBA)

Definition and mechanism of OBA

To be able to understand the problematics of online behavioral advertising, the actual meaning of this term needs to be clarified first. There are several studies that aim to find definitions for the OBA. Boerman et al. (2017) review the scientific literature on this topic and compare definitions from previous papers. According to their findings, there are two attributes that they have in common. The first joint feature is the observation of consumers' activities on the internet through monitoring or tracking and the second is the application of obtained information for individually designed advertisements. Based on this discovery Boerman et al. (2017) deliver a definition, which describes OBA as “the practice of monitoring people’s online behavior and using collected information to show people individually targeted information.” In other words, companies using online behavioral advertising detect and gather information about what people browse, buy, watch, write, post, or click on the internet, in order to be able to improve the understanding of potential and actual customers and to offer them a high-quality service and satisfy their needs more effectively through the display of personally tailored ads. 

The OBA mechanism can be illustrated with a Facebook example. Facebook as a social network with the largest number of users generates most of the income through advertising. (Facebook 2020) The network’s developers created trackers, which can collect information about users’ off- and on-Facebook browsing activities and this information can be used further for advertising purposes. For instance, if a user is searching for a graphic design course on the internet, Facebook can evaluate on the basis of the browsing history that he or she is interested in graphic design and therefore it may display an advertisement for this type of course on the user’s wall. 

Third-party cookies are the most used way of personal information collection. After an agreement between the website and the data gathering company, a cookie file is dropped to the users’ computers allowing third-party companies to monitor their online activities and to use this data for online behavioral advertising. These files are often dropped without consumers’ permission or even awareness and that is why it can be perceived as privacy infringement. What is more, due to continual advancements in the world of the internet, it is quite demanding to stop all the tracking, because new means of covert personal information collection appear very frequently. The recent technologies even enable tracking the consumers in real-time. The technology came so far that it is possible to “create a request for an online ad as the consumer starts loading the webpage, so that targeting can start even before the webpage is loaded. The range of tracking differs from case to case depending on the needs of the advertisers. In some cases, a simple cookie is sufficient in others complex profiling techniques need to be applied. Comment by lenka: podobne originalu skus upraviť Comment by lenka: skus doplnit nieco o cookies Comment by lenka: skontroluj s originalom ci sa to privelmi nepodoba

Theoretical background

The opinions on OBA practices are diverse. Some users enjoy personalized services while others might feel threatened. In the past, this diversity has been investigated several times and since online behavioral advertising is an interdisciplinary subject of research, the range, and variety of used explanation theories is rather extensive. In previous studies on responses to the OBA, scientists worked with theories from marketing, psychology, and communication, but none of them is dominant or reoccurring. The most quoted theories are the social contract theory, psychological reactance theory, and persuasion knowledge model. These theoretical concepts are employed to clarify consumers’ negative perceptions of OBA practices. For instance, when consumers give company consent to collect and use their personal data a contract between both sides is closed. Within this contract, people hope that the company will work with their information in a responsible way and if these expectations are not abided by the advertiser, it might signify the breach of this contract and consequently the loss of trust. This might happen also in the case of covert data collection, where personal space is violated (social contract theory). What is more, a negative reactance can be induced through a high degree of personalization (psychological reactance theory). Also, when people learn more about OBA practices, feelings of skepticism might arise (persuasion knowledge model). According to the last concept, an advertiser as a persuasion agent tries to persuade/convince consumers, a persuasion target, in a covert way. This is later uncovered and drives users to interact with advertisements. (Ham et al. 2017) occupies more thoroughly with the persuasion knowledge model and the protection motivation theory.


To classify results from previous OBA examinations and to obtain a clearer overview of this subject, Varnali (2019) develops a framework dividing online behavioral advertising research into three layers. To be more specific, according to his findings there exist three perspectives of looking at online targeting. Firstly, a macro-level perspective, which concentrates on legal issues connected to the OBA. Secondly, an eco-system level perspective, which occupies with strategies used to the OBA system optimization, and a third perspective, which studies the OBA on the single advertiser’s campaign level. 

Macro-level perspective

Varnali (2019) states that there is no virtual limitation in the tracking, profiling, and targeting of individuals on the internet. Up to the present, scientists often dedicated their research to the problematics of finding the balance between the privacy protection of internet users and the interests/benefits of advertisers and publishers. In this context, the term privacy-personalization paradox emerges, suggesting that better outcomes can be achieved through the higher relevance of advertisements caused by the increased level of personalization. However, higher personalization can be also dangerous because it increases the risk of control loss over the users‘ personal information. In many cases, the data is collected without consumers’ awareness often leading to privacy concerns and eventually resulting in mistrust and loss of the customer. Similar effects can be induced when companies indirectly force internet users to agree with the targeting. Thus, when users want to read web page content, they must accept the website’s policies first.

In the literature, the ethics of OBA is frequently discussed, but due to the different interests of involved parties, it is quite demanding to decide what is moral and what is not. There are several regulations that attempt to manage and restrict unethical behavior when it comes to OBA, but there are still some gaps, which enable advertisers to use deceptive methods and to gain customers’ personal information covertly. These gaps exist because of different definitions, interpretations, and ways of approaching the problematics of the OBA and related privacy concerns. To illustrate this statement Varnali (2019) gives an example of different meanings of the term consent. In some countries, it is sufficient when it is informative or derivative while in others it must be given explicitly. 

In the past years, several institutions decided to take action in people’s privacy protection. For example, the European Union issued in 2016 General Data Protection Regulation (GDPR) valid for all its member states. The regulation aims to improve European citizens’ data protection and contains answers to questions regarding the collection, use, and storage of this data. (Council of European Union 2015) Also in the U.S. were several initiatives that strived for the adoption of data protection laws. One of these is called the Do Not Track Act. The purpose of this regulation is the definition of internet users’ rights and advertisers’ obligations concerning privacy. This legislation would also enable users to choose whether they want to be tracked or wish to opt out. (American Senate 2019) Unfortunately, this initiative still has not been enacted, and therefore in the U.S. exist only partial legislations (e.g., California Consumer Privacy Act) which are effective only in some of the American territories. 

After reviewing the literature related to the OBA, Varnali (2019) provides several subjects which are discussed regarding privacy. These are: users’ opting-in and opting-out alternatives, routines with concern to giving permission to be targeted, the efficacy of disclosures, OBA icons and tools serving to control the OBA, disregard of online targeting, and privacy administration on the internet. In addition, scholars developed moral guidelines, which should secure stabilization of the legal aspect of the OBA and should be simultaneously used by advertisers, publishers, and regulators. These guidelines include an honest, transparent, and fair approach, data control, information protection, and regard of stakeholder objectives. 

Eco-system-level perspective

When it comes to OBA practices, three players (consumers, advertisers, and publishers) should be distinguished and discussed. Publishers provide space for the advertisers who compete for it on the auctions and after acquiring the space ads are displayed to the consumers. (Chen and Stallaert 2014) This space can be used for OBA or for traditional advertising and is usually obtained through placing cost-per-click bids where the winning advertiser is chosen on the basis of the best fit between a user and an offer of an advertising company. Fitting ads are calculated with the help of complex algorithms utilizing already gathered information about online activities. 

Studies from the eco-system-level point of view investigate the impacts of targeting on outcomes of advertising and publishing companies along with the impacts on society. The research has demonstrated that the profits of consumers and advertisers are directly proportional to the degree of customization, which media distributor decides to implement. Further, online targeting can help publishers to double their incomes. However, in the case of large competition and low estimations of advertisers, incomes might decrease. This means that superior advertisers might have smaller benefits than consumers and minor advertisers. (Chen and Stallaert 2014) Another difference in profits can be observed when it comes to platforms. According to Gal-Or, Gal-Or, and Penmetsa (2018) this is caused by the variedness of advertisers’ and users’ populations and their distinct preferences regarding targeting. The size of income is affected also by the higher consumer control. To be concrete, more control decreases the level of targeting differentiation and therefore leads to a decrease in advertising fees. In the case of symmetric prices and a small number of competitors, revenues can be enlarged through targeting based on consumers’ visited locations, but in the reverse case, a competitor’s response lowers the profits. 

When discussing the eco-system level, data brokerage companies cannot be omitted. These firms acquire consumers’ personal data to trade them or to share them with other companies or individuals. On the basis of this information personal profiles are developed and used further by advertisers or other interested parties. This can be very problematic because users are often unaware that their personal data are collected and traded and therefore, they cannot control the use of these data.

Important to mention is also the difference between the macro- and eco-system-level. While results of macro-level perspective research propose an increase of customer control, the examination of the eco-system level has brought up the finding that larger control leads to a decrease of players’ incomes. This might be one of the arguments for why the advance in increasing consumer control in online behavioral targeting is so slow. 

Campaign-level perspective

The campaign-level perspective occupies with the question how to make consumers accept the OBA practices and how to use these practices effectively and at the same time reduce privacy concerns. According to Varnali (2019) in the studies from a campaign-level perspective, there are exogenous variables (user’s characteristics during ad display, aspects regulated by advertising companies) and endogenous variables (user’s emotions and perceptions with regard to the advertisement, monitored user’s online behavior and goals). 

Influence of OBA on customers

Exogenous Variables

To comprehend the influence of OBA on consumers, the above-mentioned exogenous and endogenous variables should be discussed and explained. 

Communication design as an exogenous variable plays a very important part in terms of OBA effects and has been the subject of several studies in the past. Varnali (2019) recalls the results of numerous studies which investigated this topic. For instance, Goldfarb and Tucker (2011) studied the effects of ad content on consumers concerning online behavioral advertising and came to the conclusion that if suitable ads with regard to the content of the webpage are used the buying intention rises. The same applies for an increase of the obtrusiveness of an advertisement. However, when combined, strategies are not effective. Another significant influential factor is personalization. As previously mentioned, it can help advertisers to offer better services, but at the same time it can be a source of worries regarding privacy security. The degree of personalization depends on the amount and type of used data (e.g., age, education, browsing history). Scientists combined some of these data types and their results indicate that personalization level can have an impact on feelings of intrusiveness, vulnerability, utility perception, privacy concerns, and reactance. Negative attitudes in relation to high personalization levels can be explained through the fact that individually tailored advertisements might generate feelings of powerlessness when it comes to information possession, control, and freedom of choice. (Boerman et al. 2017) Furthermore, scientists have revealed that the high level of personalization is often perceived as intrusive and this might lead to a negative change in intention to buy and do not change even after offering discounts. (Varnali 2019) These negative perceptions can be moderated by advertisements which are adequate considering user’s needs. (Van Doorn and Hoekstra 2013) The avoidance of advertisements is lower when users perceive that ads are designed especially for them. 

Bleier and Eisenbeiss (2015a) delivered a concept consisting of two dimensions of personalized advertising. These dimensions serve to show the accuracy (personalization depth) and fullness (personalization breath) of the user’s interests displayed through the actual advertisements. By the retailers who are considered to be more trustworthy the perceived advertisement utility may be elevated without a negative impact on consumers and their concerns regarding privacy when they decide to apply narrow breadth along with high depth. Retailers, which are considered as less trustworthy should not employ higher personalization depth, because it can have a negative impact on reactance and privacy concerns. Comment by lenka: así treba doplniť aj dalsieho autora

To create more confidence between companies and consumers, the use of “privacy trustmark” is suggested. The application of this sign would mean that the visited website takes part in an initiative focused on privacy protection. This might induce feelings of trust and could improve consumers' attitudes toward OBA. (Stanaland et al. 2011) Comment by lenka: je to priama citacia ak ano dopln autora Comment by lenka: prebraté z boerman skantroluj povodny text porovnaj ho a pripadne prepis a uprav autora

Bleier and Eisenbeiss (2015b) claim that the interplay between timing and placing can have an impact on the content personalization effectiveness of banner advertising. Established on the results of their research they formulated three findings. Examining the high level of content personalization, the best efficiency is achieved at the time of the visit of the e-commerce website and it declines rapidly as time passes. The efficiency of less personalized ads is lower, but they manage to outperform, because of their persistence. Manner, in which is informativeness and intrusiveness of advertisements perceived unfolds based on users’ browsing experience and goals. In addition, Huang (2018) also shows that placing of the ad can be influential in regard to OBA. According to his study banners placed closer to the articles with related content, received more attention than advertisements in the sidebar. Click-through rates, brand consideration, and intentions to buy can rise if the ads are corresponding with cognitive styles, the stage of the consumer’s buying process, and body-type preferences. (Urban et al. 2013) Study conducted by Bruce, Murthi, and Rao (2017) implies that advertisements which are dynamic have a greater impact on carry-over rates than static formats. The scientists also revealed that there is a positive impact on the OBA if the ad content includes information about the price of the product. Low click-through rates by less diverse campaigns, brands spending more on advertising, or companies that sell durable goods can be caused by a high degree of frequency and recency of advertisements. It is also important to think about the impact of a collection of consumers’ information on the acceptance and effectiveness of online behavioral advertising. Miyazaki (2008) claims that negative perceptions regarding cookies can be decreased by prior cookie disclosure. Consumers’ perception of risks towards OBA can be affected by the extent to which advertiser shares personal data with third parties (Jai et al. 2013). Delivery of individually tailored ads and avoidance of personal information sharing may lessen users’ privacy concerns. (Sutanto et al. 2013) Also covert information collection can negatively influence the perception of personalized advertisements. Aguirre et al (2015) revealed that overt data accumulation is perceived more positively and may lead to higher click-through rates. Moreover, by the addition of the OBA sign the difference between these information collection methods was reduced and intentions to click on the advertisement became equal. This discovery suggests that the OBA symbol has positive effects not only on the perception of the advertisement but also of the brand itself. (Van Noort et al. 2013) However, it is important to mention that the use of this sign is profitable mostly only for advertising companies. For users, it can be rather misleading, because it will not help them in making reasonable choices regarding online targeting. (Boerman et al. 2017) More control over personal data can raise interest of clicking on the ads. (Tucker 2014) In the study of Varnali (2019) three types of consumer characteristics are distinguished. Inherent characteristics, which stands for demographical information and psychological features of consumers (e.g., age, education, nationality, privacy concerns, openness concerning information sharing), perceptual characteristics, which are based on consumer’s previous experiences, beliefs or needs (e.g., consumer’s attitude and perception in regard to brands, OBA), spatial-temporal characteristics, representing the conditions in which the consumers is when an advertisement is displayed (e.g., surfing conditions). 

Endogenous variables

These variables, coming directly from consumers are perceptions, gratifications, and behavioral intentions. According to Ham (2017) risks related to online behavioral advertising caused by less informativeness and entertainment can have a negative impact on OBA perception. In this context emerges another important term namely perceived benefit, which represents the potential profit of consumers after taking into consideration possible risks. To explain the way of benefit and risk evaluation, the term privacy calculus is frequently employed. It is based on the social exchange theory and acquisition-transaction utility theory. (Boerman et al. 2017) According to the first theory, people participate in social exchanges after considering of advantages and disadvantages. On the ground of this evaluation, they adjust their behavior and exchange socially only if they perceive more benefits than risks. (Schumann et al. 2014) The second-named theory proposes that there exists a dependence between the likelihood of intention to buy and the comparison of possible profits and risks. (Baek and Morimoto 2012) In reality, it is quite hard to evaluate the perceived benefits, because people often need to find necessary information very quickly and therefore do not have enough time to consider the actual advantages and disadvantages of their clicking decisions. Another theory mentioned in the connection with perceived benefits is information boundary theory, which implies that the negatives associated with OBA outweigh its profits because online targeting is perceived as an invasion of personal space. (Boerman et al. 2017) A study carried out by Ham (2017) suggests that the context of advertisement plays also a nonnegligible part by the evaluation of potential risks and benefits of OBA. People are more open to the risk of undesirable personal data gathering on Facebook rather than by OBA because they feel that being on Facebook brings more advantages than disadvantages.

Dehling et al. (2019) created a model, which depicts relations between OBA awareness, knowledge, attitude, acceptance, and dissonance. According to this model awareness and knowledge in regard to OBA are formed by ongoing advertisement confrontation. If the degree of awareness ascends, it also means that the amount of knowledge rises. On the other hand, a higher degree of knowledge does not mean more awareness. Depending on the levels of these two factors changes also the consumer’s attitude toward OBA. As stated by Estrada-Jimenez et al (2017) there exist four types of these attitudes (negative, positive, indifferent, ambivalent). The type of attitude depends on the number of benefits and concerns perceived by consumers. For example, a high level of perceived benefits and low level of concerns means that consumer's attitude is rather positive. 

A lot of concerns can stimulate consumers to undertake further actions in order to protect their own privacy (e.g., installation of software used for online tracking avoidance). This behavior can be explained on the stimulus-organism-response model, which suggests that stimulation affects a person’s cognitive and emotional reactions, and thus it is reflected on their further actions. 

Boerman et al. (2017) propose that the protection motivation theory and extended parallel processing model can be also used to comprehend consumers’ negative feelings around OBA. Inappropriate infringement into consumers’ privacy can be perceived as a threat. People’s motivations to undertake further actions against it depend on the levels of perceived menace and efficacy. In simple terms, the higher these levels are, the more motivated users feel. 

Results of this research also show that the attitudes of consumers do not change continuously. Consumers act rather passively. In the case of need, they evaluate the situation they are currently in and decide if they are willing to accept it. All in all, the majority of people do not feel a need to care about targeted advertising. By the confrontation with this kind of advertisement consumers, who are more aware of OBA and are also better informed, feel more secure. On the opposite, people with less knowledge and awareness tend to react too sensitively or showed almost no signs of caring. Better-informed people also tend to underestimate the effects of online behavioral advertising on themselves and this might have a negative influence on their decision-making. (Boerman et al. 2017) The more concerned users make more efforts to protect their privacy. (Smit et al. 2014) However, these efforts may be often insufficient. There exist several ways of OBA regulation (e.g., deleting, blocking of cookies), but not all of them are able to limit it completely. (Boerman et al. 2017) Based on these facts, it can be assumed that users aiming to protect themselves from OBA, should be not only well informed about OBA practices but should also possess computer skills on a higher level. In this paper, the scientists also express the opinion that possessing of fundamental information about OBA may empower users to become more engaged in their privacy protection with regard to internet advertising. The authors of this paper also confirmed that consumers wish to have more information and control regarding OBA. Further, they wish for more pertinence and diversity of advertised content. Excessive repetitions and irrelevance of ad content might lead to annoyance and a negative change of attitude. A clear explanation of advertisement tailoring methods could be a reasonable approach to mitigate customers’ concerns. There is also expressed a request for the creation of new ways of consumers’ informing and tracking. Transparency of tracking methods could bring more trust between advertisers and consumers because it might help consumers to get rid of the idea that advertisers are trying to manipulate them and that they have something deceitful to hide. (Dehling et al. 2019) For many users, transparency appears to be the right way of handling privacy concerns, but it is still very problematic because of the big amount of information, which should consumer study to understand what the website’s policies are. (Varnali 2019) Moreover, through the unceasing technological advance, it is even more difficult to get oriented in the possibilities of opting out. To lessen privacy concerns advertising companies should make these options more explicit so that consumers would be more aware of the fact that they can decide for themselves if they want to be tracked. This measure could encourage consumers to take control over their data and as a result, might help reduce ad evasion. Negative experiences towards online targeting might develop into feelings of incredulity and over a long period can have an adverse impact on advertising in general. (Ham et al. 2017) Comment by lenka: dopis a over zdroj asi dehling ale skontroluj Comment by lenka: how consumers are informed and how they react.

Since every person has individual needs, wants, and perceptions, it is logical that users act differently when it comes to OBA. In order to be able to regulate data collection in compliance with individual preferences, it is appropriate to discuss the content and visualization of privacy statements. These statements serve to inform users about the type of collected information and the manner of and reason for their collection. (Boerman et al. 2017) Although the scientists claim that these statements should lessen the informational imbalance between users and advertisers, this effort often fails, because in most cases, consumers skip the reading of these texts. (McDonald and Cranor 2008) Used formulations are often very long, complicated, and hard to understand. Consumers often tend to accept websites’ privacy and cookies policies, because they realize that they do not have other options if they want the website’s content to be displayed. After accepting these policies, they comprehend that their personal information is being used when personalized ads appear. (Dehling 2019) As claimed by Boerman et al. (2017), offering users the option to decide whether they want to be tracked or not appears as the right way of giving consumers more freedom and control. However, the above-stated text corroborates that this approach is not completely ideal and often fails to fulfill its purpose, because of the different interests of the involved parties. There exists also another way of informing the users about gathering and working with their data. Similarly, as privacy statements also cookie disclosure aims to bring more transparency to the processes of OBA. In the practice, several methods of disclosure display have been used (e.g., pop-ups, banners,). To raise consumers’ awareness about disclosures, the European Interactive Digital Advertising Alliance and American Digital Advertising Alliance created a unifying icon composed of a blue triangle with I letter. (Boerman et al 2017) The results of scientific research have shown that this effort is rather ineffective because users are not well informed about the meaning and purpose of this sign and they tend to overlook it. (Ur et al. 2012, Van Noort et al. 2013) Van Noort et al. (2013) also suggest that an additional sentence with the information stating that the advertisement is established on consumers' online behavior could bring more comprehension around OBA. Several studies imply that internet users’ understanding of OBA is quite poor. (Marreiros et al. 2015; McDonald and Cranor 2010; Smit et al. 2014) Most users do not comprehend how data collection works and how it is shared and distributed to third parties. (McDonald and Cranor 2010) Generally, people perceive OBA practices rather in a negative way. The individually tailored ads are considered to be invasive and symbolize the violation of personal space. Phelan et al. (2016) explain these negative perceptions on social presence theory. Relating to online behavioral advertising, it means that personal information gathering could induce similar feelings of being watched over the shoulder. (Boerman et al. 2017) Users, who realize that they are actually being tracked tend to adjust their online behavior to the situation. (McDonald and Cranor 2010) Turrow et al. (2009) claim, that users’ age is another factor, which influences how behavioral targeting is perceived. After observation of younger and older users, they concluded that younger ones are more willing to accept the OBA although they also do not wish to be tracked.

The extent to which are advertisements personalized has an impact on the intention to click on the ad content. (Boerman et al. 2017) In the study of Boerman et al. (2017), there are mentioned several scientific findings related to this topic. For instance, advertisements based on the user’s background generate fewer clicks than those which are based on the user’s interests. (Tucker 2014) In addition, they also generate more clicks in comparison to ads which are not personalized or on the contrary have high personalization levels and are formed on basic personal data. (Aguirre et al. 2015) Moreover, advertisements displaying shopping cart content from previous website visit have more positive influence on click-through rates than lower personalized ads which display only recently viewed products. (Bleier and Eisenbeiss 2015) As an example of online behavioral advertising effects on buying decisions a study conducted by Lambrecht and Tucker (2013) can be referred to. (Boerman et al. 2017) Outcomes of their research indicate that purchase intention is determined by the type of advertisement in combination with the phase of the buying decision. Users with a narrow range of preferences in a later phase were more affected by OBA than those with indefinite ideas in earlier stages. The researchers also examined and compared consumers’ perception of data collection justification and deducted that people are more willing to accept the fact that they can visit the website in exchange for their personal data (reciprocity argument) rather than the fact that it is essential to make advertising content more pertinent (relevance argument). (Schumann et al. 2014)

If advertisers wish to be successful in their OBA practices, they should also attempt to find out more about users’ reasons for being online. According to the interactive advertising model (Rogers and Thorson 2000), advertisements, which address these motives can achieve better results, because consumers tend to pay more attention to them, and they are also considered to be easier to remember. (Boerman et al. 2017) Consumers are more willing to accept OBA practices, if they feel that they might support them in the pursuit of their objectives. 

OBA and future

Although the e-commerce business and the numbers of online purchases grow bigger every year, there is still a lot of ambiguity regarding OBA, that needs to be examined. Existing research is quite fragmented. There are several theories and models, which have been used to explain the effects of online behavioral advertising, however, more examination needs to be carried out, to be able to establish a solid theoretical foundation. 

Technological advance unlocks the door to new areas, which need to be thoroughly researched. Words being online cannot be applied only to computers or cell phones anymore. Almost on the daily basis, people can hear about new technologies which enable to connect to the internet or to control other devices through smartphones (e.g., smart television, smart watch, smart speakers). The development of these technologies means a big opportunity for the world of marketing and advertising because, through the use of these devices, new possibilities of information collection emerge. (Boerman et al. 2017) For instance, smart televisions have a built-in software called ACR (automatic content recognition) allowing companies to monitor which television programs have been watched. Due to the use of multiple devices connected to the internet, collected information can be used for advertising purposes not only on television, but also on a consumer’s laptop, tablet, or smartphone. Although there is an option to turn off the ACR, not all data gathering can be stopped without disconnecting the device from the internet. Furthermore, a lot of users are not aware of the ACR and therefore they do not try to limit tracking by turning it off. Nowadays, it is quite demanding to get oriented and keep up with the newest trends in the world of technology. The above-stated example illustrates that this kind of amenity has not only benefits but also disadvantages in bringing ingenious ways of data gathering. Hence, it is even more important to raise public awareness of new online behavioral advertising techniques, so that consumers can decide for themselves whether they want to be tracked and enjoy all the advantages of these devices or choose to use a limited version and do not have to be concerned about their privacy. Moreover, privacy protection legislation should be updated and adjusted to new OBA practices, to secure that consumer data will not be stolen or misused.

Boerman et al. (2017) suggest that more research concerning users’ responses to personalized advertisements should be conducted. The perception of OBA and its personalization levels differs from user to user. Some consumers might enjoy the benefits of targeted advertising while others may find it very intrusive. Further investigation of this problem could be advantageous for all involved parties. Firstly, it could help advertisers better comprehend people’s feelings around OBA, so that they could improve their services. Secondly, consumers would have less reasons to be afraid of using the internet and would be more encouraged to purchase products online finally it might also facilitate lawmakers to set the borders between admissible and inadmissible OBA practices, so they could advance in consumers’ privacy protection.


To conclude, the influence of OBA on consumers depends on several factors, which are of exogenous or endogenous nature. The actual attitude towards behavioral targeting represents the result of their combination. Despite prevailing negative feelings regarding targeting, online behavioral advertising is for entrepreneurs very attractive tool because it raises ad effectiveness and results in increased revenues.

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Although a lot of OBA research has been conducted throughout the last decade, there arise still many questions that should be answered in order to find a balance between the needs and wants of involved parties. Moreover, constantly evolving technologies generate more and more opportunities of monitoring and data collecting and thus provide a lot of space for further research.


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