Research of How Online Behavioral Advertising Influences Consumers

Introduction

Rapidly growing population along with digitalization and globalization re-sult in constantly increasing number of internet users. (ITU 2019) Closely relat-ed to this development is the expansion of 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 great oppor-tunity for the growth of online shopping industry. Lockdowns in the countries across the whole world have had considerable influence on the numbers of online purchases. The statistics compiled by the Organisation for Economic Co-operation and Development confirm this assumption showing that the e-commerce retail in the United States and in the United Kingdom rose between the first quarter and the second quarter of 2020 (first lockdown in the UK on the 26th March 2020, in the U.S. on the 19th March 2020 ( from 11.8% to 16.1% respectively from 20.3% to 31.3%. The increasing numbers of online purchases signify higher revenues and at the same time add the importance to this sector. Temporary closures of brick-and-mortar stores due to containment measures have led to de-creases in retail volumes (Eurostat 2020) and have caused slumps in earnings , shifting companies’ focus to transition to the e-commerce, making them invest more capital in online marketing and advertising. (Wertz 2020)

In general, people often get irritated by online advertisements and especially when they are not relevant, they tend to avoid them. (Ham et al. 2017) To increase the efficiency of their marketing strategies, companies choose to employ different methods and one these is the online behavioral advertising (OBA) also called online targeting . This method targets consumers on the basis of collected personal in-formation. However, to be effective, the 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 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 personal information of millions of Facebook users without any consent and used it for polit-ical advertising. This scandal is the 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 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 which aim to find definition for the OBA. Boerman et al. (2017) review scientific literature on this topic and compare definitions from previous papers. According to their findings there are two attributes which they have in common. The first joint feature is the observation of consumers activities on the internet through monitor-ing or tracking and the second, the application of obtained information for individ-ually designed advertisements. Based on this discovery Boerman et al. (2017) de-liver definition, which describes OBA as “the practice of monitoring people’s online behavior and using collected information to show people individually target-ed information.” In other words, companies using online behavioral advertising detect and gather the 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 incomes through advertising. (Facebook 2020) The network’s developers created trackers, which can collect information about user’s off- and on-Facebook browsing activi-ties 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 the graphic design and therefore it may display an advertisement for this type of cours-es on the user’s wall. 

The third-party cookies are the most used way of personal information col-lection. After an agreement between website and 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 consumer’s 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. (Ham et al. 2017) The recent technologies even enable to track the consumers in the real time. The technology came so far that it is possible to “create a request for an online ad as 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, simple cookie is sufficient in others complex profiling techniques need to be applied. (Varnali 2019)

Theoretical background

The opinions on the OBA practices are diverse. Some users enjoy personal-ized services while the others might feel threatened. (Boerman et al. 2017) In the past, this diversity has been investigated several times and since the online behav-ioral advertising is an interdisciplinary subject of research, the range and variety of used explanation theories is rather extensive. In previous studies on responses on the OBA scientists worked with theories from marketing, psychology, and commu-nication, 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 the OBA practices. For instance, when consumers give company the consent to collect and use their personal data a contract between both sides is closed. Within this contract people hope that company will work with their information in responsible way and if these expectations are not abided by advertis-er, 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). (Miyazaki 2008, Boerman et al. 2017) What is more, a negative reactance can be induced through the high degree of personali-zation (psychological reactance theory). Also, when people learn more about OBA practices, feelings of skepticism might arise (persuasion knowledge model). (Boerman et al. 2017) According to the last concept, an advertiser as a persua-sion agent tries to persuade/convince consumer, persuasion target, in covert way. These is later uncovered and drives users into the interaction with advertisement. (Ham et al. 2017) occupies more thoroughly with the persuasion knowledge model and the protection motivation theory.

Framework

To classify results from previous OBA examinations and to obtain clearer overview of this subject, Varnali (2019) develops a framework dividing the online behavioral advertising research into three layers. To be more specific, ac-cording to his findings there exist three perspectives of looking at the online target-ing. Firstly, a macro-level perspective, which concentrates on legal issues connect-ed to the OBA. Secondly, an eco-system level perspective, which occupies with strategies used to the OBA system optimization and 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, pro-filing, and targeting of individuals on the internet. Up to the present, scientists often dedicated their research to the problematics of finding the balance between privacy protection of the internet users and 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, the higher personaliza-tion can be also dangerous because it increases the risk of control loss over the us-ers‘ 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 a web page content, they must accept website’s policies first. 

In the literature, the ethics of OBA is frequently discussed, but due to differ-ent interests of involved parties, it is quite demanding to decide what is moral and what is not. There are several regulations which attempt to manage and restrict un-ethical behavior when it comes to OBA, but there are still some gaps, which enable advertisers to use deceptive methods and to gain customer’s 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 de-rivative while in others it must be given explicitly.

In the past years, several institutions decided to take actions in people’s pri-vacy protection. For example, the European Union issued in 2016 General Data Pro-tection Regulation (GDPR) valid for all its member states. The regulation aims to improve European citizens’ data protection and contains answers to questions re-garding collection, use and storage of this data. (Council of European Union 2015) Also in the U.S. were several initiatives which strived for adoption of data protec-tion laws. One of these is called Do Not Track Act. The purpose of this regulation is the definition of internet users’ rights and advertisers’ obligations concerning the 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) pro-vides several subjects which are discussed regarding the privacy. These are: users’ opting-in and opting-out alternatives, routines with concern to giving permission to be targeted, 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, pub-lishers, and regulators. These guidelines include honest, transparent, and fair ap-proach, 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 winning advertiser is chosen on the basis of the best fit between a user and an offer of 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 impacts of tar-geting on outcomes of advertising and publishing companies along with the impacts on society. The research has demonstrated that 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 the 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 differences in profits can be observed when it comes to plat-forms. According to Gal-Or, Gal-Or, and Penmetsa (2018) this is caused by var-iedness of advertisers’ and users’ population and their distinct preferences regard-ing targeting. The size of income is affected also through the higher consumer con-trol. To be concrete, more control decreases level of targeting differentiation and therefore leads to decrease in advertising fees. In the case of symmetric prices and a small number of competitors, revenues can be enlarged through the targeting based on consumer’s visited locations, but in 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 macro- and eco-system-level. While results of macro-level perspective research propose an increase of cus-tomer control, the examination of eco-system level has brought up the finding that larger control leads to decrease of players’ incomes. This might be one of the ar-guments why the advance in increasing consumer control in the online behavioral targeting is so slow. 

Campaign-level perspective

The campaign-level perspective occupies with the questions 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 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 advertise-ment, monitored user’s online behavior and goals).

Influence of OBA on customers

Exogeneous 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 very important part in terms of OBA effects and has been the subject of several studies in the past. Var-nali (2019) recalls results of numerous studies which investigated this topic. For instance, Goldfarb and Tucker (2011) studied effects of ad content on consumer concerning online behavioral advertising and came to the conclusion that if the suitable ads with regard to content of the webpage are used the buying intention rises. T he same applies for increase of obtrusiveness of an advertisement. How-ever, 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 the 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 con-cerns and reactance. Negative attitude in relation to high personalization level can be explained through the fact that individually tailored advertisements might generate feelings of powerlessness when it comes to information possession, con-trol, and freedom of choice. (Boerman et al. 2017) Furthermore, scientists have re-vealed that the high level of personalization is often perceived as intrusive and this might lead to negative change in intention to buy and do not change even after of-fering discounts. (Varnali 2019) These negative perceptions can be moderated by advertisements which are adequate considering user’s needs. 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 dimen-sions of personalized advertising. These dimensions serve to show the accuracy (personalization depth) and fullness (personalization breath) of user’s interests dis-play 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 the privacy, when they decide to apply narrow breadth along with high depth. The retailers, which are con-sidered as less trustworthy should not employ higher personalization depth, because it can have negative impact on reactance and privacy concerns.

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 attitude towards OBA.

Bleier and Eisenbeiss (2015b) claim that interplay between timing and plac-ing can have an impact on content personalization effectiveness of banner advertis-ing. Established on the results of their research they formulated three findings. Ex-amining the high level of content personalization, the best efficiency is achieved at the time of the visit of e-commerce website and it declines rapidly as the time pass-es. 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 a related content, received more attention that advertisements in the sidebar. Click-through rates, brand consideration and intentions to buy can rise if the ads are corresponding with cognitive styles, 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 greater impact on carry-over rates than static formats. The scientists also revealed that there is an positive impact on the OBA if the ad content includes the information about the prize of the product. Low click-through rate by less diverse campaigns, brands spending more on advertising or companies which sell durable goods can be caused by high degree of frequency and recency of advertisements. It is also important to think about the impact of collection of consumers’ information on the acceptance and effectiveness of online behavioral advertising. Miyazaki (2008) claims that negative perception regarding cookies can be decreased by prior cookie disclo-sure. Consumers’ perception of risks towards OBA can be affected through 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 perception of personalized advertisements. Aguirre et al (2015) revealed that overt data accumulation is perceived more posi-tively and may lead to higher click-through-rates. Moreover, by addition of OBA sign the difference between these information collection methods was reduced and intentions to click on the advertisement became equal. This discovery suggests that 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 men-tion that 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 reasona-ble choices regarding online targeting. (Boerman et al. 2017) More control over the personal data can raise the 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 psycho-logical features of consumers (e.g., age, education, nationality, privacy concerns, openness concerning information sharing), perceptual characteristics, which is based on consumer’s previous experiences, beliefs or needs (e.g., consumer’s atti-tude and perception in regard to brands, OBA), spatial-temporal characteristics, representing the conditions in which the consumers is when advertisement is dis-played (e.g., surfing conditions).

Endogenous variables

These variables, coming directly from consumers are perceptions, gratifica-tions, and behavioral intentions. According to Ham (2017) risks related to online behavioral advertising caused by less informativeness and entertainment can have 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 social exchange theory and acquisition-transaction utility theory. (Boerman et al. 2017) According to the first theory, people participate in social exchanges after consideration 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 dependence between likelihood of intention to buy and comparison of possi-ble 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 infor-mation very quickly and therefore do not have enough time to consider actual ad-vantages and disadvantages of their clicking decisions. () Another theory men-tioned 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 into personal space. (Boerman et al. 2017) A study carried out by Ham (2017) suggests that the context of advertisement plays also nonnegligible part by the evaluation of potential risks and benefits of OBA. People are more open to risk undesirable personal data gathering on Face-book rather than by OBA, because they feel that being on Facebook brings more advantages than disadvantages. 

Dehling et al. (2019) created model, which depicts relations between OBA awareness, knowledge, attitude, acceptance, and dissonance (Fig. 3). According to this model awareness and knowledge in regard to OBA is formed by ongoing adver-tisement confrontation. If the degree of awareness ascends, it also means that amount of knowledge rises. On the other hand, higher degree of knowledge does not mean more awareness. Depending on the levels of these two factors changes also the consumer’s attitude towards OBA. As stated by Estrada-Jimenez et al (2017) there exist four types of these attitudes (negative, positive, indifferent, ambivalent). The type of the attitude depends on the amount of benefits and concerns perceived by consumers. For example, high level of perceived benefits and low level of con-cerns 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 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 ex-tended parallel processing model can be also used to comprehend consumers’ nega-tive 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 attitudes of consumers do not change con-tinuously. Consumers act rather passively. In the case of need they evaluate the sit-uation they are currently in and decide if they are willing to accept it. All in all, majority of people do not feel a need to care about the targeted advertising. By the confrontation with this kind of advertisements consumers, who are more aware of OBA and are also better informed, feel more secure. In 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 influ-ence on their decision making. The more concerned users make more efforts to protect their privacy. 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 prac-tices, but should also possess the computer skills on 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. Authors of this paper also confirmed that consumers wish to have more information and control regarding OBA . Further, they wish more pertinence and diversity of advertised content. Excessive repeti-tions and irrelevance of ad content might lead to annoyance and negative change of attitude. Clear explanation of advertisement tailoring methods could be reasonable approach to mitigate customers’ concerns. There is also expressed a request for creation of new ways of consumers’ informing and tracking. Transparency of tracking methods could bring more trust between advertisers and consumers, be-cause 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, the transparency appears to be the right way of handling the privacy concerns, but it is still very problematic because of the big amount of the information, which should consumer study to understand what website’s policies are. (Varnali 2019) Moreover, through the unceasing technological advance it is even more difficult to get oriented in possibilities of opting out . To lessen priva-cy 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 experienc-es towards online targeting might develop into the feelings of incredulity and over a long period can have adverse impact on the advertising in general. 

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 manner of and reason for their collection. (Boerman et al. 2017) Although the scientists claim that these state-ments should lessen the informational imbalance between users and advertisers, this effort often fails, because in most cases, consumers skip reading of these texts. (McDonald and Cranor 2008) Used formulations are often very long, complicat-ed, and hard to understand. Consumers often tend to accept website’s privacy and cookies policies, because they realize that they do not have other option if they want website’s content to be displayed. After accepting these policies, they com-prehend that their personal information is being used when the 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 cor-roborates that this approach is not completely ideal and often fails to fulfil its pur-pose, because of different interests of involved parties. There exists also other 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 Adver-tising Alliance created a unifying icon composed of a blue triangle with i letter. The results of scientific research have showed 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. Van Noort et al. (2013) also suggest that additional sentence with the in-formation stating that the advertisement is established on consumers online behav-ior could bring more comprehension around OBA. Several studies imply that the internet users’ understanding of OBA is quite poor. Most users do not comprehend how the data collection works and how it is shared and distributed to the third parties. Generally, people perceive the OBA practices ra-ther in negative way. The individually tailored ads are considered to be invasive and symbolize the violation of personal space. Phelan et al. (2016) explain these nega-tive perceptions on social presence theory. Relating to the online behavioral adver-tising, it means that personal information gathering could induce similar feelings of being watched over shoulder. (Boerman et al. 2017) Users, who realize that they are actually being tracked tend to adjust their online behavior to the situation. (McDon-ald and Cranor 2010) Turrow et al. (2009) claim, that users’ age is another fac-tor, which influences how behavioral targeting is perceived. After observation of younger and older users, they concluded that younger one’s are more willing to ac-cept the OBA although they also do not wish to be tracked.

The extent to which are advertisements personalized has an impact on 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, the advertisements based on the user’s background generate less clicks than those which are based on the user’s interests. (Tucker 2014) In addition, they also gener-ate more clicks in comparison to ads which are not personalized or on the contrary have high personalization level and are formed on basic personal data. (Aguirre et al. 2015) Moreover, advertisements displaying shopping cart content from previous website’s visit have more positive influence on click-through rates than lower per-sonalized ads which display only recently viewed products. As an example of online behavioral advertising effects on buying decisions a study conducted by Lambrecht and Tucker (2013) can be referred to. Outcomes of their research indicate that purchase intention is determined by type of advertisement in combination with the phase of the buying decision. Us-ers with narrow range of preferences in 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 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 towards them, and they are also considered to be easier to remem-ber. (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. (Kirmani and Campbell 2004)

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 towards 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 advertis-ing, however, more examination needs to be carried out, to be able to establish solid theoretical foundation. (Boerman et al. 2017)

Technological advance unlocks the door to the 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 technol-ogies which enable to connect to internet or to control other devices through the smartphones (e.g., smart television, smart watch, smart speakers). Development of these technologies means a big opportunity for the world of marketing and advertis-ing, because through the use of these devices new possibilities of information col-lection 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 use of multiple de-vices connected to the internet, collected information can be used for advertising purposes not only on the television, but also on 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 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 technologies. The above stated example illustrates that this kind of amenities 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 limited version and do not have to be concerned about their privacy. Moreover, privacy protection legislations should be updated and adjusted to new OBA practices, to secure that consumer’s data will not be sto-len or misused. 

Boerman et al. (2017) suggest that more research concerning users’ respons-es 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 und would be more encouraged to purchase products online and finally it might also facilitate lawmakers to set the borders between ad-missible and inadmissible OBA practices, so they could advance in consumers’ pri-vacy protection.

Conclusion

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

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

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