ORIGINAL LITERATURE REVIEW
The negligent and liberal exchange of digital privacy and personal data in return for a personalized internet experience may or may not be justified in its benefits for individual web users. The often inadvertent deployment of an individual’s personal details and data points are strategically processed and calculated through various programs at which point they are tactically directed and deployed into advertisements, appearing based on the continuous input of consumer actions and behaviors. The data points democratize marketing by generating content that is specifically retrieved from the sources for whom the advertisements will ultimately reappear by integrating what could often be up to “65 third-party trackers” into the web page, without the consumer’s knowledge. Both the quantity of data that is extracted from a user and the number of organizations doing the extraction from user-generated activity is tremendous with hundreds of thousands of data points appearing in the digital environment each day. In turn, advertisers who use third-party tracking and other target marketing systems and technologies produce some of the highest returns on advertising investment. Advertisers are quick to compete for high-visibility spots on big name search-engines that similarly track user activity. These engines methodically place any given ad based on a combination of consumer interest analytics and pay per click rates. Take for example, Google, whose third quarter advertising revenues were $9.72 billion in the third quarter alone-allotting for 96% of its total profits. Google’s advertising is based in the systematic generation and targeting of ad placement. These search engines and advertisers work together to generate the content on our webpages, sometimes offering a view into the methodology and reasoning for ad placement for reasons of transparency and credibility, as Google does with its available overview of Google Adwords. These engines and advertisers simultaneously profit from steep pay per click (PPC) rates and increased visibility, respectively.
However, the data that users ultimately, and often accidentally, provide inherently shapes the way that search engines like Google strategically place ads. Yet, this data that is the foundation for high-level streamlined search engine advertising is considered to be valued as private information by 94% of web consumers, as based on a study conducted by the University of Pennsylvania. However, of those 94%, only 37% took precaution to protect their digital privacies, and only 19% downloaded software to block web trackers. Often, the reason that the data belonging to those who value privacy is inevitably shared is for lack of reading the fine print. In the terms and conditions of Apps or social sites like Facebook, wherein users freely generate and continuously disperse private details and images, including birthdays, addresses and locations, Facebook notes that this provided information that is so crucial to maintaining not only digital, but also personal security, is transferred into the ownership of Facebook and therefore can be shared and utilized as such. It is in this exact way that advertisements containing products that have been mentioned in personal Facebook conversations, begin to appear in the advertisements on the side of the webpage. The assumption by third-party sources that extract this data and consumer behavior is that the generation of personal, digital user profiles will be both beneficial to the those selling the goods and services and also to those users receiving the goods and services-as the accessibility is greater than ever through targeted advertisements.
However, the failure of target-marketing, despite the ever-presence of its third-party data extraction tactics from social profiles,web searches and online purchases, exists in the incompleteness of the data that is extracted from the user. Target marketing requires a thorough understanding of the target consumer including attributes such as age, gender, class, industry, etc. However, even those classifying characteristics may be too vague to isolate a group target audience. An effective target marketing procedure deployed through market segmentation, or micro-marketing, splits the target audience into distinct groups. In turn, the segmented target audiences are more defined and therefore more easily located and addressed. The process of this segmentation requires the marketers to divide their audience into extremely definable and similar enough demographic groups, consumer behaviors, lifestyles, geographic locations etc., that they are able to understand the need of those consumers. Because the internet is so vast in its quantity of users and information, technologies such as automated marketing programs and cookies, among others, are utilized to track the data input and map the millions of users’ activities in a way that humans simply cannot. Though the technology has the capacity to pull various and randomized information about a consumer’s profile from that user’s digital history, inevitably the entire ‘package’ of the consumer is impossible to see based on that selected set of data input and pulled information. As such, it is not rare that the target segmentations are incongruent and the individuals targeted share in common far less than they should for effective targeted micro-marketing. Ultimately, many data points that are pulled for individualized marketing are focused on keywords or phrases to generate ads that perpetually reappear, and often feature goods or services in the mixed-media advertisements that are misaimed at a consumer due to their accidental inclusion in any given segmentation. On the other hand, a consumer can be redirected to a product that they have already searched, known or owned because the data that is pulled directs the ad to land on the page of a currently aware consumer. Therefore, instead of being brought to an item from which one potentially could benefit, one is brought to an item of which one is often already savvy. In this way, many times, advertisements are brought to the attention of current customers and not to prospective ones, and thus, mutually, the advertiser and the user face the flaws of data point based target-marketing.
Furthermore, the credibilities of web-based target advertisements are far lower than print advertisements as the digital ads, which are tailored to an individual, are perceived to be deceptive in nature. The disconnect and lack of awareness that one’s personal data has been obtained to lure that user into purchasing goods and services creates a boomerang effect in that the information that the third-party sources illicit to advertise, becomes the reason for the mistrust of the ads. This lack of trust is also cultivated through the incapacity for sites to be transparent with their viewers and users about the third-parties who are actively withdrawing personal data input on the site. Furthermore, this lack of certainty about the validity of targeted ads becomes more disconcerting when considering that a high-quality organization or marketing firm pulls data from sites using the same or similar methodology, systems, as well as access capabilities as a low-quality organization or marketing firm. In this way, low-quality firms are able to mimic more credible-firms as they have access to data sets that share much resemblance. As such, low-quality products or firms have as much greater capacity to reach out to consumers on the digital target marketing platform as compared to their abilities to catch consumer attention in “lower-noise” marketing environments. In this way, the less credible firms are far more prevalent in digital target marketing, increasing the likelihood that a user will click on a low-quality, non-beneficial advertisement, and in turn, that they will develop a bias against target marketing on the web for its deceptive nature. In this way, the replication of credible advertisements by non-credible ones causes the success of the high-quality target ads to decline.
The credibility of targeted advertisements are ever-more lessened with what has been termed “banner blindness,” or the brain’s inability to process the ‘noise’ of these advertisements due to the ever-present ‘loudness,’ particularly existing in non-credible targeted ads. This creates a cycle of ads attempting to ‘shout’ over one another, in turn decreasing the likelihood that they will receive clicks for their spam-like nature and appearance. Similarly, the imposition of “growth hacking,” or inconspicuously weaving marketing and sales tactics into the infrastructure of a web page based on social metrics, data and site analytics is a low-cost method that uses the information acquired by private data points to strategically place goods or services in a loop of referral, without purchasing advertisements. “Growth hacking” aggressively targets current or prospect users by enticing those current users or consumers to spread awareness of their specific product in return for continued use of their product or endowment of perks. The imposition of methods like “growth hacking,” which require little to no financial investment on the seller’s side, allow for the possibility to have asymmetry between the appearance of the ad, and the actual quality of the good or service being cycled and sold.
This false signalling falls in opposition to the principal of advertising, which is that a high-quality product can afford to advertise, for their good is worth enough that the costs of promoting it are recovered in the unfaltering excellence of the good or service itself. A good in traditional advertising catches the eye for upholding its reputation with the certitude and accurate representation in its advertisements. With target marketing, this is not so. Low-quality goods may have the same procedures and standards of target advertising as do those of high-quality goods, thus driving down the trust in brands to which one may have formerly had brand loyalty. “Perceptions of brand quality [are] in turn the most critical predictor of a participant’s inclination to purchase a brand.” When products of either low or high credibility are constantly and unpredictably placed together in the tailored ads on web pages, both become undoubtedly more mistrusted due to the inability to tell them apart and the lack of transparency in how the necessary data was acquired for the ad to appear on the page.
Therefore, the web pages that are not conspicuously tailored or customized from data that has been pulled from an individual without their knowledge or true consent, are far more likely to contain advertisements that will be viewed as being credible. As such, it is predicted that the more tracking protection and third-party blocking software one has, the more purchases the individual will make. This seems to be contrary to the expectation of internet users who, assuming that they are aware of the target-marketing, may not prevent third-party data extraction for their perception that the web personalization is beneficial. However, it may be that the consumer is actually less likely to purchase or benefit from a tailored web experience for the amount of mistrust in the incongruent, repetitive or asymmetrical advertisements. It seems paradoxical that sharing privacy and personal data with third-party sources actually inhibits an advertisers ability to sell to a consumer for their lack of transparency, their overbearing tactics to seek attention and their incapacity to place the singular data points that they have pulled into the context of the true consumer needs.
However, the data that users ultimately, and often accidentally, provide inherently shapes the way that search engines like Google strategically place ads. Yet, this data that is the foundation for high-level streamlined search engine advertising is considered to be valued as private information by 94% of web consumers, as based on a study conducted by the University of Pennsylvania. However, of those 94%, only 37% took precaution to protect their digital privacies, and only 19% downloaded software to block web trackers. Often, the reason that the data belonging to those who value privacy is inevitably shared is for lack of reading the fine print. In the terms and conditions of Apps or social sites like Facebook, wherein users freely generate and continuously disperse private details and images, including birthdays, addresses and locations, Facebook notes that this provided information that is so crucial to maintaining not only digital, but also personal security, is transferred into the ownership of Facebook and therefore can be shared and utilized as such. It is in this exact way that advertisements containing products that have been mentioned in personal Facebook conversations, begin to appear in the advertisements on the side of the webpage. The assumption by third-party sources that extract this data and consumer behavior is that the generation of personal, digital user profiles will be both beneficial to the those selling the goods and services and also to those users receiving the goods and services-as the accessibility is greater than ever through targeted advertisements.
However, the failure of target-marketing, despite the ever-presence of its third-party data extraction tactics from social profiles,web searches and online purchases, exists in the incompleteness of the data that is extracted from the user. Target marketing requires a thorough understanding of the target consumer including attributes such as age, gender, class, industry, etc. However, even those classifying characteristics may be too vague to isolate a group target audience. An effective target marketing procedure deployed through market segmentation, or micro-marketing, splits the target audience into distinct groups. In turn, the segmented target audiences are more defined and therefore more easily located and addressed. The process of this segmentation requires the marketers to divide their audience into extremely definable and similar enough demographic groups, consumer behaviors, lifestyles, geographic locations etc., that they are able to understand the need of those consumers. Because the internet is so vast in its quantity of users and information, technologies such as automated marketing programs and cookies, among others, are utilized to track the data input and map the millions of users’ activities in a way that humans simply cannot. Though the technology has the capacity to pull various and randomized information about a consumer’s profile from that user’s digital history, inevitably the entire ‘package’ of the consumer is impossible to see based on that selected set of data input and pulled information. As such, it is not rare that the target segmentations are incongruent and the individuals targeted share in common far less than they should for effective targeted micro-marketing. Ultimately, many data points that are pulled for individualized marketing are focused on keywords or phrases to generate ads that perpetually reappear, and often feature goods or services in the mixed-media advertisements that are misaimed at a consumer due to their accidental inclusion in any given segmentation. On the other hand, a consumer can be redirected to a product that they have already searched, known or owned because the data that is pulled directs the ad to land on the page of a currently aware consumer. Therefore, instead of being brought to an item from which one potentially could benefit, one is brought to an item of which one is often already savvy. In this way, many times, advertisements are brought to the attention of current customers and not to prospective ones, and thus, mutually, the advertiser and the user face the flaws of data point based target-marketing.
Furthermore, the credibilities of web-based target advertisements are far lower than print advertisements as the digital ads, which are tailored to an individual, are perceived to be deceptive in nature. The disconnect and lack of awareness that one’s personal data has been obtained to lure that user into purchasing goods and services creates a boomerang effect in that the information that the third-party sources illicit to advertise, becomes the reason for the mistrust of the ads. This lack of trust is also cultivated through the incapacity for sites to be transparent with their viewers and users about the third-parties who are actively withdrawing personal data input on the site. Furthermore, this lack of certainty about the validity of targeted ads becomes more disconcerting when considering that a high-quality organization or marketing firm pulls data from sites using the same or similar methodology, systems, as well as access capabilities as a low-quality organization or marketing firm. In this way, low-quality firms are able to mimic more credible-firms as they have access to data sets that share much resemblance. As such, low-quality products or firms have as much greater capacity to reach out to consumers on the digital target marketing platform as compared to their abilities to catch consumer attention in “lower-noise” marketing environments. In this way, the less credible firms are far more prevalent in digital target marketing, increasing the likelihood that a user will click on a low-quality, non-beneficial advertisement, and in turn, that they will develop a bias against target marketing on the web for its deceptive nature. In this way, the replication of credible advertisements by non-credible ones causes the success of the high-quality target ads to decline.
The credibility of targeted advertisements are ever-more lessened with what has been termed “banner blindness,” or the brain’s inability to process the ‘noise’ of these advertisements due to the ever-present ‘loudness,’ particularly existing in non-credible targeted ads. This creates a cycle of ads attempting to ‘shout’ over one another, in turn decreasing the likelihood that they will receive clicks for their spam-like nature and appearance. Similarly, the imposition of “growth hacking,” or inconspicuously weaving marketing and sales tactics into the infrastructure of a web page based on social metrics, data and site analytics is a low-cost method that uses the information acquired by private data points to strategically place goods or services in a loop of referral, without purchasing advertisements. “Growth hacking” aggressively targets current or prospect users by enticing those current users or consumers to spread awareness of their specific product in return for continued use of their product or endowment of perks. The imposition of methods like “growth hacking,” which require little to no financial investment on the seller’s side, allow for the possibility to have asymmetry between the appearance of the ad, and the actual quality of the good or service being cycled and sold.
This false signalling falls in opposition to the principal of advertising, which is that a high-quality product can afford to advertise, for their good is worth enough that the costs of promoting it are recovered in the unfaltering excellence of the good or service itself. A good in traditional advertising catches the eye for upholding its reputation with the certitude and accurate representation in its advertisements. With target marketing, this is not so. Low-quality goods may have the same procedures and standards of target advertising as do those of high-quality goods, thus driving down the trust in brands to which one may have formerly had brand loyalty. “Perceptions of brand quality [are] in turn the most critical predictor of a participant’s inclination to purchase a brand.” When products of either low or high credibility are constantly and unpredictably placed together in the tailored ads on web pages, both become undoubtedly more mistrusted due to the inability to tell them apart and the lack of transparency in how the necessary data was acquired for the ad to appear on the page.
Therefore, the web pages that are not conspicuously tailored or customized from data that has been pulled from an individual without their knowledge or true consent, are far more likely to contain advertisements that will be viewed as being credible. As such, it is predicted that the more tracking protection and third-party blocking software one has, the more purchases the individual will make. This seems to be contrary to the expectation of internet users who, assuming that they are aware of the target-marketing, may not prevent third-party data extraction for their perception that the web personalization is beneficial. However, it may be that the consumer is actually less likely to purchase or benefit from a tailored web experience for the amount of mistrust in the incongruent, repetitive or asymmetrical advertisements. It seems paradoxical that sharing privacy and personal data with third-party sources actually inhibits an advertisers ability to sell to a consumer for their lack of transparency, their overbearing tactics to seek attention and their incapacity to place the singular data points that they have pulled into the context of the true consumer needs.