Consumer Behavior Intervention Project

Consumer Behavior Intervention Project

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Consumer Behavior Intervention Project

Executive Summary

The marketing effectiveness of online ads that are pushed through social media platforms was being challenged by the paring of these ads with toxic and controversial content. Some large brands like Unilever, AT&T and Verizon, who has large advertising budgets were threatening to withdraw from advertising over social media platforms like YouTube because of the threats on their bran reputation because of the association with such content and the ideologies therein. In turn, social media companies had reactively responded by promising to delete such content from their web pages alongside offering markets, sellers and users to control the placing and viewership of online ads. In order to determine the acceptability of these measures alongside a raft of other measures such as increased regulatory control to supplement the self regulation mechanisms in the marketing and social media industry, a study employing a mixed methods approach was suggested. Using questionnaires, in-depth interviews and focus groups, the perceptions of the regulatory and control measures recommended would be determine and correlated to the demographics of the participants who would be drawn from marketers, users and social media companies.    

Description of the Problem/Opportunity and Background

Marketing practices have been irreversibly transformed by the disruptive digital technologies and especially social media platforms such as YouTube, Facebook and Twitter among others (Voramontri & Klieb, 2019). Business organizations are increasingly adopting social media marketing as part of their marketing strategies because of the benefits in cost-effectiveness, expansiveness of reach of targeted audiences, flexibility of application due to a wide range of options and formats that the social media platforms present (Tanner & Raymond, 2013). In addition, digital advertising targets the millennials (aged between 23 and 36 years) because they are digital natives whose proportion in the global population as consumers in large and growing. For instance, in the United States, millennials account for 73 million people while baby boomers have declined to 72 million (Fry, 2018). Their purchasing behavior is attractive to social media marketers because they are inseparable from their smartphones and social media platforms, they prefer spending their money over the internet and quickly, they are attracted to online bargains such as discounts, sales and coupons, and they exhibit relative and limited brand loyalty. As such, have a high preference for personalized engagement, immediate gratification and enjoyable buying process (Moreno, et al., 2017; Pate & Adams, 2013). However, their curiosity, tolerance for diversity, high need to autonomy and individuality and expenditure of extended periods online alongside a yearning to be understood makes them vulnerable to diverse influences from online content (Kurian, 2017). As such, marketers and social media companies have realized that they can capture the attention of millennials and other online enthusiasts by partnering their ads with content, with little concern for the alignment between the messages in the online content and the advertisement. In addition, they hope they can influence the purchasing decision of a consumer by influencing the information search stage of the decision making process of the consumer (Boundless marketing, 2017).          

Although social media marketing is able to gather customer information related to their purchasing behavior and use it to facilitate the making of purchasing decisions among consumers, and can even be used to change the buying behavior of customers, it has recently been plagued by negative outcomes. Specifically, online advertisements that have been presented alongside and associated with online content that is related to aggression, hate speech, fake news, discriminatory ideologies and other controversial content, have been eroding the reputation of brands and their products, and therefore yielding negative business outcomes. Brogunier (2019) observed that online marketing industry had evolved into commercialized and toxic environment due to its influencer marketing approach. Indeed, large business organizations and brands such as Verizon and AT & T have removed their advertisements from YouTube with many others such as Unilever, threatening to follow suit because they are concerned about the association of their marketing messages with content they consider to be toxic (Lomas, 2018; Shu, 2017). In fact, companies, marketers and consumers have raised concerns about such association because of the negative marketing outcomes they present and social media companies have responded with adjustments in platform features and policy reforms in a bid to secure and preserve their ad-generated revenues and promising marketing dominance. Unfortunately, companies, marketers and consumers have little or no control over the placement of ads on web pages and the social media companies hold most of the control. 

Social media companies acknowledge that social media influencers and content creators are capable of influencing the buying behavior of consumers and often leverage on their ability to increase traffic to the social media platforms, which is a valuable source of their revenues. The symbiosis between influencers, marketers and social media companies has seen rise and proliferation of social media marketing with the three players deriving mutual benefit from the monetization of the social media marketing approaches and techniques. Therefore, to ensure that these players continue to derive the monetary benefits, social media companies have instituted measures such as enhancing the features of the social media platforms and reforming user policies as self-regulatory mechanisms. Notably, Facebook and Twitter has added ad transparency tools onto its platform to enable users including marketers, businesses and consumers, to see the exact advertisements that are running in a Facebook page or a Twitter account (Gotter, 2018). In addition, social media platforms such as Facebook, Twitter and YouTube have come up with user policy reforms that aim at stemming the misuse of their social media platforms by content creators and users to influence the buying behavior of consumers. For instance, Facebook vets ads that address ‘national issues of public importance’ and flags them for political content, making them eligible for disapproval is found to be inappropriate. In this regard, Facebook requires that advertises undergo an authorization process to approve their inclusion of politically-related content. Likewise, Twitter allows the viewing of metrics to ads containing political content alongside intending to archive such ads indefinitely (Roer, 2018). In the same vein, YouTube has implemented a user policy aimed at removing videos and video channels that contain toxic content such as fake news, hateful ideologies, violent practices, discriminatory ideologies, extremist ideologies, and hate speech. In addition, the policy targets the limiting of the proliferation borderline content without banning it due to its subjectivity (Sands, 2019). Specifically, the new policy by YouTube bans offensive and controversial videos that advance ideologies of exclusion, segregation and discrimination of groups of people, and glorify the superiority or demean one group of people over another. This adds up to the previous policy of the prohibition of videos that promote hatred and violence based on discrimination of protected categories of people (Dwoskin, 2019).              

Social media companies have been accused of not doing enough to protect marketers and consumers from toxic content alongside acting in a reactionary manner only when there is public uproar rather than a proactive manner (Dwoskin, 2019). In addition, they continue to use algorithms in their automated advertising systems that pair ads from major brands with offensive videos with the expectation of influencing consumer behavior (Roose & Conger, 2019). Therefore, there are concerns that social media marketing may be losing its utility as a marketing strategy that is able to influence the consumer behavior in a manner that drives up sales and increases revenues for the business enterprise and the marketer. To this end, this study seeks to understand how consumer behavior is influenced by social media platforms in the environment of increasing toxic online content and how social media marketing can continue to positively influence consumer buying behavior without the adverse social implications associated with toxic content.

Conceptual/Theory Framework

Consumer buying behavior comprises of the decision making processes and actions undertaken by people that are involved in the purchasing and use of products and services available in the marketplace. Consumer buying behavior is part of consumer behavior which is an aggregation of the reasons why people shop for products or services, purchase them, use them and dispose of them including the reasons that make customer to be loyal to certain products or products and brands. As such, consumer buying behavior is an extensive concept comprising mainly of the factors that influence the buying behavior and the decision-making process involved in the making of purchases.

The concept of consumer buying behavior has been widely researched and various theoretical frameworks and models have been developed. The theories that best underpin the consumer behavior in the digital era in the 21st century include the theory of reasoned action (TRA), the theory of planned behavior (TPB), the motivation-need theory and the impulse buying theory, which are able to explain online purchasing behavior.

The theory of reasoned action

The theory of reasoned action (TRA) was advanced by in 1980 by Icek Ajzen and Martin Fishbein and highlights the pertinence of attitudes in the process of making decisions in a bid to explain the discrepancy between behavior and attitude (Khurana & Kaur, 2017). The theory posits that the behavior of a consumer is directed by the intentions of receiving or creating a particularly desired outcome (Javadi et al., 2012). As such, consumers act in a rational manner that advances their best interests in the best way possible. In this regard, marketer should associate a purchase with a specific positive result that serves the interest of the consumer and therefore should facilitate the movement of the consumer through the sales pipeline. As such, marketers should shorten the interval between the initial intention of the consumer and the completion of the purchasing process to limit the time spent by consumers in questioning the purchase which may result in a change of mind.

Theory of planned behavior

The theory of planned behavior (TPB) is an extension of the theory of reasoned action that emphasizes on the intentionality of the individual when acting out certain behavior without considering the beliefs held by the individual regarding the behavior. In this regard, the theory posits that the consumer behavior is influenced by consumer intentions and the behavioral control perceived by the consumer. The concepts that underpin this theory and make it applicable to online purchasing behavior include attitude, subjective norm and perceived behavioral control (Javadi et al., 2012). In this regard, the positive attitude towards digital technologies and online purchases held by digital natives and tech savvy people enhances their engagement in online purchases (Pelling & White, 2009). However, the consumer attitude is closely related to trust for the marketer and seller, and therefore the expectation of integrity, competence and benevolence from these online actors. In addition, the subjective norm of a consumer is related to the influence others have on the behavior of the consumer with normative beliefs of consumers predisposing and motivating them to behave in a manner that is based on the views of other people (Javadi et al., 2012). From this precept, online consumer behavior is influenced greatly by reviews from peers and communities of interest, influencers that are held with high regard by the consumer and the need for belongingness by the consumer.       

The motivation-need theory

The motivation-need theory was advanced by Abraham Maslow in a bit to explain how people acted to fulfill their needs based on the importance of those needs to the individual. The theory posits that people fulfilled their needs progressively starting with the fulfillment of basic needs before progressing to the fulfillment of higher level needs (Boundless marketing, 2017). In this regards, the needs of people are hierarchical and progress from psychological needs that are considered vital for the human survival, through safety needs, social needs, esteem need and finally self-actualization needs (Boundless marketing, 2017; Tanner & Raymond, 2013). In the online environment, the motivation-need theory anchors the practice of tailoring the marketing strategies and messages in a manner that addresses the needs of the consumer and evokes a sense of urgency for the consumer to satisfy their needs through their purchases. In addition, marketers and sellers create artificial needs that resonate with the consumer and motivate purchasing behavior for need gratification.   

The impulse buying theory

The impulse buying theory was advanced by Hawkins Stern as a way of explaining the irrational, unplanned hedonically complex and compelling purchasing behavior exhibited by consumers from time to time (Chan, Cheung & Lee, 2017). The theory posits that consumers make purchases because they experience a sudden urge to buy rather than only because they need the products or services. According to the theory, instant purchases are inspire by external stimuli largely and do not conform to the traditional decision-making process. According to the theorist, impulse buying can be categorized as pure impulse purchasing, reminded impulse purchases, suggested impulses purchases and planned impulse purchases. In the online environment, marketer and sellers leverage in the impulsivity of consumers by sending them numerous cues such as pop-ads that accompany content in webpages. Notably, the regular display of discounted products and e-coupons as aimed at preying on the impulsive buying behavior of consumers. Indeed, the practice of shock advertising and subliminal advertising target the impulsivity of consumers by exposing them to continuous marketing stimuli that is embedded in other media (Tanner & Raymond, 2013).

Many studies have addressed the complexity of online consumer behavior and attempted to explain it using these theories.

Khurana and Kaur (2017) used an extensive review of the literature to trace the evolution variable factors underpinning consumer behavior due to the emergence of the online consumer and the subsequent emergence of online consumer behavior models. In their study, Khurana, S. & Kaur, B. (2017) used TRA and TPB theoretical models alongside the technology acceptance model (TAM) to explain the purchasing behavior exhibited by consumers in the online environment. Veronika, S. (2013) was able to demonstrate that although different age groups had different needs that they needed to satisfy as stipulated in the motivation-need theory, the motives that inspired online shopping behavior were similar across different age groups although they were unique for the online environment. However, Moreno et al. (2017) demonstrated that millennials responded to online visual cues such as graphics, coupons, discount offers as external stimuli that influenced their buying behavior. In addition, millennials tended to spend their income quickly, which explained their impulsive purchasing behavior that can be explained using the impulse buying theory (Moreno et al., 2017). In addition, Chan, Cheung and Lee (2017) identified and classified the factors influencing online impulse buying using the stimulus-organism-response framework, using literature analysis that contextualized the impulse buying theory in the online environment.   

Recommendations

To eliminate the practice of coupling online advertisements with toxic online content and influencers, particularly that which is undertaken in social media platforms, the following recommendations are made.

Firstly, marketers and sellers should publicly dissociate themselves with the toxic online content, the ideologies contained therein and the influencers who propagate the toxic content. This would push the social media companies that host the toxic content and pair it with advertisements to become more accountable to the marketers, advertisers and sellers, the consumers and the public. Indeed, Abdollahbeigi and Salehi (2019) observed that social media marketer needed to be honest with their customers if they expected to endear loyalty and influence the purchasing behavior of consumers.

Secondly, online hosts of content such as internet providers and social media companies should withdraw the toxic online content that is detrimental to good public order. In this regard, they should develop algorithms are able to detect toxic content and prevents it to be uploaded to the internet and especially on social media platforms. Indeed, toxic content influenced the attitudes of the online users and this can be used to make the content acceptable if it is associated with major and popular brands, and therefore this recommendation can prevent the development of undesirable attitudes among online consumers (Javadi et al., 2012).

Thirdly, marketers and sellers should have more control over where their advertisements are placed and which content their advertisement should be paired with so that they can continue to advertise online without injuring their brand reputations. In the same vein, users should also have more control of the adverts they see and where they appear so that they can stem the association of adverts with toxic content based on their browsing behavior and interests. This is premised on the pertinent of the information search step in the 5-step process of consumer buying behavior, which may explain the deliberate and willful pairing of online ads and content to take advantage of the information seeking behavior of online buyers (Ertemel & Ammoura, 2017).   

Fourthly, the self-regulatory mechanisms used by social media companies should be reinforced with law and regulation so that violators can be sanctioned though punishment. This would stem the practice of using personal information and browsing behavior by social media companies to target advertisements to user segments without their consent. In addition, this would stem the selling of personal information to marketers without the express consent of the owners of such information. Fengler (2012) proposed the audience-inclusive model to overcome the failures in self-regulation and increase media accountability so as to overcome the violations of professional standards in journalism in the digital age. In addition, Molina (2019) indicated that self-regulatory measures such as the removal of controversial and toxic content from You-Tube would restore the confidence and trust of marketers and users. In the same vein, Tucker (2014) demonstrated enhanced user control on social networking websites such as privacy settings that allowed the users to opt out of online advertisements and personalization of ads using unique private information improved the likelihood of the users clicking on the ads.

Evaluation

The effectiveness of the proposed recommendations can be evaluated using a study that unearths the perceptions about the feasibility of the recommendations such as increased marketer, seller and user control over the placement and viewing of online advertisements and increased regulation to supplement self-regulatory mechanisms use by the social media and marketing industries.

A mixed methods research approach that combines qualitative and quantitative studies is proposed because of its ability to provide in-depth insight into the perceptions related to the recommendations and the successes that have been achieved by some of the players in the online marketing environment that have implemented some of these recommendations (Rohm, Kaltcheva & R. Milne, 2013).

The target population for the proposed study would be online marketers, sellers and users and social media companies. Random sampling would be used to obtain participants in each segment. The data collection techniques would comprise of a combination of questionnaires, in-depth interviews and focus groups to provide sufficiently detailed data that can be used to decipher perceptions (Kim & Lennon, 2013).  

The results from the study should be measures through the level of acceptance or rejection of the recommendations. In addition, the correlations between the demographic variables such as age and genders with the various measures proposed in the recommendations would help reveals which consumer characteristics are likely to embrace these measures (Rohm, Kaltcheva & R. Milne, 2013).

In conclusion, the limitations of the recommendations include the absence of legislations and regulations that expressly control online ads on social media platforms, the fragmentation of existing legislations and the low user awareness on such regulations. In addition, the non-compliance of various social media companies regarding ethical online marketing alongside the rarity of user-controlled and marketer-controlled ads would limited the understanding of how such controls can be utilized by users and marketers who want to be exposed by as much information as possible. The thin line between privacy and the right to information and free speech would present further limitations in the perceptions of the respondents.        

References  

Abdollahbeigi, B. & Salehi, F. (2019). The impact of social media on purchasing intentions of green products. Asian Journal of Technology and Management Research, 8(2), 9-14. 

Boundless marketing (2017). Lumen Learning. Retrieved 22 July 2019 from https://courses.lumenlearning.com/boundless-marketing/.

Brogunier, T. (2019). 4 reasons why social media has become toxic and what to look for next. Entrepreneur. Retrieved 22 July 2019 from https://www.entrepreneur.com/article/328749.

Chan, T. K., Cheung, C. M., & Lee, Z. W. (2017). The state of online impulse-buying research: A literature analysis. Information & Management54(2), 204-217.

Dwoskin, E. (2019). YouTube will remove more white supremacist and hoax videos, a more aggressive stance on hate speech. The Washington Post. Retrieved 22 July 2019 from https://www.washingtonpost.com/technology/2019/06/05/youtube-will-remove-more-white-supremacist-hoax-videos-greater-hate-speech-effort/?utm_term=.957d63083ac5.

Ertemel, A. V. & Ammoura, A. (2017). The role of social media advertising in consumer buying behavior. International Journal of Commerce and Finance, 2(1), 81-90.

Fengler, S. (2012). From media self-regulation to ‘crowd-criticism’: Media accountability in the digital age. Central European Journal of Communication5(09), 175-189.

Fry, R. (2018). Millennials projected to overtake baby boomers as America’s largest generation. Pew Research Center. Retrieved 22 July 2019 from https://www.pewresearch.org/fact-tank/2018/03/01/millennials-overtake-baby-boomers/.   

Gotter, A. (2018). How to use Facebook and Twitter ad transparency tools. Social Media Examiner. Retrieved 22 July 2019 from https://www.socialmediaexaminer.com/ad-transparency-tools-facebook-twitter/.

Javadi, M. H. M., Dolatabadi, H. R., Nourbakhsh, M., Poursaeedi, A., & Asadollahi, A. R. (2012). An analysis of factors affecting on online shopping behavior of consumers. International Journal of Marketing Studies4(5), 81.

Khurana, S. & Kaur, B. (2017). Online consumer behavior models: A literature review. Biz and Bytes, 8(1), 209-217.

Kim, J., & Lennon, S. J. (2013). Effects of reputation and website quality on online consumers’ emotion, perceived risk and purchase intention: Based on the stimulus-organism-response model. Journal of Research in Interactive Marketing7(1), 33-56.

Kurian, S. (2017). Meet the millennials. KPMG. Retrieved 22 July 2019 from https://home.kpmg/content/dam/kpmg/uk/pdf/2017/04/Meet-the-Millennials-Secured.pdf.

Lomas, N. (2018). Unilever warns social media to clean up ‘toxic’ content. Verizon Media. Retrieved 22 July 2019 from https://techcrunch.com/2018/02/12/unilever-warns-social-media-to-clean-up-toxic-content/.

 Molina, B. (2019). YouTube says it’s removing more hateful videos from platform. USA Today. Retrieved 22 July 2019 from https://www.usatoday.com/story/tech/news/2019/06/05/youtube-remove-more-extreme-hate-videos-its-platform/1357364001/.

Moreno, F. M., Lafuente, J. G., Carreón, F. Á., & Moreno, S. M. (2017). The characterization of the millennials and their buying behavior. International Journal of Marketing Studies9(5), 135-144.

Pate, S. S., & Adams, M. (2013). The influence of social networking sites on buying behaviors of millennials. Atlantic Marketing Journal2(1), 92-109.

Pelling, E. L., & White, K. M. (2009). The theory of planned behavior applied to young people’s use of social networking web sites. CyberPsychology & Behavior12(6), 755-759.

Roer, G. (2018). Ad transparency: What it is and how it affects social media marketing. Groer. Retrieved 22 July 2019 from https://uproer.com/articles/ad-transparency/.

Rohm, A., D. Kaltcheva, V., & R. Milne, G. (2013). A mixed-method approach to examining brand-consumer interactions driven by social media. Journal of Research in Interactive Marketing7(4), 295-311.

Roose, K. & Conger, K. (2019). YouTube to remove thousands of videos pushing extreme views. The New York Times. Retrieved 22 July 2019 from https://www.nytimes.com/2019/06/05/business/youtube-remove-extremist-videos.html.

Sands, M. (2019). YouTube’s ‘borderline content’ is a hate speech quagmire. Forbes. Retrieved 22 July 2019 from https://www.forbes.com/sites/masonsands/2019/06/09/youtubes-borderline-content-is-a-hate-speech-quagmire/#123d37916299

Shu, C. (2017). AT&T and Verizon joining advertising boycott against Google over offensive YouTube videos. Verizon Media. Retrieved 22 July 2019 from https://techcrunch.com/2017/03/23/att-verizon-boycott-google-ads/

Tanner, J. F. & Raymond, M. A. (2013). Principles of marketing, version 2.0. Flat World Knowledge. Retrieved 22 July 2019 from https://saylordotorg.github.io/text_principles-of-marketing-v2.0/

Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research51(5), 546-562.

Veronika, S. (2013). Motivation of online buyer behavior. Journal of competitiveness5(3), 14-30.

Voramontri, D. & Klieb, L. (2019). Impact of social media on consumer behaviour. International Journal of Information and Decision Sciences, 11(3), 1-25.

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