Big data, big dilemmas: Are we “slaves” of personalized marketing?

Data is the fuel of our Information age and can be used to predict unforeseen things about our lives. This raise concerns not only about the ethics of data but also the violation of privacy.

From the real world to the internet and digital media, information is everywhere around us. Over history society learned to adapt to new technologies and now can almost claim it can not live without it. Along with technology also the digital environment evolved and now scholars, researchers, business analysts try to have a claim on data generated collectively by the users of the digital world (Boyd & Crawford, 2012). 

Brands and organizations use those data for their own benefit in order to create engagement with the consumers, track their purchase habits and construct a profile on them depending on their age, location, gender (Steinberg, E. (2020). Although data helps the relationship between businesses and consumers for a more in – depth personalization and satisfying experience (Wealthengine, 2018), we need to ask ourselves how ethical is such practice? We indeed agree to voluntarily give our personal information in order to acquire access to search engines and visit sites, but where is the line drαwn in the data usage?

Dana Boyd and Kate Crawford (2012) bring the issue to the fore and argue that until now little is known about the subsequent effects of big data usage and most users do not realise that their data, they so freely provide, can and will be used elsewhere for any purpose. Because what they provide is so useful that it is almost impossible to ask from organisations not to reclaim it. When Orwell wrote his well-known novel 1984 it seemed dystopian but how much truth holds now in the age of information?

Amazon’s pioneering personalized marketing and rare connection with its consumers

Let’s use the example of Amazon and personalized marketing to discuss the points above. Amazon is one of the pioneers in that field and leads the way in individual content personalization (Loverus, 2018). The company started succeeding in 2010 with the emergence of its widget “Customers who bought” (Khandelwal, 2021)  which was used to recommend new products to users and well, it was a game changer.

Since then, the sales of the company have only skyrocketed with 35% happening because of the personalised recommendations. Even the customers love Amazon’s features: 44% of the consumers will buy what Amazon recommends under the item they purchased. It is safe to say that Amazon has mastered the art of creating a connection with the customers and delivering a personalized experience with relevant items on the ecommerce site.

How does the giant company archive that? Amazon is using artificial intelligence in everything it does (Khandelwal, 2021). With Al the company browses the customers data and their purchase history which results in improved recommendation algorithms (Srihari, 2015). Al helps extremely to understand the consumers habits and behaviors and tailor their site experience according to their needs.

Netflix is also another company that has invested a lot in Al to power recommendation engines in order to grab the viewer’s attention and create the desire to want to come back for more. The sophisticated recommendation engine Netflix uses enables depicting what viewers like and dislike and according to statistics (Khandelwal, 2021) in 2014 the giant streaming platform used 76,897 different ways to regulate what movies users want to watch and personalize their experience.

The ethical dilemmas with personalized marketing

So predictive analytics is nothing new, but is a crucial strategy. Organizations always wanted to find ways to attract new consumers and retain their lifetime value (Artun & Levin, 2015) by using the data customers generate by using the services offered. Such practices as Amazons only accelerate the normalization of surveillance of the consumers (West,2019) and the fact they constantly want to derive even more information from them so they design services that can be even more competitive in the digital economy. But until when? 

In pursuit for personalization, individual freedoms and consent are affected. Companies do acknowledge the needs of the customers but their values fade in the process of data collection. Many are not aware that data can be gathered and stored for future use. Yes, not all data is sensitive, for example the ones used for weather broadcasts (Kitchin, 2014) but what about those that highly concern us? Questions should be raised about the different forms of “dataveillance” (Kitchin, 2014, p.18) and the data analysis used to divide individuals to different groups and create personalized services depending on their characteristics (Graham 2005).

A big percentage of consumers seem to agree that personalized ads are not ethical (Koetsier, 2019). Amazon uses Al to evaluate the information about its consumers and curate their experience with the company, but who is going to protect the data accumulated? As stated by Nissenbaum (1998) the collection of personal data and information on individuals constitutes a violation of their privacy. People might be inclined to trade a bit of data for personalized web experience, but on the other hand they might not appreciate brands following them everywhere on the web and augment the feeling of surveillance (van Doorn & 21 Hoekstra, 2013).

Conclusion

In today’s digitized era, systems, organizations and people generate more data than we can absorb (Bavati, 2020). Data is our frenemy and the basis of our world. There’s a constant flow of information that we can only hope it’s used in a moral way. We, humans, sacrifice our privacy and give voluntary information about our identity, age, gender and allow platforms to use it and indicate to us where we can go, what we can do, what we should buy and what we need.

Platforms seem to know us better than we know ourselves. Well, with all that data they have on us should we be surprised? Society relies on such practices, but what should our ethical boundaries be? Responsibility is vital with data, but also requires diligent thinking (Boyd & Crawford, 2012). Although, General Data Protection Regulation (DPA)  exists to ensure the protection of personal data, a more strict framework needs to be regulated to corroborate our data privacy. Because in the end, as Crawford (2014) states, “how much trust should we have in the custodianship of data?”

References

Boyd, D. and Crawford, K. 2012. “Critical Questions for Big Data”, Information, Communication & Society, 662-679. https://doi.org/10.1080/1369118X.2012.678878  

Bavati, Ilai. “Ethical Personalization: Weighing Benefits and Risks”. Keenethics. March 23, 2021. Accessed on 2/10/2021 < https://keenethics.com/blog/ethical-user-personalization > 

Crawford, Kate & Gray, Mary & Miltner, Kate. (2014). Big Data| Critiquing Big Data: Politics, Ethics, Epistemology | Special Section Introduction. International Journal of Communication. 8. 10.  

Ethical By Design – Marketing in the Age of Personalization and Privacy, Wealthengine. October 29, 2018. Accessed on 2/10/2021 < https://www.wealthengine.com/ethical-by-design-marketing-in-the-age-of-personalization-and-privacy/> 

Graham, John & Harvey, Campbell & Rajgopal, Shiva. (2004). The Economic Implications of Corporate Financial Reporting. Journal of Accounting and Economics. 40. 3-73. 

Khandelwal, Astha. “How Does Amazon & Netflix Personalization Work?”. March 30, 2021. Accessed on 2/10/2021 < https://vwo.com/blog/deliver-personalized-recommendations-the-amazon-netflix-way/ > 

Koetsier, John. “Only 17% Of Consumers Believe Personalized Ads Are Ethical, Survey Says”. Forbes. Accessed on 2/10/2021 < https://www.forbes.com/sites/johnkoetsier/2019/02/09/83-of-consumers-believe-personalized-ads-are-morally-wrong-survey-says/?sh=2c6f3e3a19f5 > 

Loverus, Anna. “Can marketing personalisation be unethical?”. April 18, 2018. Accessed on 2/10/2021 < https://annaloverus.com/unethical-targeting-personalisation/ > 

Lovelace, Robin. (2016). The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences , by Rob Kitchin. 2014. Thousand Oaks, California: Sage Publications. 

Nissenbaum, H. (1998). Protecting privacy in an information age: The problem of privacy in public. Law and Philosophy, 17(5-6), 559-596. https://doi.org/10.2307/3505189 

Omer, A and Dominique, L. “Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics”. 2015. New Jersey. 

Steinberg, E. (2020). Big Data and Personalized Pricing. Business Ethics Quarterly, 30(1), 97-117. doi:10.1017/beq.2019.19 

Van Doorn, Jenny & Hoekstra, Janny. (2013). Customization of online advertising: The role of intrusiveness. Marketing Letters. West, Emily.2019. Amazon: Surveillance as a Service.Surveillance& Society17(1/2): 27-33. https://doi.org/10.24908/ss.v17i1/2.13008