Big Data Analytics: Impact of AI on Consumer Privacy and Marketing

This report delves into the multifaceted impacts of big data analytics and artificial intelligence on consumer privacy and marketing strategies. It examines the evolution of data storage, security, and sharing practices in the context of AI advancements, highlighting the emergence of new concerns in data privacy and security. The report explores how big data has introduced both opportunities and challenges in marketing, including the importance of data security, privacy, and its effects on consumer behavior. It references several studies and research that support the claims. Additionally, it discusses the impact of AI on customer service and the need for service providers to ensure customer privacy and security when interacting with their accounts. The report emphasizes the importance of understanding these complex relationships for businesses and consumers alike.

Running head: BIG DATA ANALYTICS 1
Big Data Analytics
Name
Institution

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Big Data Analytics
Big Data, Artificial Intelligence, and Consumer Privacy
Solutions to many pressing economic and social problems lie in the understanding and
interpretation of data. New tools have been developed to analyze data sets that have accumulated
to form big data. The era of big data has brought a breakthrough, particularly in businesses where
it is critical in marketing and research. Firms are gathering data hoping to use it in the future.
“The data is the oil of economies” as Welel, and Kannan (2016) stated. Also, courtesy of big
data, artificial intelligence has spurred exciting innovations. Both AI and big data have changed
how consumer privacy and data security is perceived. A lot has changed on how data is stored,
secured, and shared in forms that ensure consumer privacy and security. However, the changes at
the advent of AI have introduced a new whole new level of concerns in data privacy, security,
and laws (Insights Team, 2019). In this regard, the AI as the development in big data has
presented an innovative method of data analyses and use but has a far-reaching impact on
consumer privacy and security.
Big Data Comes with Consumer Privacy Issues
In 2018, Lizot and Islam found online privacy concerns could hurt consumers’
engagement and business customer relationship. Perera, Ranjan, Wang, Khan, and Zomaya,
(2015) observed that the internet of things have affected consumer privacy and hence exposed
their data to security threats. According to Brill and Jones (2016), privacy concerns are created
regarding the perceived data benefits, cloud storage security, business reputation, and
transparency of the infrastructure. Big data has led to the notion that big is better than but
challenging compared to little things which limit decision making.
Artificial Intelligence has Impacted on Consumers

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Åberg and Khati (2018) found that consumers are willing to accept the IVR technology
and adapt to its use to the extent the technology offers them the required satisfaction. André et al.
(2018) have found that AI limits consumer autonomy in matters choices, and behavior. They
found that consumers are willing to accept and adapt AI technologies to the extent they offer
required satisfaction. However, Attaran, Attaran, and Kirkland (2019) found that most
consumers are skeptical about the AI-driven customer service because they are unaware of its
benefits and doubts about how their privacy is handled. As such, service providers have a
responsibility to assure customers of their privacy and security when interacting with their
accounts.
Big Data has Affected Marketing Approaches
Alshura and Zabadi found that the era of big data has changed how businesses handle
data, and it has been challenging. Although big data is essential to marketers, Couldry and
Turow, (2014) found it challenging to leverage its benefits due to a large amount of data
available, laws, and consumer privacy concerns. However, according to Martin and Murphy
(2017), companies have tried to harness the presence of big consumer data which expose them to
breach of privacy and security. The findings are significant as they are drawn from diverse and
credible qualitative and quantitative research. Big data has facilitated reach to consumers and at
the same time posed a threat to their privacy

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References
Alshura, M. S., Zabadi, A., & Abughazaleh, M. (2018). Big Data in Marketing Arena. Big
Opportunity, Big Challenge, and Research Trends: An Integrated View. Management and
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André, Q., Carmon, Z., Wertenbroch, K., Crum, A., Frank, D., Goldstein, W., ... & Yang, H.
(2018). Consumer choice and autonomy in the age of artificial intelligence and big data.
Customer Needs and Solutions, 5(1-2), 28-37.
Åberg, E., & Khati, Y. (2018). Artificial Intelligence in Customer Service: A Study on
Customers' Perceptions regarding IVR Services in the Banking Industry.
Attaran, S., Attaran, M., & Kirkland, D. (2019). Savoring the product: a look at the impact of ai
on pre and post-purchase satisfaction in 2019 Global Fashion Management Conference at
Paris (pp. 614-625).
Brill, H., & Jones, S. (2016). Little things and big challenges: information privacy and the
internet of things. Am. UL, Rev., 66, 1183.
Couldry, N., & Turow, J. (2014). Advertising, big data, and the clearance of the public realm:
marketers' new approaches to the content subsidy. International Journal of
Communication, 8, 1710-1726.
Insights Team. (2019). Welcome from Forbes to a special exploration of AI. Retrieved from
https://www.forbes.com/sites/insights-intelai/2019/05/22/welcome-from-forbes-to-a-
special-exploration-of-ai-issue-6/#49c5b2b04650
Lizot, E., & Islam, S. M. (2018). The impact of Privacy concerns in the context of Big Data: A
cross-cultural quantitative study of France and Bangladesh.

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Perera, C., Ranjan, R., Wang, L., Khan, S. U., & Zomaya, A. Y. (2015). Big data privacy in the
internet of things era. IT Professional, 17(3), 32-39.
Martin, K. D., & Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the
Academy of Marketing Science, 45(2), 135-155.
Wedel, M., & Kannan, P.K. (2016). Marketing analytics for data-rich environments. Journal of
Marketing, 80, 97-121. https://doi.org/10.1509/jm.15.0413