Posted: August 1st, 2022

Big Data: Privacy versus Personalization

Big Data: Privacy versus Personalization
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Introduction
As companies turn to the online platforms to market and sell their goods, and as consumers heavily rely on the online platforms for purchase of products and services, the issue of privacy arises in an attempt to provide highly personalized services to consumers. Providing highly personalized services to consumers require companies to have a deep understanding of the needs of the consumers, their history in terms of purchase, as well as their preferences. In short, companies hold a lot of consumer data regarding their preferences and online behaviour. More personal information such as contact addresses and physical addresses is held by the companies since in most cases, the retailers communicate with the buyers through email. It is, therefore, more likely that consumers tend to hesitate before deciding what information to use why registering to an online shop. On the other hand, companies have to prove to consumers why they should feel safe while haring their personal data with them. To further address the issues on privacy and personalization, some factors have to be considered into detail as will be indicated in the paper which includes; how brands benefit from the big data context, how personalization gradient influences consumer concerns when online, and how personalization and privacy influences consumer behaviour.
How brands benefit from the big data context
To understand the correlation between privacy and personalization of big data in the online consumer world, we have to understand what big data is and how brands grow as a result of the readily available information. Big data analytics is an aspect that examines a large amount of data available in a system to draw out patterns and correlations (Brock & Khan, 2017). The world of technology today presents a situation where personal data can be analyzed and useful information derived from it. Many brands today are aware that they can utilize the information regarding consumer data by applying analytic to get meaningful value from it. Big data analytics technologies have made it easier for companies to identify potential clients by analyzing consumer needs through their online behaviour. Social media platforms have been a major source of information for companies that seek to increase their revenue by utilizing big data analytics technologies (Taylor et al., 2009).
To reap maximum revenue, companies must start by identifying their business reasons that motivate them towards making use of big data analytics and then identify the type of analytic to use to collect and process data. One of the major reasons for utilizing big data analytics technologies such as Hadoop as well as other cloud-based technologies is to minimize expenditure cost. Collecting information from Google, Facebook, Twitter, and YouTube among other online platforms and storing the data in the company systems saves time and money that could have been used on hiring people to conduct market surveys. It is hence a faster and more affordable way of collecting consumer data which also enables the brands to identify new ways of conducting business given the data collected on competitors. Secondly, the system offers a faster and more informed decision-making approach. Hadoop is known to be super-fast software where business can make real-time information analysis and hence make decisions regarding the information they receive. For example, a new competitor may come up and within a short period, a brand will have discovered the new business, what if offers, and therefore make decisions on what to improve on in their products and services. Lastly, through big data, a company is able to collect consumer needs and hence come up with new products and services that are personalized to meet their unique needs for maximum sales and revenue. Walmart is among the largest online retailers that aim at maximizing its profit by providing maximum consumer satisfaction in all the locations it operates in, as well as maintaining the stores’ standards (Singh et al., 2017). The sales data of Walmart play a big role in providing consumer insight to the retailers affiliated with the store. It is through the data gathered that the retailers get to allocate their resources in a more informed way which may include the need to increase stock or employees working with Walmart. The retailers are hence able to make significant changes that help to make them competitive in the market and make changes that sustain the future of their businesses.

How the gradient of personalization impact customer concern when online

In as much as consumers are more appreciative of customization in product and service provision, many are concerned to the extent at which their privacy may be intruded. Customers are beginning to raise questions regarding how companies can personalize their needs, how they store the personal details shared, and how trustworthy third parties are. Consumer data is collected during site registration, when filling in warranty forms, and when making a transaction. For brands to communicate with consumers, they have to interact on the online platforms and at times, some very personal information may be exchanged such residential addresses, family size, and health status of an individual when buying products such as paint. Brands need to gather some more detailed information about the consumer for them to meet the precise consumer needs that are safe and very convenient for the longevity of business transactions between the two parties as well as increasing revenue (Alsghaier et al., 2017).
Companies with well-structured data security measures are more likely to have long-term consumer retention. On the other hand, companies that are known to breach consumer data, or have questionable conduct scare away consumers as they may be worried over who else has access to their information. For example, a consumer visits an online store to buy a one-time item that they may never need again in their lifetime such as paint for their old house. After closing the deal and the paint is delivered, the consumer discontinues interaction with the online store by unsubscribing from the store’s email notification. However, when the consumer gets online to search for other products, they receive ads on paint by the former store and other paint stores in their notifications. Such a consumer will be concerned over how the information got shared and how much more of their information could have been spread. It is wise that companies assure consumers of what type of their information will be shared with third parties to avoid unnecessary privacy concern that may draw consumer away hence leading to loss of revenue.

Online privacy concerns fall under different categories which determine the degree of trust that a consumer will have on an online store. User anonymity allows the consumer to access the online platforms without revealing their identity and hence untrusted sites will not be able to link the identity of the user to request that they receive. Sensitive information such as IP addresses is not available hence assuring consumer safety while making online marketing interactions (Petrescu & Krishen, 2018). On the other hand, disclosure of private information about a known user raises concerns among consumers. Some sites may promise to safeguard personal information such as age while others disclose the information to other sites.

Nondisclosure and anonymity guarantee will draw more users to a site that promise to offer security to personal information. Online companies that utilize data security protection have higher chances of retaining their consumers, unlike those sites that leave consumer worried over their online safety. It is, therefore, no doubt that having a great balance between the privacy needs of the consumers and the personalization of product and services can improve customer experience and hence retaining customers, drawing more traffic, and increasing revenue for the business.

How personalization and privacy impact behaviour on individuals
The more secure a site is, the more frequent a consumer will use the site and hence the more the consumer retention capacity for the company. In some or most cases, consumers are not aware that personal information is being collected until the point where they receive some sort of personalized communication from the firm (Habegger et al., 2014). Most of the firms use emails to send the information to the unsuspecting consumers and address them by their names which send mixed reactions among consumers. On one hand, the consumer is elated that the firms appreciate them and is willing to provide personalized ales including personalized pricing which will draw the consumer to purchase a product from the company. On the other hand, a more informed consumer will notice the interplay if their-parties in the acquisition of non-self-disclosed information which may make the consumer turn away from accessing the firm (Bol et al., 2018). The trust between the firm and the consumer is hence broken and there is no willingness to purchase from the firm. Broken trust means that there is the unwillingness of the consumer to continue in further purchase with the firm. Consumers are more likely to participate in future purchases and even spreading the word on a company if they feel both appreciated in terms of personalization of their needs and secure in terms of data privacy.
Conclusion
Personalizing customer experience will on the positive side retain the customer and hence increase revenue for the brands since customers are more appreciative of brands that recognize their individual needs. There are instances where the personalization may go wrong. For example, companies that may collect data of pregnant women based on the sites they visit online and sending the pregnant women gift coupons may raise issues with the women or the family members especially when they had decided to keep the pregnancy a secret. Another example is when one makes a one-time purchase for a friend and leaves the site but will still keep getting ads on the particular items they bought for the friend every time they are online. Too much invasion is annoying to a consumer and may lead to loss of customers as a result of privacy concerns. Companies hence need to learn how to strike a balance between consumer privacy and personalization to avoid too much invasion and to retain the comers for maximum revenue.

Annotated Bibliography
Alsghaier, H., Akour, M., Shehabat, I., & Aldiabat, S. (2017). The importance of big data analytics in business: a case study. American Journal of Software Engineering and Applications, 6(4), 111. The article informs on how companies generate revenue from accessing data from social media by making use of big data analytics. It talks of how the big data analytic technology guides a company in making more informed business decisions that increase revenue.
Bol, N., Dienlin, T., Kruikemeier, S., Sax, M., Boerman, S. C., Strycharz, J., … & de Vreese, C. H. (2018). Understanding the effects of personalization as a privacy calculus: Analyzing self-disclosure across health, news, and commerce contexts. Journal of Computer- Mediated Communication, 23(6), 370-388. The authors analyze the impact of disclosing personal information across various field inclusive of commerce and how personalization affects their privacy.

Brock, V., & Khan, H. U. (2017). Big data analytics: does organizational factor matters impact technology acceptance?. Journal of Big Data, 4(1), 21. The article was useful in explaining what big data is and how organizations and companies are making use of it.

Habegger, B., Hasan, O., Brunie, L., Bennani, N., Kosch, H., & Damiani, E. (2014). Personalization vs. privacy in big data analysis.The article introduces the reader to what personalization is and how big data analysis techniques are used by companies to personalize consumer needs hence maximizing revenue.
Petrescu, M., & Krishen, A. S. (2018). Analyzing the analytics: data privacy concerns. Petrescu and Krishen, introduce scholars to various dangers that they are exposed to by sharing their information online. It warns of how consumers may be unaware of their data being shared. The article draws insight into the need to have a balance between personalization and privacy for best customer experience.

Singh, M., Ghutla, B., Jnr, R. L., Mohammed, A. F., & Rashid, M. A. (2017, December). Walmart’s Sales Data Analysis-A Big Data Analytics Perspective. In 2017 4th Asia- Pacific World Congress on Computer Science and Engineering (APWC on CSE) (pp. 114-119). IEEE.The authors basically explore how retailers at Walmart utilize big data analytics to identify consumer need in order to personalize their services.

Taylor, D. G., Davis, D. F., & Jillapalli, R. (2009). Privacy concern and online personalization: The moderating effects of information control and compensation. Electronic commerce research, 9(3), 203-223. This article was very useful in that it provided information on how personalized online interactions between consumer and firms can create a bond. It also informed on how the willingness of a consumer to make further purchases and spread the word regarding a firm is dependent on how well the personalization and data privacy is.

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