Personalized offers without compromising the privacy of personal information

Searching on the internet for information is one of the most common activities these days. This behavior varies from searching for the closing time of your favorite shop, to finding out how cognitive processes work. Consumers are generating and sharing data when they search on the web. The knowledge of this process is not always present. Even if consumers knew their steps were being followed, would it change their daily behavior? Privacy is not a new term. Yet, it disclosed itself more than ever the last couple of decades, together with the introduction of the Internet. The general definition is the right to be let alone. It is based on the principle of protection of the individual in both person and property (Warren & Brandeis, 1890). However, this definition is too broad. Informational privacy fits more in the context of these days. The definition is the right to control of access to personal information (Moor, 1991).
It is clear that privacy concern is an issue for companies. Companies want to use personal information to offer personalized adverts which is often considered as something positive by the consumers. A business example is Amazon.  The well-known E-commerce company continually updates the user’s personal page to create more tailored experiences. This is done based on past purchases and browsing history and the objective is to stimulate impulse buys (Reverte, 2013). However, personalization has some concerns.



Sutanto, Palme, Tan and Phang (2013) wrote an article in which they study the so called personalization-privacy paradox. This is the tension between how IT developers and marketers of applications exploit personal users’ information to offer personalized products or services and these users’ increasing concern regarding the privacy of that information. Eventually, this may restrain the use of these applications. The purpose of this paper is to study whether a personalized privacy-safe application works. This application stores and processes information within the user’s smartphone, but does not transmit it to the marketers. This way, personalized information can be offered, without compromising the privacy of personal information (Sutanto, 2013).

Personalized privacy-safe application
To understand the personalization-paradox, the authors build on two theories; the use and gratification theory (UGT) and information boundary theory (IBT).  UGT suggests that consumers use a medium either for the experience of the process or for the content it offers. These two dimensions are called process gratification and content gratification (Sutanto et al., 2013). While the latter refers to the messages carried by the medium, the first one relates to the enjoyment of using the medium.

Next, IBT gives a better understanding in which factors influence process and content gratification.  This theory suggests that consumers form so-called physical or virtual information spaces around themselves. These spaces have boundaries and an attempt by third parties to cross these boundaries will be considered invasive which makes consumers uncomfortable.   In case of an intrusion, consumers will apply a risk-control assessment, weighting the risk of disclosing personal information and the benefits they gain when doing so (Stanton, 2003).

This study conducted a field experiment with three mobile advertising applications. The first mobile application broadcasts adverts generally (i.e. non-personalized application). The second application filters and displays adverts based on the profile information of users, stored in a central server (i.e. personalized, non-privacy-safe application). The last application filters and displays adverts on the profile information of users, stored on their smartphone (i.e., personalized, privacy-safe application). In this context, process gratification is measured with the number of application launches.  On the other hand, if a user is interested in the content offered by the application, they are more likely to save the advert with the purpose of retrieving it later, thus content gratification is measured in terms of the frequency of saving adverts (Sutanto et al., 2013).

Personalized application

The results of the field experiment showed that there is indeed a difference in process and content gratification between the three different applications.  Process gratification increased by 64.5% when the adverts were personalized compared to when adverts were general. However, there was no significant difference in content gratification. This may be explained by the fact that saving adverts explicitly indicates interest in a specific product, thus it requires the user to reveal deeper levels of information than their own boundaries allow. It is likely that this situation causes an uncomfortable feeling and which eventually will lead to a hesitation to save adverts.  Next, the local privacy-safe personalization design increased both process and content gratification. Application use increased by 9.6% compared to personalized, non-privacy-safe application and by 79.1% compared to the non-personalized application.  Respectively, advert saving increase by 24.5% and 55.1%.

However, there is an important limitation in this paper. There is a possibility that some users launched the application, but already were interested in a certain ad. This makes it more difficult to disentangle process gratification from content gratification.

Concluding, this article proposes a personalized privacy-safe application. The results show significant differences between the three applications in favor of the local privacy-safe personalization application. Thus, offering personalized adverts without compromising the privacy of personal information is possible.


Moor, J.H. (1991) ‘The ethics of privacy protection’, , pp. 69–82

Reverte, C. (2013) Personalization Innovators: Amazon, Netflix, and Yahoo! | Available at: [Accessed 18 February 2018].

Stanton, J. M. (2003). Information technology and privacy: A boundary management perspective. In Socio-technical and human cognition elements of information systems (pp. 79-103). Igi Global.

Sutanto, J., Palme, E., Tan, C. H., & Phang, C. W. (2013). Addressing the Personalization-Privacy Paradox: An Empirical Assessment from a Field Experiment on Smartphone Users. Mis Quarterly, 37(4).

Warren, S.D. and Brandeis, L.D. (1890) ‘The right to privacy’, Harvard Law Review, 4(5), pp. 193–220. doi: 10.2307/1321160

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