How Your Run is Turning into Amazing Customer Experiences for Nike: Data Collection and Invasive Marketing

Nike’s digital retail and fitness guidance apps are working together to improve customer experiences and create loyal buyers through the method of data collection. Certain app affordances by their fitness guidance apps provide relevant data which illustrate how they maintain their incredible customer experiences. This blog post questions these methods using theoretical frameworks centred around data mining and usage to provide both criticism and possible solutions to the ethical implications of invasive marketing tactics.

“Will large scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing?” (Boyd and Crawford 663). Since Nike has adopted its method of collecting data by their popular fitness tracking apps and using this to create valuable customer insights it has created an unrivalled customer experience compared to any other competitor in the fitness industry (Here’s how Nike is turning data into unrivalled customer experiences). The huge amount of data generated by Nike apps are being mined and analysed by leading data analytics company Zodiac which allows Nike to collect data points on their apps as well as their connected apps. The relevance of this marketing model can be seen through competitors attempt at mimicking it, for example, demonstrated by Adidas’ recent release of the app Adidas Training and Adidas Running. Data at such a large scale has always been seen in the market as a huge opportunity and fitness tracker data in specific have been largely discussed in both the academic field and news for its use in health insurance optimisation. When looking at how the affordances of the app generate specific data that provide customer insights for the company it becomes an object worth critically assessing.

Nike Run Club

Nike Run Club advertises itself as a free app that offers endless motivation, support and guided coaching sessions. This is not a new phenomenon, our obsession with tracking our health has been around since the 1960s where health tracking devices have been growing at a rapid pace taking inspiration from the first Manpo-kei (10,000 steps meter) invented by Yoshiro Hatano (Waton A study of fitness trackers and Wearables). With the introduction of smart devices, fitness trackers can now “store data and automatically analyse them to provide insights into the quantified self” (Henkel et al. 31). Nike Run Club introduced a new affordance that allows users to select which shoes they wish to wear for their run, this way the user can see how much mileage is made on each pair of shoes and Nike knows exactly when the user will be needing new running shoes. I turn to the famous concept that Raw Data is an Oxymoron, where “data too need to be understood as framed and framing, understood, that is, according to the uses to which they are and can be put” (Gitelman and Jackson 5). The affordance ensures that this data will serve a very specific purpose, namely personalisation on their digital retail channels. This is subsequent to ethical concern as “[f]eatures like personalisation allow rapid access to more relevant information, but they present difficult ethical questions and fragment the public in troubling ways” (Boyd and Crawford 664). The app has zero pop up ads, zero ad campaigns, its marketing is so incredibly invasive but is presented in a very passive manner.

Ethical Implications

This case can be seen as unique as technically this marketing model does not sell data to third parties, but is still used with personalisation as the end goal. Crawford and Boyd discuss the concept of the imagined audience, where “[u]sers are not necessarily aware of all the multiple uses, profits, and other gains that come from the information they have posted” (673). Despite the privacy policies and terms and conditions that apps make available to the user, there is generally a lack of knowledge on how individual data is being used and shared because most people don’t read these policies let alone understand them (Vitak et al. 235). Data on human subjects inherently raise issues regarding privacy and the way in which this poses risks of abuse (Boyd and Crawford 627).  These outline some of the political dimensions of data, wherein data cannot speak for itself, it’s only through methods of interpretation that they can be used and in this case, be abused. Critical aspects of data are important to discuss as data is becoming an integral part of capitalism and serves as a form of currency.

The Importance of Accountability 

Some runners may like the idea that once their shoes get worn out Nike will be giving them ads to get new ones, and others may not. Personalisation can be a great thing but it is important to note that just because data is accessible does not make it ethical to collect and use. This begs the question, is there an ethical way to use data? Boyd and Crawford introduce the concept of accountability, which is a multi-directional relationship (673). If companies were to adopt this academic method of handling data by being more direct and transparent with their data usages it shifts some of the hierarchical power structures in place when it comes to owning data. It would also allow companies to reflect upon the ramifications of their processes and could possibly make these personalised experiences more ethical. Unfortunately, this is highly unlikely because companies such as Nike thrive on “online data mining, widespread data aggregation, and confusing privacy settings” (Vitak et al. 231). The level of power and control they have on this pervasive method of data mining is not likely something they will willingly give up.

Works Cited

Boyd, Danah and Kate Crawford. “Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information, Communication and Society, vol. 15 no. 5, 2012, pp. 662-679. https://doi.org/ 10.1080/1369118X.2012.678878.  

Gitelman, Lisa and Virginia Jackson. Introduction. “Raw Data” Is an Oxymoron . The MIT Press, 2013, pp. 1-14.

Henkel, Maria, et al. “Rewarding Fitness Tracking—The Communication and Promotion of Health Insurers’ Bonus Programs and the Use of Self-tracking Data.” Social Computing and Social Media. Technologies and Analytics, 2018, pp. 28-49. doi:10.1007/978-3-319-91485-5_3. 

“Here’s How Nike Is Turning Data into Unrivaled Customer Experiences.” NGCX 2022, WBR Insights, 18 Mar. 2021, nextgencx.wbresearch.com/blog/nike-data-unrivaled-customer-experiences-strategy. 

Milnes, Hilary. “In Effort to Grow Direct Sales, Nike Integrated Its App Strategy into Its Stores.” Digiday, 25 Apr. 2019, digiday.com/retail/nike-integrated-app-strategy-stores/. 

Vitak, Jessica, et al. “Privacy Attitudes and Data Valuation Among Fitness Tracker Users.” Transforming Digital Worlds, 2018, pp. 229–39, doi:10.1007/978-3-319-78105-1_27.

Waton, Josh Douglas. “A Study of Fitness Trackers and Wearables.” HFE, HFE, 20 May 2020, www.hfe.co.uk/blog/a-study-of-fitness-trackers-and-wearables/.