Blog post

Your Sensored Life: An Expanded View of Quantified Self

By Mike Gotta | January 20, 2014 | 2 Comments

Since mid-2013 I have been looking at the quantified self movement and how use of wearable technologies and mobile self-tracking apps have become integrated with social network sites, allowing people to share experiences, build community, and gain peer support (illustrated in Figure 1). My focus on quantified self grew out of my research into social networks and how ethnographic research could help business and IT strategists better understand social networking, including design practices for social network sites. Ethnography has been an interest of mine for a few years. Some time ago I contributed a guest blog post (“Can Ethnography Save Enterprise Social Networking”) to Ethnography Matters, a popular site that discusses various aspects of the craft. As quantified self becomes more established in the market, its intersection with mobility, social networking, and ethnography is one of the most intriguing areas of my coverage.

Figure1

Figure 1: Quantified Self – More Than Wearable Gear & Self-Tracking

I tend to think of quantified self beyond just wearable gear and self-tracking. In my mind, the trend is more about how aspects of our lives have become, or are fast becoming, quantified (or sensored) which raises significant societal issues. For the Gartner audience, the key issues are more related to how business and IT strategists should respond to this confluence of trends.

Major brands (e.g., Nike) are strategically providing consumers with such community environments (Figure 1: Digital Business). Wearable devices, mobile self-tracking apps, and the self-tracking information people share with community members provides business strategists (e.g., digital marketers, product/service teams, and innovation groups), with opportunities to engage audiences in new ways, build more collaborative customer relationships, and gain a competitive edge. The network effects arising from quantified self have led me to examine a variety of different impacts ranging from accelerators like Rock Health (Figure 1: Funding & Business Development), to fashion issues (Figure 1: Society at Large), and how organizations might position quantified self within wellness programs – in turn, leveraging enterprise social networking platforms for the personal support and community aspects (Figure 1: Workforce Engagement). Down the road, the types of self-track apps and supporting services for quantified self could intersect with smart machines such as smart advisors and virtual personal assistants (Figure 1: Internet of Things).

The opportunity for unpacking some of these trends presented itself at the EPIC 2013 conference held in London this past September where I was fortunate enough to moderate a workshop, “Mobile Apps & Sensors: Emerging Opportunities For Ethnographic Research” The focus of the session was based on two trends:

  • Mobile apps are emerging that are specifically designed for observational and participatory ethnographic field research (e.g., Ethos App, MyServiceFellow , and Over The Shoulder). These apps can also be used as part of market research efforts, augmenting current practices that rely on surveys, interviews, and focus groups.
  • The ethnographic community has also become interested in trends related to quantified self, giving rise to discussions (and debate) on how self-tracking, personal data / data aggregation, and common API’s can also support field research activities.

While the workshop was not intended as an in-depth presentation on the issues, preparing for the session helped me to organize some thoughts and build on two key related pieces of 2013 researched published just prior to the event:

For an overview of the workshop, I encourage you to read a guest post submitted to Ethnography Matters, “Lessons Learned From EPIC’s Mobile Apps & Quantified Self Workshop”. I would like to thank Tricia Wang for reaching out and encouraging my research. This blog post acts as Part 2 to that contribution.

In the workshop, we discussed how increased use of mobile apps and quantified self is causing greater interest in blended research approaches (see Figure 2). While data science is perhaps the most popular approach covered in the media, use of social and behavioral sciences is also on the uptake to better understand the cultural and cognitive dynamics that influence people, decisions, relationships, and actions (individually and/or collectively).

Figure2

Figure 2: Shifting From Episodic To Continuous Observation

The key workshop conclusion (summarized in Figure 3), was that ethnographic research can be enhanced via purposeful mobile apps but can also be extended as quantified self becomes a broader market dynamic. However, common interfaces (e.g., APIs) might be needed to support field research activities. Also, for this type of intimate participation and third-party observation to be viable, attendees felt that research ethics and privacy issues (e.g., awareness, notice, and consent) had to be addressed. It was noted that there are many open-ended questions regarding the security, privacy, and data ownership rights related to quantified self.

Figure3

 Figure 3: Extending The Reach Of Ethnographic Research

I encourage you to share your viewpoint via comments. For clients, if you would like to discuss issues raised in this blog post, or my guest post on Ethnography Matters in greater detail, feel free to follow the Gartner inquiry process.

 

The Gartner Blog Network provides an opportunity for Gartner analysts to test ideas and move research forward. Because the content posted by Gartner analysts on this site does not undergo our standard editorial review, all comments or opinions expressed hereunder are those of the individual contributors and do not represent the views of Gartner, Inc. or its management.

Comments are closed

2 Comments

  • Thanks for this post Mike, it’s extremely interesting. The ease with which we can now track, observe and analyse how we go about our daily lives has definitely shifted how we can interpret what our potential audiences are doing.

    We’re starting to be able to understand how even this data could be manipulated by each person to project an image of their ideal self, much as they would choose the ‘right’ Facebook likes to share.

    Where it becomes really valuable is tracking shifts in which data people choose to share about themselves and the areas that will dominate (e.g. fitness apps).

    It certainly offers brands with a wide range of opportunities to connect better with their existing and potential audiences!

  • Craig Levine says:

    Thank you for this – we have been working with the real time sharing model for years (our patent is based on ingesting multiple sensors AND sharing this information in real time with their team/other individuals). Our main focus is law enforcement, but are expanding with first responders and eventually the consumer market…..