AKF

Incorporating Object-Oriented Analysis into Market Driven Mobile Ethnography

November 2019

Section 1 Purpose of my study

Current mobile technologies used for market ethnographic research are geared towards understanding consumer needs, desires, and pain points of a user journey. They typically function as a crowd sourcing platform that incentives users to provide feedback on consumer goods through payment. Once in the system, a user provides feedback on customer experience related to a particular product, store, or activity in the form of video diaries, textual notes, or prompts given from push notifications. There are a number of benefits for using mobile ethnography, some of which are in its price as it is cheaper than hiring a team of ethnographers to do research (Indeemo 2018). Another benefit is in its ability to reach a wide range of users from different locations (Indeemo 2018). Mobile ethnography also affords methodological naturalism as it unpacks the participant perspectives of everyday life, captures mobility within the marketplace, and begins to democratize the research process (DeBerry-Spence et al 2019).

While mobile ethnography is effective in getting the consumer feedback overtime and space, there is a missed opportunity to receive insight from the consumer goods they are interacting with, especially those that make up the Internet of Things. These smart objects in the Internet of Things possess their own capacities and kinds of experiences in interaction with the consumer and each other that could be useful for ethnographic market research (Hoffman et al 2017). According to Meyer (2016) the overall IoT industry is expected to be worth $3 trillion in 2025, with 27 billion different types of smart things connected to the internet. These objects are equipped with sensors and actuators and can sense, perceive, and act in an environment. Because of these sensing capabilities, design researchers have begun to explore user experiences from the orientation of the “thing” or smart object (Giaccardi et al 2016). The benefits of such angle of analysis is that generated insight can not only tell the researcher more about the thing itself, but about the user as well. It serves as a sort of reflexive method to obtain a deeper insight into consumer-object or human-thing relationship.

Given the prevalence of smart objects in the Internet of Things that are populating homes—Alexa, Google Home among others, there is a potential for mobile ethnography to incorporate networked capabilities from these smart objects into the software in order to receive data from the object itself (Hoffman et al 2017). Potential pain points could be observed if the quantitative and qualitative data of both the consumer and object are analyzed and assessed side by side. This study would function to consider the implications for this type of ethnography—what type of data can be generated and what sorts of insights can be revealed from incorporating an object-oriented perspective into mobile ethnographic software.

Section II Relevant Literature

For the purposes of this research, I conducted a literature review that investigates design approaches from a non-anthropocentric perspective in the context of mobile ethnography. Academic articles from scholarly journals and books which are peer reviewed from credited sources from the basis of my review in which the focus is to research and analyze a variety of methods that aim to elevate the artifact as co-ethnographer and or research artifact experience through an object oriented perspective. The articles explore ways to observe and identify aspects of artifact ontology including its essence, or materiality, its ability to perceive, sense, and observe, and how humans and artifacts can collaborate in the ethnographic process in the context of networked smart environments.

Concept Map of Literature:

Section III Prior Work

In order to get a deeper understanding about current uses of ethnography, I conducted an interview with a design researcher and did a mini ethnographic study of two urban parks in downtown Raleigh. These studies revealed insights into means, methods and attitudes towards ethnography in the corporate context as well as affordances and limitations of individual participant observation of a dynamic urban environment.

Section IV Proposal

For my proposal, I am interested in how can the design of a multi-use mobile ethnographic tool that incorporates both the human (consumer) data and object (smart thing) data can serve as a viable research tool for market researchers in the professional context. How can this tool incorporate several researchers in collaborative, observational work? How can its interface enable asynchronous annotation and data input? How can the software leverage the networked capabilities of interconnected smart things on the web to to incorporate their data in the researcher observation platform? And how a collaborative web platform provides access to the data in a visually organized way?

Methods

I will select a range of participants and begin by conducting interviews.

I will also send participants a cultural probe package in order to gain insights into their general feelings about mobile ethnography and the smart objects they possess. I will use both the interviews and cultural probe information as research to help generate personas.

Once I do the interviews and get the cultural probes I will send out instructions for them to do an ontography map in which they map out objects in her home (the fixed ones that do not move) on top of a floor plan they will provide.

I will then send each participant a fit bit that is equipped with a sensor to track their location as well as sensor to track how much time it has been used. This way I can accumulate data on its use and location as well as proximity to other objects in the home. They will use the fit bit for a month.

During the month I will prompt them 2 times a week with questions regarding their attitudes towards the fitbit. They will also be responding to prompts from the mobile ethnography company's general website. They will do this in the form of diary studies, interviews, and photo studies.

After the month, I will have accumulated enough data on all participants on their day to day life as well as that of the Fitbit. I will combine this data together to see what insights unfold.

Data

  • Will be from their month long study:
  • Data from diary studies, photostudies, questionnaires, interviews, personal inventories, ontography map and floor plans, videos, images received by Mindswarms.
  • Answers to prompts related to the Fitbit
  • Data on the fit bit’s location and use throughout the month.

Resources

  • 5 fit bits
  • For each participant:
  • $25 for the initial interview
  • $50 for the ontography map, floor plan, and personal inventory
  • $250 total for the whole study
  • 5 participants: $1,250
  • 5 Fitbits: $50/each: $250
  • Total: $2500

Timeline

  • January 1 - March 5
  • Jan 1: Mindswarms puts out a call for participants.
  • Jan 6: Mindswarms sends out a list to me with potential participants, I narrow down.
  • Jan 7-11: Interviews Occur: 5 are selected.
  • Jan 12: Initial payment of $25.
  • Jan 13: Secondary payment of $50
  • Jan 14: Fitbits are sent out.
  • Jan 18: Pilot test to make fitbits work.
  • Jan 20: Study begins.
  • Jan 20 - 27 (Week 1): 2 prompts from me, 3 prompts from Mindswarms:
    • Diary Studies, Photo studies, Videos, Images
    • Receive Ontography maps, cultural proves, and personal inventory.
  • Jan 28 - Feb 4 (Week 2): 2 prompts from me, 3 prompts from Mindswarms:
    • Diary Studies, Videos, Images.
    • Send Mid-Study compensation: $50.
  • Feb 5 - 10 (Week 3): 2 prompts from me, 3 prompts from Mindswarms:
    • Diary Studies, Videos, and Images
    • Feb 11 - 18 (Week 4): 2 prompts from me, 3 prompts from Mindswarms: Diary Studies, Videos, and Images
    • Feb 18: Send out a return package with instructions on how to send the Fitbit.
    • Feb 18: Wire the remaining money for each participant: $125.
    • Feb 20: Follow up interview over the phone asking about participants experience.
    • Feb 20: Have the participants fill out a questionnaire about experience.
    • Feb 23: Receive all Fitbits, upload data on to computer.
    • Feb 24: Package and return Fitbits to owners.
    • Feb 25: Begin analysis of data.
    • Feb 25-March 5: Analyse data, create charts, graphs, and write up the results of the study.

References

Aisher, A., & Damodaran, V. (2016). Introduction: Human-nature interactions through a multispecies lens. Conservation and Society, 14(4), 293-304. doi:10.4103/0972-4923.197612

Bennet, J. (2010). Introduction. Vibrant Matter: A Political Ecology of Things. NC: Duke University Press.

Bødker, S., & Klokmose, C. N. (2012). Dynamics in artifact ecologies. Proceedings of the 7th Nordic Conference on Human-Computer Interaction Making Sense Through Design - NordiCHI 12. doi: 10.1145/2399016.2399085

Bogost, I. (2012). Alien phenomenology, or, What its like to be a thing. Minneapolis: University of Minnesota Press.

Bowens, M. (2018). The Flesh of The Perceptible: The New Materialism of Leviathan. Film-Philosophy,22(3), 428–447. doi: 10.3366/film.2018.0088

Chang, W.-W., Giaccardi, E., Chen, L.-L., & Liang, R.-H. (2017). Interview with Things: A First-thing Perspective to Understand the Scooter’s Everyday Socio-material Network in Taiwan. Proceedings of the 2017 Conference on Designing Interactive Systems - DIS 17. doi: 10.1145/3064663.3064717

Deberry-Spence, B., Ekpo, A. E., & Hogan, D. (2018). Mobile Phone Visual Ethnography (MpVE): Bridging Transformative Photography and Mobile Phone Ethnography. Journal of Public Policy & Marketing. doi: 10.1509/jppm.16.228

DiSalvo, C., & Lukens, J. (2011). Nonanthropocentrism and the Nonhuman in Design: Possibilities for Designing New Forms of Engagement with and through Technology. From Social Butterfly to Engaged Citizen. US: The Mit Press.

Forlano, L. (2016). Decentering the human in the design of collaborative cities. Design Issues, 32(3), 42-54. doi:10.1162/DESI_a_00398

Forlano, L. (spring 2017). Posthumanism and Design. She Ji: The Journal of Design, Economics, and Innovation, 3(1), 16-29. Retrieved April.

Giaccardi, E., Speed C., Cila N., & Caldwell, ML. (2016). Things as Co-Ethnographers: Implications of a Thing Perspective for Design and Anthropology. (n.d.). Design Anthropological Futures. doi: 10.5040/9781474280617.ch-015

Hoffman, D. L., & Novak, T. P. (2016). Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach. SSRN Electronic Journal. doi: 10.2139/ssrn.2840975

Indeemo (2018). White Paper: An Introduction to Mobile Ethnography. Indeemo, November 11, https://indeemo.com/mobile-ethnography-white-paper.

Kuijer, L., & Giaccardi, E. (2018). Co-performance. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI 18. doi: 10.1145/3173574.3173699

Meyer, David (2016), “Why Smartphones Are Bringing Down Internet-of-Things Revenue Forecasts,” Fortune, April 4 ,http://fortune.com/2016/08/04/smartphones-iot-revenue-ma china/.

Pink, S. (2015). Introduction: Doing Sensory Ethnography. Los Angeles: SAGE.

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