Part V: Representativeness

Representativeness emerged as a critical variable related to the User Data Spectrum research during the design of this survey. When a company engages in collecting, interpreting, and implementing user data, it must have the ability to choose the best collection methods, take the data collected and translate them, and then apply that translation to the product design. There are many variables that need be factored into the methods selection, translation, and

implementation process. This research suggests that the degree to which a decision maker is representative of the target end user of her product is related to where her company falls on the User Data Spectrum.

At the core of representativeness is empathy. There is a fair amount of research on

empathy across many fields of study, e.g., Gibbons (2010); Miaskiewicz (2008). “One who

empathizes suffers along with the one who feels the sensations directly. Empathy is similar to sympathy, but empathy usually suggests stronger, more instinctive feeling” (“Empathy,” n.d.). Similarly, empathy is a core skill of UX practitioners (Six, 2010). UX research methods such as day-in-the-life-of direct observation are intended to promote and foster empathy for end users. Psychology literature describes two types of empathy: state and trait. Trait empathy is based on personal characteristics that the observer may share with the one observed—in this case, designer and end user(s). Shared traits may include demographics (age, race, gender, socioeconomic status, and residence location), aptitude, attitude, cognitive abilities, physical abilities, knowledge, and values. However, a state type of empathy is when the observer and observed have gone through similar experiences or the observer can relate to the emotional impact of the observed (Felt, 2011). In the design literature, Kouprie and Visser (2009) referred to these two types of empathy as affective and cognitive. Affective empathy is when the observer can identify with the emotional response and feelings of the observed, similar to the state type of empathy in psychology literature. Cognitive empathy is when the observer understands and may share the same perspective as the observed, just as in trait empathy (Kouprie & Visser, 2009).

The representativeness measure in this survey assesses both state and trait types of empathy for individuals of the product development team. Aggregate of individual responses for the same organization will be used to assess organization representativeness.

4.11.2. Goal of the Representativeness Section

Assessing the representativeness of decision makers in product development is an important aspect of the User Data Spectrum research. The importance of individual responders’

degree of representativeness of the end user is related to whether or not that person is responsible for collecting, interpreting, and implementing user data. I propose that empathy is a limiting factor irrespective of placement along the spectrum; however, the degree of representativeness that the team possesses for end users is important to understand. If a team is more representative of end users, it may be able to flourish without as much direct user contact; however, if a team is low on representativeness, it may fare better on the participatory end of the spectrum where more direct user interaction takes place. Essentially, the degree to which members of the organization cannot empathize with end users, on both state and trait aspects, is the extent to which an organization might ultimately use this tool to see that it would benefit from following a

participatory model. For example, when I worked for John Deere, which produces equipment for farmers, I had low representativeness of end users. I have no agricultural background, and I did not match the demographics of the target audience of farmers I designed for. Therefore, I relied on direct interaction with the farmers to better serve them through my designs.

Table 4.10. Part V Questions

No. Question

Q64 Describe the gender of the target end user for product. (check all that apply) Q65 Describe the ethnicity of the target end user for your product. (check all that

apply)

Q66 Describe the region that the target end user for your product live. (check all that apply)

Q67 Describe the age of the target end user for your product. (check all that apply) Q68 Describe the education level of your target end user for your product. (check all

that apply)

Q69 Describe the income level of your target end user for your product. (check all that apply)

Q61 Describe the target end user of your product.

Q62 What is your target end user’s knowledge level with respect to the content in your product?

Table 4.10. continued

Part V Questions

No. Question

Q49 What is the context of use for the product you described above? (Select all that apply.)

Q50 How will this product change your user’s life? Explain in 1-2 sentences. Q51 Why is that important to you? Explain in 1-2 sentences.

Q70 Describe your gender. Q71 Describe your ethnicity.

Q72 Describe the region you currently live. Q73 Describe your age.

Q74 Describe your education level. Q75 Describe your income level.

Q76 Describe your level of technical aptitude and favoritism towards technology. Q77 What is your knowledge level with respect to the content in your product? Q52 Will you use the end product you are making?

Q54 Are you similar to your end user?

Q55 How are you similar to the end user of your product?

4.12. Part VI: Process