
I created a "print" version of the document after hearing the executives and leadership are more likely to print and read, and some will read in "lean back mode". Simultaneously I was working with our internal Tools and Security team to establish where I could create an internal research site accessible to everyone in the organization. I planned to make research accessible with an information site organized by topic, not a repository of reports.

I worked closely with my VP to craft an impactful summary. I wanted to emphasize Divergent vs Convergent research and what would come next.

The Analysis included looking at the results from a business perspective - starting with my target audiences' mental models. After the general background, approach, and methods section I presented the first of the analysis - the representation of the business and results.


Since we had people in the organization insisting that gender determines laundry behavior, I looked at the data from a gender perspective and showed a comparison between female and Male responses for both laundry and technology themes. No notable statistical differences. This is also an example of demonstrating the range of results with frequency. In the end, regardless of gender, everyone does laundry, knowledge, and attitudes about it are relevant with a 5% Margin of Error. Whenever I use a weighted Likert scale I like to include an opportunity to express themselves via "Comments". I analyzed the comments and used the quotes in reporting and personas.

I drafted proto-personas from the results and used them to present the variations in results in a meaningful, and rememberable manner. I also used two of the six profiles to teach the organization to look at results with greater complexity than just averages for each question.

It was important to include senior profiles because of an assumption that seniors are tech-phobic and not tech-savvy. Although confidence levels are slightly lower, they are not dominating the lower range. There are those seniors who are less confident- and people within each age group, it is a smaller part of our population. I noted seniors have support from different groups including family, AARP, SSA, etc. that make efforts to educate and support their use. In previous studies, I have seen greater awareness of tech security among seniors than younger generations.

There was a prevalent assumption that accounts/people with higher incomes are more open to technology and more technically savvy. This is combined with the assumption that one account represents one person. I explored these assumptions and found that our accounts represented households with a range of members. This gives a different perspective of income. I also gathered sources of income such as set income - retired, set-income gov assistance, full-time employed, number of people employed, etc. so we understand what this income means. This immediately influenced the analysis of pricing and the question of how much can we increase prices without impacting usage. I started to work with Finance in complementary analysis/studies.

With any business, we have goals to increase engagement. Beginning to understand personal laundry with self-reported triggers.

With any business, we have goals to increase engagement. Beginning to understand personal laundry with self-reported use of options and the potential for increasing engagement.

Understanding the laundry experience includes the variations in the emotional experience. This finding began to reveal insights into increasing internal empathy and increasing engagement.

The finding that had an immediate impact on product roadmaps was the finding that accounts are shared. This survey also began to explore laundry roles and needs including managing funds, needing to guide children in doing laundry, and the need for multiple users at one time.

A sample of the quantitative personas I eventually produced with iterative updates from quantitative and qualitative studies. I used the foundational proto-personas to create survey questions I repeated with all surveys and interviews to allow for meta-analysis across studies. Because the personas started with this efforts smaller "proto-personas" the organization was able to learn how to use them with smaller sets of data, get to know the personas, and slowly expand their understanding and depth of usage.
I used gender-neutral names, avoided pronouns, used signatures rather than photos, and selected names from across the world to reduce the likelihood of personal bias towards people and cultures to influence use.