Digging For Generative Data To Ideate

Skills: Affinity Mapping, Empathy Mapping, Ideation
Tools: Miro, Google Meet, Pens, Sticky Notes

The Story So Far

My partner, Carson Stanch, and I won a bid to create Queerbomb Austin’s first website. This was our first project outside of the classroom, and I learned how to advocate for research as a tool for connecting to users and creating great products.

Finding Our Generative Data

Because Queerbomb did not allocate for generative research I was unsure of what to use as our baseline to begin empathizing with users. Our stakeholders offhandedly mentioned that they had recently sent out a Queerbomb satisfaction survey to current and former members of Queerbomb as well as those who have attended Queerbomb. I was thrilled to hear this and asked if we could have access to this qualitative data.

Our stakeholders were uncertain at first because they felt the responses were skewed in a negative light and contained some personal information.

“I don’t want to even talk about [the survey data] because it is so negative.”
-Stakeholder 1

We were able to convince them that the data would be fully confidential, and that we would analyse the data to assist in our design process, not to judge their organization.

Analysis and Synthesis

After some convincing they gave us the data, and we immediately jumped into data visualization. We added every response to a sticky note, and then created an affinity map of like responses. With the structure of the affinity map, we created How Might We questions for each cluster to help us ideate with intention.

Affinity Map with How Might We Questions

From the affinity map, we created an empathy map to build bridges between us and our users. We found that our users were most concerned with building community, accessibility of the main Queerbomb event and an emphasis on inclusion of BIPOC voices in the Queerbomb universe.

Key Focus Found from the Emapthy Map

We followed up with a prioritization grid to determine what aspects are most important for testing. This influenced our ideation because we wanted to prioritize our energies to the key aspects of the site. We determined that the donation flow and volunteer sign up flow would be our focus because of our stakeholders’ explicit expectation that the site would bring in more donations and volunteers.

Prioritizaiton Grid To Focus Our Testing


Ideation

With our focus on the donation and volunteer sections we did one round of crazy eights for each topic as well as a round of SCAMPER each to create a lot of diverging ideas. These ideas were the infrastructure for my partner to begin the prototyping process for the website. The following images are some of the highlights from our ideation sessions that are discussed more in the case study User Testing with No Budget.

Highlights from our ideation sessions.


Reality Check

I did assumption mapping to cover our bases around what I believed regarding this site. Due to the lack of generative research we had to assume that creating a donation button and a volunteer sign up flow would increase donations and volunteers. This is something I wished I could have tested. It could have potentially saved the organization a lot of money and time if I could have learned about how LGBTQIA+ folx donate their money and their time in Austin.

Takeaways

  • Imperfect generative data is better than no data. If I had not advocated for the survey data we would have missed an important opportunity to connect with our users and discover what their needs were. Our ideation time was more focused and connected to the thoughts, feelings and experiences of our users.
  • While I was bummed to not complete generative research, having some data at our disposal helped us connect to our users and make a better product.
  • I will continue to advocate for the needs of the user in future projects, even when the budget prohibits me from fully exploring generative research.