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Bringing Quant to a Qual Party

Research Lead Rosalind Koff shares her strategies for mixing methods and a template to keep your projects on track.

Words by Stevie Watts, Visuals by Jarred Kolar

You may have heard the expression, “Anyone can ________.” Anyone can cook, anyone can dance, anyone can play guitar, you name it.

While not everyone can cook (sorry, mom), it is true that with the right coaching, anyone can do research.

Rosalind Koff, dscout Research Lead, is a standout research coach. Throughout her career, she's worked with clients such as the Centers for Disease Control and Prevention (CDC), the National Institutes of Health (NIH), the National Institute of Justice (NIJ) and the Associated Press.

But where her expertise really lies is in collaboration—working with researchers with non-traditional backgrounds and bringing them quickly, and meaningfully, "up-to-speed."

This is increasingly critical as more researchers find their way into the industry through non-traditional routes such as bootcamps, certifications, or department-switching. The variety of experiences not only brings new perspectives to project design and analysis—it enriches our understanding of the user.

We met with Rosalind to discuss her unique path to UX, what it’s like working at a qual research company with a quant background, and any advice for qual researchers looking to introduce more quant to their projects. Plus, she shares her calendar template for keeping projects on track and stakeholders in the loop.

What was your path "into" user research? How does that path shape or impact the work you do at dscout?

My journey into research actually started back when I was in undergrad at the University of Wisconsin-Madison. I was studying the impact of social media on older adolescents’ health and my work involved a lot of tagging Facebook profiles to reconcile against self-report data, and conducting/transcribing focus groups.

There was something about pulling the numbers from that project that really stuck with me. I remember sitting in my boss’s office watching her write syntax on SPSS and being awestruck. But it wasn’t until grad school at Georgetown that I finally learned SPSS syntax for myself and it was there that I discovered the beauty and power of mixing quant and qual data to tell a story.

After graduation, I joined the National Opinion Research Center (NORC) at the University of Chicago.

Research in general can be large and slow, so at an 80-year-old organization—that’s true tenfold. However, NORC saw an opportunity to innovate on traditional methods and decided to start a panel that was probability-based (sampled through scientific selection), and could be administered on both the phone and online.

This was a strategy that was super unique at the time—and I knew immediately that I was in. I transferred into that department and became one of the first members of the client services team helping clients conduct research with our panel, managing specialists across the project workflow, and completing projects from start to finish.

I absolutely loved it. Building a panel, caring for it, determining processes for working with it, and of course—data collection. In my six years there, I managed over 300 projects, and found a lot of joy in the social good of the work I was doing, but I missed tech...a lot. And I missed qual...a lot a lot.

And so the story goes, I met dscout. Here I could get back into researching the many aspects of tech, while expanding into so many other verticals including design and visualization. Being at dscout has challenged me in all the best ways to use the foundation of rigor and high quality research I was brought up in and apply it creatively to our purposes. And of course, the most exciting aspect was returning to qual while helping to build out my newfound team’s mixed methods skills.

As our resident quant aficionado, how has working for a qualitative platform like dscout affected your research?

It’s allowed me to learn a TON. In quant, we prioritize scale and representativeness over everything else. Working here I’ve come to realize just how valuable the ‘why’ is. Even a handful of folks can give you a better understanding of their thoughts, perceptions, and needs.

I also come from a world where research is extremely specialized. As in, entire teams of statisticians, programmers, data analysts, etc. There wasn’t a mix of people, they all had similar (if not the same) journey to their profession.

While there’s definitely a time and a place for that type of specialization, I’ve always hated the stigma of the in/out groups of research and narrowing who ‘can’ and cannot conduct research.

I feel so lucky to work somewhere that has a mix of classically trained researchers and those who found UX along the way. This is true for our customers as well. I love that dscout cares to empower anyone to get insight into their customers/services/experiences— that’s really, really cool.

I’ve also learned to be a lot less precious with my research. (Part of that has to do with the fact that I’m not always going after enormous samples that require scientific selection for sensitive topics or at-risk populations.)

But I do think it’s that dscout has helped me hold onto the rigor in the work that I do while simultaneously taking research off of that pedestal and realizing that we can always be learning, even if things go a lil awry.

What advice do you have for researchers looking to add quant to their qual (or vice-versa)? Is there a best practice based on your experience mixing methods and approaches?

Just do it! I think there's this assumption that adding quant means a lot of extra work, it really doesn’t have to be a stressor. It’s just important to realize that it's fine to not be an expert in all methods.

There’s no better way to try mixing and matching than to dip your toe in and get a feel for how various data sources can work together.

Every researcher knows that any good research just generates more questions to be answered, so having flexibility with methods can give space to those new leads.

Personally, I’m a big fan of running a survey first to get a lay of the land before adding in a qual component. It really helps to get a sense of why participants answered the way they did in the survey.

On the flip side, if you lead with some qual you can focus your survey a bit more so you are really making the most out of your data in it. Selfishly, there’s nothing I love more than IDIs because while unmoderated stuff is fast and effective, we’re all here because we love humans and there is A LOT to learn from talking to other humans.

You're also a workshop/readout pro: What’s one deliverable or shareout has resonated the most with a client, especially for the kinds of data dscout generates?

I feel like as researchers we are so lucky to be at the front lines with our participants. We have the opportunity to really get to know them and make sense of/advocate for their needs within these organizations. So my favorite moments are honestly when we get to share that with their broader teams.

Bringing back the point I made earlier on my love of getting non-card-carrying researchers involved, I really love sessions where we are able to get the raw-ish data into the hands of the group for a discussion. A few examples:

  • Giving the attendees of a shareout a handful of curated “scout profiles” where they can watch the video submissions, read a few entries, and contribute, really builds engagement and empathy for participants. It also helps with buy-in for the results of the overall work.
  • Taking findings from the research and making it interactive - I once did a work session for a project where a big finding was that the accuracy of hashtags they were using in their product was extremely poor. The client wanted their engineers involved in the research process and to help with their buy in, we did a fun quiz with the group where we showed them a hashtag and three pieces of content and they had to guess which piece of content was served with each hashtag

One additional tip, before you get to the workshop/readout room, you should be psyching up your audience! Make it part of your practice to update your team along the way—even while you are still in the field! Here’s a few ways how:

  • Make a quick highlights reel to share with the group to show introductory thoughts (even screener videos can make awesome fodder for this).
  • Share a quote of the week, each week, that varies from funny to thought provoking, and give others a sneak peak into what you might eventually share with them. Or do a featured scout each week! Who are they, what do they care about, what can we learn from them in this work?
  • Use Slack? Teams? Skype for Business? Create a space where folks can share out ways that they’ve reported out data for inspiration

Roz's calendar template

Staying organized on projects—from operations like recruitment to communications with stakeholders—is challenging any time, but especially in our hybrid reality.

I use a simple calendar template to keep folks organized, keep visibility with my stakeholders, and ensure that results are delivered on-time. It's helped me stay on top of all sorts of projects, for stakeholders around the world, while keeping my team focused and engaged.

Stevie Watts is the Copywriter at dscout. She enjoys telling compelling user research stories, growing social channels, and exploring all things video production. As a newer Chicagoan, you'll likely find her at a concert or walking her corgi, but undoubtedly heads down looking at Google Maps.

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