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Internship Spotlight: Harmon Pardoe ’26, American Folk Art Museum

Harmon Pardoe ’26 spent the summer designing a survey and analyzing complex data to help a New York City museum understand its audience and improve its offerings.

A person giving a presentation in a small conference room

Internship company name and location: American Folk Art Museum, New York City
Hometown: New York City
Pronouns: he/him/his
The SOM class you’re using on the job: Generative AI and Social Media
Go-to work lunch: Salmon bento box
After-work routine: Walk the dogs and go for a run
Favorite thing about internship city: I love New York because it’s where I grew up, but getting to rediscover it in the context of a museum I’m learning about, in a part of the city I wasn’t familiar with, is an amazing experience that adds depth to the work I’m doing.

I came to the American Folk Art Museum (AFAM) at an interesting juncture in its history and future. The AFAM is a museum of folk and self-taught art, in all the multiplicities that category contains. Ahead of its 250th anniversary in 2026, the institution is grappling with notions of what it means to be a museum of specifically American folk art. Additionally, the actual museum space was closed for the summer for renovations, allowing for a period of reflection and self-assessment on the part of museum staff.

To that end, AFAM wants to understand better its audience: who are they, what motivates them, and what are they looking for in a small museum with a long history of punching above its weight. My work for AFAM centered on those exact questions, and included deep dives into all the organization’s existing data, as well as a major survey project to help fill in gaps in our understanding.

The museum’s existing data sources were diverse but superficial. I had the opportunity to explore past surveys, Mailchimp data, Google reviews, website analytics, social media interaction, and other online engagement to answer vital questions about the audience, including their age, location, and gender. I also had access to more quantitative data, such as program and performance reviews. To put it succinctly, the museum’s audience skewed older, female, hyper-local to the Upper West Side; most patrons have very positive feelings toward the museum. In some respects, this is great news: a stable, loyal base is good for longevity. But the museum is a national hub for folk art, which means it must work to attract a national audience. To go one step further, if the museum is concerned about maintaining its relevance as time goes on, it would help to understand its small but committed youth audience. These were all questions I wanted to answer in analyzing existing data and designing the audience survey.

My biggest challenge in parsing the existing data was that the datasets were often unorganized or irreconcilable with each other. Leaning on the tools I learned to use in the SOM course Generative AI and Social Media, I wrote Python scripts to help clean, organize, and graph data. This saved me hours of toiling in Excel and allowed me to have in-depth conversations with my supervisors to direct my work even further.

Designing the survey was more a matter of good old-fashioned academic research on the best practices of survey design, mixed in with some segmentation, which I had learned in the first-year core course Customer. I consulted previous museum surveys to help create questions along behavioral (what do people do?), attitudinal (why do they do it?), and demographic (who are these people anyway?) lines. I also used conditional logic in the survey to create segments based on museum engagement. Our segments considered whether the audience engages with the museum at all, and if they do so in person, online, or some mix of the two. This gave us four segments (in-person, mixed, online, disengaged), from which we might be able to understand the preferences of those who visit the museum and those who have yet to do so. While the survey analysis of the data is still in process, I expect that it will back up a lot of what we already know and shed further light on how AFAM can serve its audience in a dynamic, thoughtful way that maximizes accessibility and community.

My end-of-summer presentation to the director of the museum was an opportunity to lay out the entirety of the work I had done, and to do real thinking about the future of the museum with those making the decisions. I was also offered the opportunity to share my research with the museum board and staff, hammering home the comprehensive nature of what I was able to accomplish this summer.

Having spent a good deal of time on the design side of museums as part of the art consulting firm Global Cultural Asset Management (GCAM)—coincidentally run by SOM alum Thomas Krens ’84—I was very eager to work in a museum environment and understand how different parts work together. AFAM is a small museum of around 30 full-time employees, and most employees are involved in several facets of the organization, regardless of their individual role. It was helpful to think about how my work on audience could reveal simple but critical insights that impact different departments and give them the tools to improve the museum as a whole.

On a larger scale, I want to work to make museums more financially sustainable, and therefore more accessible to the public. This audience survey project helped me think about how we can accomplish that ambitious goal. After all, no two museum visitors are identical, and their motivations vary. This is a simple conclusion, but I only truly comprehended it after reading 540 survey responses. If we want to build museums that people want to go to, and museums that want to serve their people, we must ground our accessibility strategy in a thorough understanding of the audience.

Learn about Harmon’s other summer internship with New Haven art space 63 Audobon.