Beyond “warm impulses”

I’ve been catching up on the Museopunks podcast series, and a section of March’s installment, the Economics of Free, particularly caught my attention. In an interview, director of the Dallas Museum of Art, Maxwell L. Anderson compares the data that shopping malls collect about their customers to the relative paucity of data that is collected about visitors to the typical art museum. I think it’s worth repeating (from about 18min into the podcast):

[Malls] know all this basic information about their visitors. Then you go to an art museum. What do we know? How many warm impulses cross a threshold? That’s what we count! And then we’re done! And we have no idea what people are doing, once they come inside, what they’re experiencing, what they’re learning, what they’re leaving with, who they are, where they live, what interests and motivates them . . . so apart from that we’re doing great, you know. We’re like that mall that has no idea of sales per square foot, sales per customer. . . so we’re really not doing anything in respect to knowing our visitors. And learning about our visitors seems to me the most basic thing we can do after hanging the art. You know, you hang the art, and then you open the doors and all we have been doing is “hey look there are more people in the doors”.  And the Art Newspaper dedicates an annual ‘statistical porn’ edition of how many bodies crossed thresholds. Nobody’s asking how important the shows were, or what scholarly advances were realised as a function of them, or what people learned, how they affected grades in school. Nobody knows any of that. Nobody knows who the visitors were. So I consider it a baseline. We’re just at the primordial ooze of starting to understand what museums should be doing with this other part of our mission which is not the collection but the public.

I’d argue that we’re a little bit beyond the ‘primordial ooze’ stage of understanding*, although Anderson’s right in that many museums don’t go much beyond counting ‘warm impulses’ (those infra-red people counters). He goes on to describe how the DMA’s Friends program is giving the museum more data about what their visitors do while inside the museum, and how this can inform their engagement strategies (22:45):

This is just another form of research, you know . . . we do research on our collections without blinking an eye, we think nothing of it. We spend copious amounts of time sending curators overseas to look at archives to study works of art but we’ve never studied our visitors. The only time museums typically study their visitors is when they have a big show, and they’re outperforming their last three years, everybody’s excited, and there’s a fever, and you measure that moment, which is measuring a fever. The fever subsides, the data’s no longer relevant but that’s what you hold on to and point to as economic impact. And largely, it’s an illusion.

I find it interesting that Anderson puts visitor research on a par with collection-based research. Often, I get the sense that collection research is seen as ‘core’ museological business, but visitor research is only a ‘nice to have’ if there is the budget. But perhaps this is a sign of shifting priorities?

 

*Historically, most visitor experience research has taken place in science centres, children’s museums, zoos and aquariums rather than museums of fine art. Although there are of course exceptions.

IPOP Model of Visitor Preference

Most typologies of museum visitors tend to categorise visitors by demographics, motivation, or a mixture of both. The IPOP model, developed by Andrew Pekarik and colleagues at the Smithsonian Institution (Pekarik et al, 2014), is a little different in that it categorises visitors according to their preferred interests. Developed through years of research with visitors across the Smithsonian sites, the IPOP model is based on four key experience preferences:

  • Ideas – a liking for abstract concepts and facts
  • People – attraction to stories, emotional connections and social interaction
  • Objects – appreciation for objects, aesthetics and craftsmanship
  • Physical – attraction to sensory experiences, movement and physicality (this P was a later addition to the model as it evolved).

These are indicative of overall preferences rather than being absolute and mutually exclusive categories. Scores are based on responses to a self-administered questionnaire that is based on agreement to statements such as: I like to know how things are made, or I like to bring people together. The full version comprises 38 items, with shorter 20 and 8 item versions also used. Using responses to these statements, 79% of visitors show a clear preference for one of the IPOP dimensions: 18% Idea, 18% People, 19% Object, 23% Physical. The remaining 21% tend to show a combination of two dimensions (rarely three) rather than a single clear preference*.

By combining self-report IPOP preferences with tracking and timing data, Pekarik and his team have shown that it is possible to predict what exhibits a given visitor will attend to (or indeed, which exhibits they will avoid) based on their IPOP preference. People tend to seek out experiences that suit their preferences and match their expectations. When people see what they expect, they report being satisfied with their experience. However, sometimes visitors are engaged by something unexpected and different from their usual preferences. This phenomenon, described by the authors as “flipping”, can lead to more memorable and meaningful experiences.

The exhibition Pekarik et al (2014) use to illustrate the predictive value of IPOP is Against All Odds, an exhibition at the National Museum of Natural History about the rescue of trapped Chilean miners in 2010. I happened to see this exhibition on my 2012 study tour of Washington DC, and while I recall seeing it, I don’t have any specific memories of it (a consequence of breezing through dozens of exhibitions for days on end). Although I was amused to observe that the two photos I took of the exhibition are very similar to those in the Curator article!

SI-NMNH Chilean miners exhibit
My photo of the entrance / introductory graphic
SI-NMNH Chilean miners exhibit 2
The rescue capsule. The image in the Curator article takes a wider view which encompasses a tactile drill bit on the left and a video on the right. The rescue capsule was the largest and most distinctive object in the display. Whether that is why I photographed it as a way of recording the exhibition, or whether this says something about my IPOP preference I’m not sure.

I’m not sure what to make of this. Either I intuitively grasped which views best encapsulated the exhibition, or I have the same IPOP preference as the person who selected the images. . .

UPDATE 2/5/2014: I’ve just found out that the Pekarik et al article is available online for free. Happy reading!

*Interestingly, the research team categorised themselves according to the IPOP typology and found they had preferences in three of the four dimensions (none of the team was a People person). It strikes me as an interesting exercise for exhibition development teams to conduct at the outset of the project, giving individuals an insight into their own preferences as well as an appreciation of those of their differently-preferenced colleagues – there is more on this point in Pekarik and Mogel (2010).

References

Pekarik, A., & Mogel, B. (2010). Ideas, Objects, or People? A Smithsonian Exhibition Team Views Visitors Anew. Curator: The Museum Journal, 53(4), 465–482. doi:10.1111/j.2151-6952.2010.00047.x

Pekarik, A., Schreiber, J. B., Hanemann, N., Richmond, K., & Mogel, B. (2014). IPOP: A Theory of Experience Preference. Curator: The Museum Journal, 57(1), 5–27. doi:10.1111/cura.12048