Understanding how to collect data and knowing what to use it for are essential for our field. Today readers will hear more about these best practices from three women who work with data in museums. We welcome: Angie Judge, founding director of museum analytics provider at Dexbit; Dacia Massengill, Washington based digital strategist for museums and the cultural sector. She is also the creator of the Arts Analytics Group ; and Elena Villaespesa , digital analyst at The Metropolitan Museum of Art by day, PhD student at the School of Museum Studies, University of Leicester by night. Elena blogs about her research in arts & metrics.
The meteoric rise of data is now estimated at 2.5 quintillion bytes daily, 90% less than 2 years old. Bringing information, analytics and sentiment, data is unsurprisingly positioning centrally to the mission of museums globally. With technology, data’s role is increasingly predictive rather than reactive. Beyond dealing purely in cultural history, does that mean data can now provide a pathway to the museum’s future?
This upsurge has fuelled predictions on how data will inform museum practice, explored by the Center for the Future of Museums, concepts now on their way to real life. It is a mind boggling world of dashboards and machine learning, loyalty and personalization, linked open data and data journalism: 2016 it seems, is the year of ‘musedata’. As it draws closer, we take a look at the opportunities, challenges and pathways the new year brings.
Big data, big opportunities
For some museums, the origin of analytics occurs organically from the data opportunities inherent in balancing access with preservation. Data can combine the visitor’s physical gallery pathway with the digital touchpoints that complete their omnichannel experience: web, app, social, ticketing and more. At New York’s Cooper Hewitt, data on how visitors interact with collections arose naturally from The Pen, an interactive digital device that allows visitors online access to their favorite objects post visit. For others, analytics is an intentional introduction to museum management on its own business case. Take the Victoria and Albert Museum in London, for example, where the results of split testing on website behaviour serve to enhance experience. Whether data’s presence precedes the demand from decisions or vice versa, the value equation remains the same: insight. Museums worldwide are beginning to discover the possibilities in patterns. Aggregated, this can be useful in informing digital production, tweaking marketing campaigns or adjusting wayfinding. At an individual visitor level, the opportunities are even greater. “We see three benefit pillars in pursuing musedata,” says Angie Judge, founder of Dexibit, museum analytics provider, “reporting efficiency, investment optimization and personalization opportunity”. Great news in a sector constantly challenged to do more with less.
Data literacy changes things
Whilst the museum is no stranger to audience research, analytics represents challenging new territory. This trend might be commonplace in sectors such as retail, but for museums, there’s a journey ahead to achieve widespread analytics adoption. Often, this transformation starts with specific resources dedicated to this task and an increase of data literacy. Lack of resources is a common barrier, however many museums are creating analyst roles or including responsibilities for various departments. For data to make an impact, Elena Villaespesa, digital analyst at The Metropolitan Museum of Art in New York, is an advocate for prioritizing cultural change with a focus on communicating insights and a framework for evaluation to ensure findings result in outcomes. At the Met, Villaespesa is designing a dashboard for data stories. “By displaying data centrally, we can monitor trends and compare initiative results with context.” Villaespesa said. “The main objective of having a dashboard is to communicate the impact of our digital initiatives and to be able to make decisions in an effective and rapid way.”
An open future
To avoid the risk of analytics becoming solely internal, it’s important for museums to realize the ultimate value in exposing data publicly. One recent example of this is Carnegie Museums of Pittsburgh’s digital metrics dashboard, which displays analytics across five properties and ‘attempts to visualize connections between digital and physical activity’. Another is the Museum of Contemporary Art Chicago’s Facts and Figures, which presents visualizations for the most popular days, the number of free tours, even a call for visitor feedback on data they would like represented. Transparency helps visitors understand the role data plays in culture, and together with added visitor value, develops underlying trust. While museums determine compliant policy on individual privacy, sharing summative data at a higher level within the sector can advance the cultural cause. “Sharing data can – and should – be a tool in which museums can work together to better determine how to provide the best content for both online and offline audiences” says Dacia Massengill, digital strategist for museums and the cultural sector.
How can musedata guide the future of museums and encourage inclusion? Indoor positioning, dashboards and linked open collection data are just a few of the ways museums are starting to use data for the greater good. 2016 might be the year of musedata, but it will be a gathering at the starting line rather than a sprint to the finish.
What are your predictions on how musedata will shape our cultural future? Comment below, join the Arts Analytics Group on Facebook or tweet #musedata.
One thought on “Predicting our Cultural Future: Is 2016 the year of musedata?”
I agree that museums can make better use of more data. If 2016 is the year for museum data, then I hope that my new book Measuring Museum Impact and Performance: Theory and Practice, being published by Rowman and Littlefield this spring, will add to the tide.
The book lays out the theory for how to evaluate the impact and performance of museums and then how any museum can use that theory to select its prioritized desired impacts and then use operating and community data to measure changes in the museum's selected key performance indicators (KPIs), checking KPI validity periodically by using other evaluation methodologies.
The bloggers' suggestions are good. but require some missing steps: Museum managers need to see direct benefits from using data; they need a rationale for how to use data to show evidence of their value and impact, and museums need to standardize data field definitions before any meaningful sharing can occur. There are initiatives afoot to address these issues, and this CFM blog and my book are among the solutions — thanks!
John W. Jacobsen