The Art Institute of Chicago is known for its visual masterpieces. But for the past few years, it has developed expertise in another area: data. Analysts collect data on who visits the museum and how those visitors navigate the institution. Then they use that information to advise the marketing team.
For example, the museum measures “dwell time” — the length of time people spend in different exhibits. When guests connect to the museum’s Wi-Fi using their phones, the museum can track their paths through the building and create a “heat map” of aggregated movement patterns, “without investing in the human capital of counting heads,” says Amanda Hicks, executive director of public affairs.
When an Edgar Degas painting on loan from the National Gallery of Art went on display, the staff noticed an 18 percent increase in the number of people moving through its gallery. The visitors were staying in the room housing the Degas painting for nearly double the amount of time as usual for that room.
“People are clearly having a strong connection to what’s happening in this space,” Ms. Hicks says.
So the museum increased its promotion of the Degas installation and enhanced signage to direct people to the popular work of art.
Another effort collects patrons’ ZIP codes. During point-of-sale transactions for tickets, for example, the museum collects guests’ ZIP codes to understand which regions visitors call home and whether they behave differently than do people from other regions.
That came in handy in 2014, after the museum was named No. 1 in the world by TripAdvisor. Using ZIP code data, employees saw an uptick in attendance among locals who seemed likely to have heard of the honor. So the marketing team shifted its approach and spent more of its budget to advertise the announcement to all of its audiences, hoping for a similar increase from other groups of people. The publicity effort helped the museum earn $1.8 million more in attendance revenue than expected in 2015.
Andy Simnick, vice president of finance and strategy, and Matthew Norris, executive director of analytics, oversee the data collection. Mr. Simnick has a background in engineering and management consulting, while Mr. Norris studied computer science and finance and previously served in the museum’s IT department.
“Curators think about one artwork at a time,” Mr. Norris says, but with data sets, “you can look at those pieces in a group and gain new insight.”
Although not every nonprofit can match the resources of the Art Institute, certain principles can benefit almost all charities, Mr. Simnick and Mr. Norris say. Here are three tips they offer on how to use data to advance your goals.
1. Pick the right questions.
The keys to using data are identifying which questions are most important for your organization to answer and deciding which analyses and tools will help you answer those questions. The institute wanted to know who its visitors were and how they traversed the museum, and it wanted to collect that information without relying on staff members to stand in each room and count them.
2. Use the information you have.
“Not everyone has a state-of-the-art central database,” Mr. Simnick says, “but every organization has information.”
And if your information can get you 90 percent of the way there, “you’ve got to do that,” Mr. Norris says. “Don’t let the perfect be the enemy of the good. Good information is much more valuable than being forced to make a decision without any information.”
To get that information, you’ll need to talk to co-workers who are experts in the subjects you’re studying. When Mr. Norris meets with a department for the first time, staff members are typically resistant, he says. But he makes sure to convey that the information he’s seeking “isn’t to judge them, but to help them.” Once they understand, he says, people are “interested in what analytics could do to help.”
3. Know your audience.
When presenting findings to your co-workers, it helps to know how they prefer to take in new information. At the museum, many staff members have strong visual skills but lack extensive training in math, Mr. Simnick and Mr. Norris say. So they use data visualization tools to create presentations that explain their findings in ways that appeal to their colleagues.
