Understanding Museum Website Visitor Motivation using Google Analytics
This post is a collaboration between Sarah Wambold and Marty Spellerberg. Sarah Wambold is a Denver-based project manager and documentary producer. Marty Spellerberg is an Austin-based interactive media developer.
Google Analytics is a powerful tool for understanding traffic to a website. The standard site statistics, however, don’t always tell the full story.
For instance, interpreting the duration of an average site visit is highly speculative. It is typically thought that the longer a visitor spends on the site the better, and that shorter interactions are less successful. But this is not necessarily the case.
Take a visitor who comes to the site looking for the museum’s hours. If she was able to quickly and efficiently locate the information she needed, this interaction should be considered positive, despite the short visit duration. Conversely, if she was unable to find the information and had to search for a longer amount of time to find the information, the long duration would signal that the interaction had been considerably less successful in this instance.
A combination of survey techniques is necessary to overcome this reporting challenge and understand the successes, shortcomings, and opportunities of a Museum’s website.
Augmenting the Standard Stats
Working with the Museum of Contemporary Art Chicago, we wanted to increase our insight into how the site was being used. We knew that, in order to analyze current and inform future online offerings, we needed to be able to identify which kinds of users were accessing the site. Are there, in fact, different motivations for visitors to come to the MCA’s site? If so, how do those groups differ in their use of the site? To gain this information, we conducted a Visitor Motivation Survey.
We modeled our survey after a study by the Indianapolis Museum of Art. We placed a one-question survey on the homepage, asking visitors to the site to self-identify into one of five user groups based on why they were visiting the site that day. Assuming IMA’s methodology, the choices we presented were:
- Plan a visit to the museum
- Find specific information for research or professional purpose
- Find specific information for personal interest
- Engage in casual browsing, without looking for something specific
- Make a transaction on the website
The visitor’s choice was synced with Google Analytics, using a custom variable to tie it to the record of their browsing session. This allowed us to model activity across the site, segmented by motivational category.
Comparing Engagement Levels
By requiring participants to interact by answering the survey question, we could infer a minimal level of engagement with the site. We segmented this group of “engaged visitors” from those users who may have found themselves on the site erroneously. Comparing these samples allowed for a more informed analysis of site traffic overall.
The survey launched on Nov 4, 2013, and collected responses for 16 weeks, receiving 1,086 responses in total. A report based on the first eight weeks yielded revealing insights into the MCA’s online audiences.
Analysis of the survey data identified which motivation groups are most likely to return to the site, and the content these types of users are seeking to engage with. The Museum is now able to apply this information in a strategic content plan aimed at generating increased repeat visitation and overall site traffic.
Producer and Project Manager: Sarah Wambold
Designer and Developer: Marty Spellerberg
Shoutout/thanks to Gray Bowman for sharing code from the IMA’s implementation.
Posted June 2014