Innovative audience research method gives voice to museum visitors
How often have you come across a kiosk with a row of colourful smiley faces paired with the question “how would you rate your experience today”? Whilst this method of evaluating subjective experiences has become standard, it offers little in analytical substance. We don’t know why someone has given a positive or negative rating — which is critical to address issues and take corrective actions.
We need strong insights to act. The traditional method for collecting detailed feedback involves a long or complex survey which has a high user drop-off. Therefore, there is a need for more engaging data capture tools; these tools are also critical to support stronger AI models which rely on meaningful, high-quality data.
Enter muse, an innovative feedback tool created to enable museums to understand their visitors better. muse has been co-developed by Deakin University’s Applied Artificial Intelligence Institute (A2I2) along with staff at the Laboratory for Experimental Museology (eM+), École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland.
muse differs from traditional surveys in that it is designed to engage visitors whilst passing through an exhibition. This means people record their experiences in real time, offering richer insights for museum operators.
The tool provides museum visitors with an engaging tablet app through which qualitative, subjective data is securely recorded. The app uses up to thirty interactive elements through which an audience can provide feedback. This level of data capture with a high completion rate has previously been unavailable to museums.
muse is multilingual, a feature usually not usually offered in this type of technology. Visitors are encouraged to take photos of their favourite parts of an exhibition, provide voice recordings with feedback, and even interact with animated graphics. This and other data are converted into quantitative insights that are elegantly presented in displays within the museum space to showcase visitor voices. Data is also presented in a central analysis tool, providing an analytical foundation for museum operators to better craft visitor experiences, and feeds directly back into strategy and reporting.
The system is currently in its second phase, expanding initial trials within eight museums based in Switzerland to twenty-four throughout 2021. This project is made possible by Migros Pioneer Fund and is supported by EPFL.
For more information on this project please visit: https://muse.stream/en/
To learn about the Laboratory for Experimental Museology (eM+) please visit: https://www.epfl.ch/labs/emplus/