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Smithsonian Learning Lab User Search: Digital Analytics Report
Location
Pratt Institute School of Information, New York City
Date
Spring 2022
Class
INFO - 685 Digital Analytics
Project Description
The Smithsonian Learning Lab is a free platform for exploring millions of digital resources held by Smithsonian museums, creating interactive learning resources, and sharing discoveries and creations with others. Faced with the increasing number of users and collections, the Lab wants to understand how users interact with the platform’s primary feature: search. Our research focuses on two guiding questions: how are users using the Smithsonian Learning Lab’s search, and are users finding the content they’re looking for?
Findings, based on data pulled from Google Analytics, are grouped into two areas: search behavior and search results.
Methods
To better understand how users are utilizing the Smithsonian Learning Lab website, the client has provided a plethora of data from Google Analytics for the Pratt team to analyze. The analysis spans from January 1, 2020 to April 1, 2022, to thoroughly analyze trends in website usage.
Using data collected from Google Analytics, aggregation, analysis, and visualization were performed using Google Sheets, Microsoft Excel, Google Data Studio, and Tableau. Our analysis utilizes the following metrics: users, source, page views, unique pageviews, exit pages, session duration, landing pages, sessions with search, unique searches, time after search, average search depth, search terms, search filters, search refinements, and search exits. Our analysis also filters out users who fall within the “spam” segment, as defined by the Lab team, in order to remove outlier data.
To support the Lab in moving forward from this report, the Pratt team developed an adaptable dashboard in Google Data Studio. The dashboard displays real-time insights on Lab search behavior on a quarterly basis and can be manipulated to show data from a specific time period.
My Role
This was a group project to collaboratively analyze the search function for the Smithsonian Learning Lab. All methods and overall analyses were done together as a group as the findings and construction of the project were collaborative but separately written. My specific written additions include the findings for sections 5.1.4 Ethnographic Analysis of Search Tool Users including user countries and language use. The recommendations I had specific written additions and ideologies behind include 6.1.4 Make Search Refinement Easier, 6.2.2 Connecting Collection Keywords, 6.2.4 Call For Smithsonian Created Collections, 6.2.3 Encouraging Exploration, and 6.2.6 Improving Language and Accessibility.
Learning Outcome Achieved
Digital Technology and Tools
Rationale
In order to appease our client, the Smithsonian Learning Lab, I was required to perform successful digital analytics to provide findings and recommendations for the user searchability of the website and collections. By analyzing search behavior and search results, we aimed to understand our user's perspectives through their exploratory or results-driven methods of search. The digital tools Google Analytics, Google Sheets, and Microsoft Excel had been in practice all semester in order to gain a deep understanding of who the users are and how they behave, thus requiring event tracking and word searching, as well as audience segmentation. After the data was gathered, it was necessary to create visualizations using Google Data Studio and Tableau that would support our recommendations for digital architecture to match the user experience, whether the user be a visitor, educator, collection builder, or museum worker. After completing this project, I am completely prepared to run digital analysis and provide recommendations with accurate visualizations to provide for a client.
