Web Analytics for Digital Collections: Appraising Collections and Assessing Impact
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This document discusses web analytics for digitized content collections. It provides an overview of the Created Content Committee which works to develop digital resources. The committee reports quarterly statistics on 167 collections from 32 institutions hosted on CONTENTdm. The document then outlines how to analyze the analytics data to understand what content is popular, where traffic comes from, any anomalies, and how to measure marketing success in order to improve efforts.
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Web Analytics for Digital Collections: Appraising Collections and Assessing Impact
- 1. Web Analytics in the Created Content Committee Adam Strom, Newberry Library Margaret Heller, Loyola University Chicago Paul Go, IIT
- 2. About the Created Content Committee • The CCC works with CARLI staff and members to identify, develop, and encourage cooperation and collaboration to foster the creation, management, and access to digital resources. • The CARLI CONTENTdm collections include digital images and accompanying metadata from 32 different institutions, totalling 167 collections in all • The CCC reports statistics on these collections quarterly
- 3. Report on sources of traffic • Google Analytics (CARLI provides spreadsheet) • Excel • OpenRefine (optional but faster and easier) • Reports
- 4. Transforming the data • Deciding what stories to tell • Finding new interpretations of the data
- 8. Beyond the Numbers: Digging into Data • Determining popular items • Discovering sources of traffic • Analyzing anomalies • Marketing success
- 9. What content is popular • Common search terms and types • Specifically relevant keywords for your collection
- 10. What drives traffic • What sites are sending users to the collection? • What types of sites tend to recur? • Are there new sources of traffic that can be identified for promotional efforts?
- 11. Anomalies • Are there spikes in traffic? • What are they generated by or tied to?
- 12. Marketing success • Matching traffic patterns with marketing efforts • Were certain campaigns or types of images better at driving traffic • Once on the landing page did the users explore other things on that site? Other collections? • Who are we reaching with our marketing?
- 13. Making Use of the Data Analysis of efforts and identifying areas of improvement
- 14. • Are these what we expected? • Are themes coming up? How might we apply these to existing collections to improve discoverability? • What implications are there for the metadata? Search terms used
- 15. Traffic Generation Now that we can see where traffic is coming from we can ask: • How can we use social media to better drive traffic? • What other channels exist to drive traffic? • What can we do to improve existing channels?
- 16. Moving forward
Editor's Notes
- Each quarter, we report on the sources that bring web traffic to the collections and the keywords that searchers use to discover these images Reports work by getting the data out of Google Analytics into a spreadsheet and reorganizing to meet our needs. This is edited in Excel and OpenRefine to get at the patterns we want. Google Analytics provides a ton of ways to look at data, but if you want to be very selective in your manipulation it will be faster to download into Excel. This also allows you (and in this case, CARLI) to share usage data with others without giving them access to your GA interface.
- How we decide what to look for and what stories the data tell. We report the numbers, but attempt to look deeper into the highest ranked keyword searches and traffic sources to identify trends and analyze not just what how users are finding our content, but what we can learn and communicate to CARLI members to encourage more traffic across all of the collections For instance, for traffic sources report, we delete search engine traffic, and generally anything with CARLI, Wikipedia, Facebook, or Flickr in the traffic URL, as well as CARLI institutions. We then look at which sources drive traffic to multiple collections, vs. which collections were most popular with a variety of sources. Report for top keywords and top traffic sources are compiled quarterly, which is often enough that there’s not a huge difference each report. Even when the top ranked sources and searches are stable, we attempt to think of new ways to look at the data, and new things to pass along to CARLI members For instance, this last quarter we experimented with including Wikipedia as a traffic source and discovered that it was driving traffic completely separate from internal promotion efforts.
- This is what Google Analytics looks like--creates many charts and graphs, but you have to figure out what you want to get out of it.
- Data downloaded into Excel.
- OpenRefine example. This is a tool that allows you to transform data very quickly and easily. This is what the the text ends up looking like.