Using digital analytics to assess the real world
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2016 LITA Forum presentation on using digital data to evaluate library services.
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Using digital analytics to assess the real world
- 1. Using Digital Analytics to Assess the Real World Tabatha Farney Director of Web Services & Emerging Tech University of Colorado Colorado Springs @sharebrarian | tfarney@uccs.edu
- 2. What is digital analytics? The analysis of digital data from your online presence.
- 3. Defining the Online Presence Library Websites Search Tools Electronic Resources Social Media Email brick and mortar online
- 4. “Goal,” Blue Diamond Gallery, http://www.thebluediamondgallery.com/scrabble/images/goal.jpg
- 5. The tools There isn’t one tool to rule them all.
- 6. Digital analytics features include: • Campaign URLs • Measurement Protocol • Custom metrics and dimensions • Uploading data sets
- 8. • Free • Combines data from Google Analytics, Google Spreadsheets, and other data sources • Sharable and easy to update • Limited to 5 reports • Difficult to integrate data sources in one chart • Beta and bugs
- 9. “Link Humans,” Flickr, https://www.flickr.com/photos/linkhumans/17362908918
- 10. Digital Analytics for Library Staffing “Collaboration Space,” Kraemer Family Library, University of Colorado Colorado Springs, https://www.flickr.com/photos/27640054@N08/26253986013
- 11. Focus on the reference desk “Reference Desk,” Kraemer Family Library, University of Colorado Colorado Springs, https://www.flickr.com/photos/27640054@N08/with/18275542498/
- 12. Content
- 13. Websites • Library website Filters • Hour • Staffed vs Non- staffed hours Metrics • Sessions • Pageviews • Content groups • User actions Data
- 14. GA Customizations Event Tracking • Used Google Tag Manager • Track outbound links, downloads, emails, searches, form submissions, chat Content Groups • Admin feature • Categorized content in large groups
- 15. Report
- 16. 1. Wasn’t a significant change in content usage between staffed and non-staffed hours 2. Repeat analysis in search tools
- 17. Digital Analytics for Assessing Instruction
- 18. Websites • LibGuides (online guides) Filters • Pagetitle • Guide Title Metrics • Sessions • Users • Returning Users • Pageviews • User actions • Search terms • Outbound links • User rating • User comments Data
- 19. GA Customizations Event Tracking • Used Google Tag Manager • Track outbound links, searches, form submissions Google Forms • Import data into GDS • Averaged user rating metric
- 20. Report
- 21. Results • Guide editors love the data • Want instruction date metric and quiz data “Mario’s Flag,” Banjo2015, Deviant Art, http://img11.deviantart.net/cb81/i/2015/319/7/d/mario_s_flag_by_banjo2015-d9gr95f.png
- 23. Websites • Library website • Discovery service • LibGuides • Catalog Filters • Electronic resource clicks Metrics • Sessions • Users • Click-through rate • Cost per click • Electronic resource clicks Data
- 24. GA Customizations Event Tracking • Yes, again… Calculated metrics • Click-through rate • Cost per click
- 25. Report
- 26. Limitations Treats all clicks the same “Doh,” QuotesGram, https://quotesgram.com/homer-simpson-quotes-doh/
- 27. Results Greater emphasis on discovery service and website “Woohoo,” Clipart Panda, http://www.clipartpanda.com/categories/simpson-clip-art
- 29. Marketing Goal: Understanding the most effective means of marketing library programs Data • Campaign URLs for all marketing links (social media, emails, digital signage) • Library program metadata • User Feedback (online form)
- 30. Collection Development • Failed search data • Search queries • Coding the data “Library books,” CCAC North Library, Flickr, https://www.flickr.com/photos/ccacnorthlib/4131076475
- 31. Additional Resources • Farney, Tabatha. “Google Analytics and Google Tag Manager,” Library Technology Reports. 52.7 (October 2016). • Google Analytics Academy, https://analyticsacademy.withgoogle.com/ • Kaushik, Avinash, Occam’s Razor, http://www.kaushik.net/avinash/
Hinweis der Redaktion
- So what do I mean by digital analytics? Evolution of web analytics that focuses on website analysis. DA includes tracking usage from any online content.
- This requires us to really understand the library’s online presence.
- However, DA is not just about analyzing data for data sake. With all those data sets, you really need to approach DA with a goal or intended outcome. What do you want to know from the data? In the corporate world, digital analytics is tied into the business goals—such as selling something. Libraries are more diverse, but we still have large organizational goals.
- When it comes to tracking all that data, there isn’t one tool to rule them all. There are lots of tools. But the tool I’m going to focus on today is…
- Survey results – how many use GA in their library and GA comfort level. What makes it a DA tool? It can collect and analyze data beyond a website.
- The tool I use is GDS. This is a new Google feature that is still currently in beta, but it is a data visualization tool
- Enough about the tools! We are here to talk about digital analytics providing us with data that impacts the physical library! After all, we are already tracking massive amounts of data. We just need to approach it with a specific lens to find the real world applications! I’m going to talk about 3 case studies we’ve done in my library and all of them are based off of sitting in meetings and people asking simple questions about usage.
- I’m not just interested in keeping the library open. The real question was about extending reference services either online or at the actual desk. There is the general notion that if you’re website is heavily trafficked at certain hours, then there’s a need to be open. But that treats all visits the same! People come to your library for different reasons and that doesn’t mean they all want to use the reference desk. So instead of just focusing on sessions, I wanted to find more about what users are doing on the library website when the ref desk is closed.
- I focused on content. I essentially did a content usage analysis comparing staffed hours vs non-staffed hours.
- Here’s a breakdown of the set up I used.
- Next case study focuses on instruction. How effective am I in the classroom? Are they really getting it? There are many ways to assess instruction, but I used DA to analyze online guide usage – focused on user actions on the guides and also gathered student feedback.
- The final case study focuses on electronic resources. We recently implemented a discovery service and our technical services team went through a crisis of where do we put these resources. Several workflows to make e-resource discoverable. Should we keep doing this or what is the best use of our resources?
- Compared four different sites and I looked at basic usage – how many sessions and users did the site receive; then I looked at the click-through rate –how many times a user actually used that site to access an electronic resource (database, online journal, ebook). Then I factored in the cost per click – they understood cost per use, so I was trying to give them a metric they could relate to. Lastly, I looked at electronic resource clicks to see if different sites were better at promoting specific e-resources. All of this was filtered by an event that only gather data from electronic resource link clicks.