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Web Analytics in the
Created Content
Committee
Adam Strom, Newberry Library
Margaret Heller, Loyola University Chicago
Pau...
About the Created Content
Committee
• The CCC works with CARLI staff and members to
identify, develop, and encourage coope...
Report on sources of traffic
• Google Analytics (CARLI provides
spreadsheet)
• Excel
• OpenRefine (optional but faster and...
Transforming the data
• Deciding what stories to tell
• Finding new interpretations of the data
Beyond the Numbers:
Digging into Data
• Determining popular items
• Discovering sources of traffic
• Analyzing anomalies
•...
What content is popular
• Common search terms and types
• Specifically relevant keywords for your
collection
What drives traffic
• What sites are sending users to the
collection?
• What types of sites tend to recur?
• Are there new...
Anomalies
• Are there spikes in traffic?
• What are they generated by or tied to?
Marketing success
• Matching traffic patterns with marketing
efforts
• Were certain campaigns or types of images
better at...
Making Use of the Data
Analysis of efforts and identifying areas of
improvement
• Are these what we expected?
• Are themes coming up? How might we
apply these to existing collections to improve
discover...
Traffic Generation
Now that we can see where traffic is coming
from we can ask:
• How can we use social media to better dr...
Moving forward
Web Analytics for Digital Collections: Appraising Collections and Assessing Impact
Web Analytics for Digital Collections: Appraising Collections and Assessing Impact
Web Analytics for Digital Collections: Appraising Collections and Assessing Impact
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Web Analytics for Digital Collections: Appraising Collections and Assessing Impact

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This presentation addresses web analytics as an assessment tool for current digital collections/resources, as well as a way to inform the appraisal or promotion of future digital projects. Since the statistics reporting capabilities of many software platforms only provides broad hit and download numbers, we'll be exploring how Google Analytics and other tools can allow an institution to generate far more detailed statistics about who is visiting their site, what they're looking at, and how they got there. Assessment via web analytics can also help an institution determine what content is in demand in order to appraise items for a new digital resource, or show what unexpected promotional tools might have the potential to bring a whole new audience to a new or upcoming digital collection. Since the same data can be used to tell any number of stories, the presenters will talk about how to ask the right questions when generating and interpreting reports, and how to use these statistics effectively.

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Web Analytics for Digital Collections: Appraising Collections and Assessing Impact

  1. 1. Web Analytics in the Created Content Committee Adam Strom, Newberry Library Margaret Heller, Loyola University Chicago Paul Go, IIT
  2. 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. 3. Report on sources of traffic • Google Analytics (CARLI provides spreadsheet) • Excel • OpenRefine (optional but faster and easier) • Reports
  4. 4. Transforming the data • Deciding what stories to tell • Finding new interpretations of the data
  5. 5. Beyond the Numbers: Digging into Data • Determining popular items • Discovering sources of traffic • Analyzing anomalies • Marketing success
  6. 6. What content is popular • Common search terms and types • Specifically relevant keywords for your collection
  7. 7. 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?
  8. 8. Anomalies • Are there spikes in traffic? • What are they generated by or tied to?
  9. 9. 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?
  10. 10. Making Use of the Data Analysis of efforts and identifying areas of improvement
  11. 11. • 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
  12. 12. 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?
  13. 13. Moving forward

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