Hi to go beyond Google Analytics and the data you can collect yourself to add to and enhance existing analytics data.

1. Analysing content:
beyond Google Analytics
Jonathan Richardson
ConsideredWords.com
#SeriouslyLDN

2. Introduction

3. Recap: Google Analytics
• Tells you about your users.
• For those of you unfamiliar, it can tell you:
• how people reach your site
• what search words they use to get there and on there
• how people are reaching your goals (eg clicking on buy, subscribing
etc)
• what your most popular pages are and where they leave your site
• what people are doing on your page

4. Case study

5. Our team had a problem
At Defra (UK environment department) - how do we
measure success?
How to convince others we had succeeded in improving
content when Google Analytics fell short.

6. http://webarchive.nationalarchives.gov.uk/20130221085659/http://www.defra.gov.uk/animal-diseases/a-z/bluetongue/
https://www.gov.uk/guidance/bluetongue

7. Add to what we measure
If Google Analytics is a measurement of output, then text
analysis is a measure of input.
Know yourself v know your users.

8. National Gallery

9. 1. Readability
http://www.hemingwayapp.com/
8.5

10. 2. Structural data
• headlines - longer is better
• shorter content - shorter is generally better, at least on
such a large sample
• readability - better content is easier to read
• keywords - GOV.UK has a style guide so what could we
look for?
• user needs - rank those and see which pages had them
and which don’t

12. Make comparisons
simple

13. 3. Combine
• Combine with Google Analytics data to measure more,
eg:
• sub-headings use
• wording used on links
• readability and conversion rates

14. Combine with
Google Analytics data

15. Results
• better user needs - set up a panel to review them
• improved heading use
• more visitors to the site
• improved sub-editing and training on what to look for
• improved testing

16. Summary
• you can go beyond Google Analytics and combine it to
squeeze out more insight
• you can analyse your own content before you hit publish
• you can use it to investigate anomalies
• measure yourself

17. Final thoughts
• you still needs an editor's eye
• not measure is going to be 'correct' and many are
criticised (eg readability), but we use them knowing the
limitations
• choose the measures you understand and can give you a
simple output to interpret
• more of the right measures give you more ammunition
and evidence for your content

18. Useful links
• Readability:
• MS Word has this feature built in
• hemingwayapp.com offers this (and
more)
• Python tools for scraping many
documents
• Structural data
• your own eye/count
• Google Docs ImportXML
• scraping (Python, Perl, dedicated tools)
• Combining & visualising data:
• Google Sheets/Excel
• Google Fusion tables
• RAW

19. Questions?