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SimplyE Analytics are provided through an integration with between the SimplyE circulation manager and Google AnalyticsTM. All events We do not track events within the mobile app, and all events are event based versus client based so that no particular user can be identified. All events are anonymously generated by the transactions of signing in, placing holds, and borrowing a book from the libraries vendors, use of the client. Therefore events fall into 3 basic categories:

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  • open_book – A patron opened a book in the SimplyE app

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  • open_book_first_time (what should we name this?) – A patron opened a book in the SimplyE app for the first time on their current device. If they open the book on an additional device later, that will also be an open_book_first_time event.

Suggestions?
Dimensions that are included in each event:

  • audience – whether the book is classified as Adult, Young Adult, Children, or Adults Only
  • fiction – fiction or nonfiction status of the book
  • genre – The "top genre" for the book in the event - the genre with the highest weight in our database.
  • identifier – The identifier (eg. Overdrive ID or ISBN) that SimplyE uses to refer to the book. Could be used for filtering to a specific book.
  • identifier_type – The type of identifier that SimplyE uses to refer to the book (eg. Overdrive ID or ISBN). Could be used to filter by distributor.
  • language – language of the book
  • publisher – publisher of the book
  • target_age – target age range of the book
  • time – time that the event occurred. May be inaccurate for distributor events.
  • title – title of the book

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  • Readers Advisory – How does what we promote affect demand? "Demand Shaping"
  • Collection Development – What do people like to read? – Genre intelligence, Audience, Authors, etc
  • Marketing – What are New Yorkers Reading? Engagement with our patrons
  • Data Analytics – SimplyE circulation vs the distributor circulation, basics stats, etc.

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Things you can do with Google Analytics

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Patron Identifier based events – This is wanted in order to measure on an event basis the type of activity individual users demonstrate so the library can better understand users needs for e vs physical media or other media types. This would mean counting event types by Patron ID but not the specific dimensions that could point to a specific reading history on a title basis. This data may need to go into a separate Analytics account or system given the individualized nature of the data capture.
Medium dimension – To filter events to a specific medium like epub or audiobook.