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Marketing Gold for Libraries - The Data Inside






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    Marketing Gold for Libraries - The Data Inside Marketing Gold for Libraries - The Data Inside Presentation Transcript

    • Marketing Gold:
      the potential of data
      Tony Hirst
      Dept of Communication and Systems,
      The Open University
    • Data today…
      Accountability and transparency
      Resource allocation
      (Service improvement)
      Context of
      Funding (accounts)
      Service delivery (stats)
      User expectations (surveys)
    • two flavours of data
    • “Stats”KPIsVanilla reports(PDF docs)
    • KPIs
      Access and facilities (i.e # Average number of libraries per 1000 inhabitants)
      Collection (i.e # Average number of volumes in public libraries per 1000 literate inhabitants)
      Library use and users (i.e # Registered users in higher education libraries as a percentage of number of students)
      Library staff (i.e # Average number of employees in public libraries)
      Expenditure (i.e $ Expenditure on literature and information per inhabitant in public libraries)
      Ellis, S., Heaney, M., Meunier, P., Poll. R. (2009), “Global Library Statistics”, IFLA Journal, Vol. 35 No. 2, pp. 123-130
      Via http://www.smartkpis.com/blog/2010/03/29/performance-measurement-and-kpi-selection-in-the-library-services-sector/
      But really via Google + MY search terms..
    • Blah
      Blah blah blah blah, blah blah blah blah, blah, blah blah, blah blah, blah blah, blah.
      Blah blah blah, blah, blah blah blah, blah, blah, blah, and up by blah, and down by bleurghh, and blah blah, blah blah, blah blah, bah!
    • via Dave Pattern @daveyp
    • “Raw” data
      Transaction data
      Attention data
      Usage data
    • “Raw” data
      ((Linked Data))
    • Change behaviour based on error data
    • “Negative feedback, closed loop control system”
    • BOTH sorts of data…
      …can be used to make decisions
      …can be “Actionable”
    • Who do you think your competitors are, and on what are they competing?
    • How do you know?
    • Who do your “customers” think your competitors are, and what do they think they are competing on?
    • How do you know?
    • “Libraries are placesthat minds like to be”
    • Starbucks/Café Nero
      (Blockbuster), Lovefilm, YouTube
      Amazon, Audible
      Google (search, scholar, books)
      Facebook, Twitter
    • As far as Google is concerned, your website is just largely unstructured DATA
    • OU Library: College of Law referrals
    • Aggregated/averaged data may mislead
    • Means sometimes are(n’t)…
    • Segregation (i.e. segmentation) can be a Good Thing
    • “treemap”
    • Data contains explicit and implicit structure
    • Geo-demographics
    • Networks, graphs, and trees
    • Custom search engines around “hashtag communities”
    • Can you cluster your data?
    • In the academic library,discovery happens elsewhere
    • Should you be an influential friend?
    • Friend
      Friend of a …
    • Data may contain signals
    • What data do you have?
      Collection data
      Usage data
      User (geo)demographics
      Occupancy/usage of physical space (and how is the space used?)
      What journals are being photocopied?
      What books are referred to but not borrowed?
      What requests/searches aren’t being fulfilled?
    • Input patterns
      Output Patterns
      “recommendation engine”
      Desired output
      Actual output
      supervised learning(desired output for given input)
    • People who..
      Borrowed this, borrowed that
      Borrowed this, studied that
      Study this so might borrow that
      Know these people who all borrowed that
      Are in this group of people, who tend to borrow the same thing at around the same time, or just before (or after) another group
    • Book reserve and collection?
    • Public open data
    • How might you be able to make use of other people’s data…… and how might they be able to make use of your data?
    • If a library is a place to go to find out about “local stuff”…
    • …how much do you know about what web services out there, anywhere, know about your locale?
    • Jon Udell’s
      elm city project
    • Hook-in to networks
      Help information flow
      Amplify, enrich and engage with others
    • Library talks…
      …or contextually amplify signing events at local bookshops
      Events: bookshops
    • Provide more information – draw on the way interests flow through networks
      Events: museums
    • “Maturity Models”
      Gartner Maturity Model for Web Analytics
      “Maturity models”
      WebTrends DM3:
      Digital Marketing Maturity Model
    • http://www.jiscinfonet.ac.uk/bi
    • blog.ouseful.info@psychemedia
    • http://www.videopong.net/?action=show&query=playlist&id=106