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Marketing Gold for Libraries - The Data Inside
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Marketing Gold: the potential of data Tony Hirst Dept of Communication and Systems, The Open University
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Transcript of Marketing Gold for Libraries - The Data Inside
Marketing Gold:the potential of data
Tony HirstDept 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”KPIs
Vanilla 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.
HhhhhhhHHHhhhhhuuuuuuuuummmmmmm.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!
Whatever…
via Dave Pattern @daveyp
“Raw” dataTransaction dataAttention data
Usage data
“Raw” data(Spreadsheets)((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, YouTubeAmazon, AudibleGoogle (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 of a …
• Friend• Event• Topic• Activity• Group
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?
supervised learning(desired output for given input)
Input patterns
Output Patterns
“recommendation engine”
Desired outputActual output
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
data.gov.uk
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’selm city project
Hook-in to networks
• Help information flow• Amplify, enrich and engage with others
Events: bookshops
Library talks……or contextually amplify signing events at local bookshops
Events: museums
Provide more information – draw on the way interests flow through networks
“Maturity Models”
Gartner Maturity Model for Web Analytics
WebTrends DM3:Digital Marketing Maturity Model
“Maturity models”
http://www.jiscinfonet.ac.uk/bi
blog.ouseful.info
@psychemedia
http://www.flickr.com/photos/psychemedia/galleries/72157624594881902/
http://www.videopong.net/?action=show&query=playlist&id=106
