Virtualization of the Patron Experience

Virtualization of the Patron Experience

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This very interesting article in USAToday about the future of retail and virtualization of the customer experience demonstrates how big data can affect and effect virtualized experiences for their patrons:

http://www.usatoday.com/tech/news/story/2012-08-05/future-retail-tech/56880626/1

Libraries compete with online information resources in much the same way the traditional retailers compete with online sellers.

Question ~ How will libraries adapt over the next ten years?

Robert Balliot for https://bestofpublib.wordpress.com

Discussion ~ My work in managing/developing online catalogs – with 20,000+ medical equipment / supply products and 7,000+ multi-website display products exceeded what library catalogs do and from an SEO standpoint would beat out Amazon for Google placement.  Traditional retail could not compete because of delivery and cost.  BestBuy is a great place to put your hands on tech, but the prices are much higher.  As e-commerce websites become more and more user-friendly – where you have good photos of products and good descriptions, the whole process ends up making all products into commodities with the lowest cost determining purchase.

With libraries, the focus has generally been on maintaining the status quo and keeping current bureaucracies in place until they can retire. This is not any different for any other bureaucracy – it is a natural inclination – not library specific to simply maintain.  With the focus on cost of maintaining services though, without innovation the perception of value diminishes.  One of the best things I have seen recently in libraries is the introduction of Makerbots as a library resource.  It is those sorts of high-priced shared resources that extend the value and bring people inside the library systems.

But, the issue does become lowest cost.  As we see transportation cost rise, the casual trip to the library could cost $10 in gas. What would $10 purchase virtually?  The associated costs of operating libraries – broken down between the people who continue to use them and the disproportionate number of people who don’t would add additional cost to each real visit.  As information becomes a commodity the lowest cost will determine where we purchase.  That does not mean that the value of libraries as a sense of place and source of inspiration does not add a real value to information consumption.

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Publib Topics – A Graphic Retrospective – November 2011

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This graphic image  or word cloud was created using Wordle. It is derived from the subjects and authors of postings in PubLib for November 2011. The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented. Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds. These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
 
The most prominent word without employing filters would have been PublibPublib and Fwd were deleted from the plaintext files before processing. In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
 
Publib Topics November 2011

Publib Topics November 2011

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Publib Topics – A Graphic Retrospective – July 2011

Beware Graphic Content Ahead!

 
This graphic image or word cloud was created using Wordle. It is derived from the subjects and authors of postings in PubLib for July 2011. The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented. Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds. These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
 
The most prominent word without employing filters would have been PublibPublib and Fwd were deleted from the plaintext files before processing. In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
 
Publib Topics - July 2011

Publib Topics - July 2011

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Publib Topics – A Graphic Retrospective – June 2011

Beware Graphic Content Ahead!

 
This graphic image  or word cloud was created using Wordle. It is derived from the subjects and authors of postings in PubLib for June 2011. The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented. Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds. These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
 
The most prominent word without employing filters would have been Publib.  Publib and Fwd were deleted from the plaintext files before processing. In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
This month and the month of May featured lively discussions of concealed carry of guns by library staff and others in libraries, Save the Libraries, Fire the Librarians, and Farting Patrons.
 
Publib Topics June 2011

Publib Topics June 2011

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Publib Topics – A Graphic Retrospective – May 2011

Beware Graphic Content Ahead!

 
 This graphic image  or word cloud was created using Wordle. It is derived from the subjects and authors of postings in PubLib for May 2011. The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented. Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds. These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
 
The most prominent word without employing filters would have been Publib. Publib and Fwd were deleted from the plaintext files before processing. In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
This  month featured a lively Rapture discussion
 
Publib Topics May 2011

Publib Topics May 2011

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Publib Topics – A Graphic Retrospective – April 2011

Beware Graphic Content Ahead!

 
This graphic image  or word cloud was created using Wordle. It is derived from the subjects and authors of postings in PubLib for April 2011. The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented. Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds. These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
 
The most prominent word without employing filters would have been Publib. Publib and Fwd were deleted from the plaintext files before processing. In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
Publib Topics April 2011

Publib Topics April 2011

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Publib Topics – A Graphic Retrospective – February 2011

Beware Graphic Content Ahead!

 
This graphic image  or word cloud was created using Wordle. It is derived from the subjects and authors of postings in PubLib for February 2011. The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented. Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds. These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
 
The most prominent word without employing filters would have been Publib. Publib and Fwd were deleted from the plaintext files before processing. In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
Publib Februrary 2011

Publib Februrary 2011

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Publib Topics – A Graphic Retrospective – January 2011

Beware Graphic Content Ahead!

This graphic image or word cloud was created using Wordle. It is derived from the subjects and authors of  postings in PubLib for January 2011.  The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented.    Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds.  These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.

 
The most prominent word without employing filters would have been PublibPublib and Fwd were deleted from the plaintext files before processing.  In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions. 
 
Publib Word Cloud January 2011

Publib January 2011

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Publib Topics – A Graphic Retrospective from January 2011 back to January 2010

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These graphic images or word clouds were created using Wordle. They are derived from the subjects and authors in PubLib from January 2010 to January 27 2011.  The size of the graphics is directly related to the number of un-weighted unique occurrences each month of the individual words represented.    Most automated graphic processes that generate these types of word clouds use additional weight for H1 – H6 tags through feeds.  These graphics are not processed with H1 – H6 tags. The titles and authors were copied to Notepad and stripped of all HTML before being run through the Wordle Java platform. The process is case-sensitive so Library is not the same thing as library.
The most prominent word without employing filters would have been PublibPublib and Fwd were deleted from the plaintext files before processing.  In addition, the Wordle program automatically disregards articles, conjunctions, and prepositions.
 
The first graphic represents the most current information for January 2011 and is followed by the normal sequence of January – December 2010.  
2011 appears somewhat ominous! 
January 2011 PubLib

PubLib January 2010

PubLib February 2010

PubLib March 2010

PubLib April 2010

PubLib April 2010

PubLib May 2010

PubLib May 2010

PubLib June 2010

 

PubLib July 2010

 

PubLib August 2010

PubLib September 2010

PubLib October 2010

PubLib November 2010

PubLib December 2010

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Best of PubLib 03.28.10

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This edition of  Best of Publib covers  March 15th through March 28th 2010. This PubLib review and analysis includes questions about naming library rooms, thought-provoking discussions about new media archives , library materials security,  and our new poll on R-rated movie access. Some of the topics we will be reviewing include: 

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