• About IR Thoughts

IR Thoughts

~ Thoughts on Information Retrieval, Data Mining, and Search Engines

IR Thoughts

Monthly Archives: November 2012

Teleporting, Marketing, and Teleportnication

18 Sunday Nov 2012

Posted by egarcia in Machine Learning, Marketing Research

≈ Leave a Comment

Here in Puerto Rico we usually run behind the rest of the Nation, in implementing technology advances and good ideas, by about 5 to 7 years. Just this month and due to the elections, a local TV channel just started experimenting with teleportation. Few years ago that was tested in the USA. It is a catchy marketing technology.

Back then my SEO and marketing friends immediately started to see the next “future” for marketing and, of course, porn: teleportation for meetings, events, and SEO Conferences.

Keep these terms in mind: Teleportnication, Teleportnography => Teleportnicación, Teleportnografía

PS: Mobile apps for that, too? Probably there are some out there now or in the near future (with the right equipment in place) Portnography, anyone?

Why time spent on a site is so important?

13 Tuesday Nov 2012

Posted by egarcia in IR Tools, Marketing Research, Miscellaneous, Software

≈ Leave a Comment

That is a recurrent question being asked by some of my readers. Here is my answer.

Back in 1995, I wrote in the Dedication section of my doctoral thesis:

“If I have a theory, but no experimental results, I may have nothing. And if I have a theory without practical applications, I may have an artifact.”

So, don’t give your visitors hearsays, half-lies, or misrepresentation of facts found across the Web, but things that they can really test, use, and that solve a real or urgent problem for them. Don’t waste your time repeating interesting -perhaps catchy concepts-, but that at the end of the day are just useless.

In addition to textual and audiovisual content of good quality, give them TOOLS. However, provide tools that make them interact more time with your site and that authoritative pages will recommend or link to.

This is important because the amount of time spent by users in a site is directly correlated to several web metrics/analytics like:

  • frequency cap – restriction on the amount of time a specific visitor is shown a particular advertisement.
  • stickiness – the amount of time spent at a site over a given time period.
  • underdelivery – delivery of less impressions, visitors, or conversions than contracted for a specified period of time.
  • unique visitors – individuals who have visited a site (or network) at least once during a fixed time frame.
  • bandwidth – how much data (e.g., content, ads, creatives) can be transmitted in a time period over a communication channel, often expressed in kilobits per second (kbps). Data is any alphanumeric content. This includes parameters, variables or any text/pixel-based creative.

Other time-based metrics inherited from traditional media (TV, radio) and that are based on the time spent by users viewing a communication channel can be applied to web channels and sites; among others:

  • average audience – the average number of people who tuned into the given time selected and expressed in thousands or as a percentage (also known as a Rating) of thetotal potential audience of the demographic selected. It is also known as a T.A.R.P -Targeted Audience Rating Point.
  • channel share – the share one channel has of all viewing for a particular time period. The share, expressed as a percentage, is calculated by dividing the channel’s average audience by the average audience of all channels (PUTs) (It is held in higher esteem by networks than media buyers on a day to day basis and is only referred to by the latter group when apportioning budgets and evaluating a programme for sponsorship).
  • cummulative audience or reach – the total number of different people within the selected demographic who tuned into the selected time period for 8 minutes or more (i.e., reached at least once by a specific schedule or advertisement).
  • frequency – the average number of times that a person within the target audience has had the opportunity to see an advertisement over the campaign period.
  • time spent viewing or TVS – how many minutes/hours an audience has viewed a particular channel.

[Sources: WebSiteMagazine, WebMediaSolutions, NielsenMedia].

So, any tool that helps your visitors to wisely improve their time spent on your site -in an effective manner, of course- cannot hurt you. For this to be true, however, the tool provided must be engaging, useful, effortless, and with a minimum learning curve; otherwise the user experience of your visitors can be frustrating and a waste of time.

Back to Business

07 Wednesday Nov 2012

Posted by egarcia in Programming

≈ Leave a Comment

Thanks, God that:

The 2012 Elections are over.

We have a political change in Puerto Rico.

http://www.miislita.com site is back to business.

Things to come:

A work and tests in progress:

How to enable JavaScript-only external web pages to execute server-side scripts.

 

 

November 2012
M T W T F S S
« Oct   Dec »
 1234
567891011
12131415161718
19202122232425
2627282930  

Favorite Sites

  • Mi Islita

Pages

  • About IR Thoughts

Categories

  • AIRWeb Course
  • Conferences
  • Data Mining
  • Dynamics
  • Fractal Geometry
  • Graduate Courses
  • Hacking
  • Homeland Security
  • Human-Computer Interaction
  • Image Compression
  • Internet Engineering
  • IR Quizzes
  • IR Tools
  • IR Tutorials
  • Latent Semantic Indexing
  • Legacy Posts
  • Machine Learning
  • Marketing Research
  • Miscellaneous
  • News
  • Newsletters
  • Programming
  • Quack Science
  • Queries
  • Scripts
  • Search Engines Architecture Course
  • SEO Myths
  • Software
  • Spam
  • Statistics and Mathematics
  • Theses
  • Vector Space Models
  • Web Mining Course

Recent Posts

  • “Powered by” in Spanish
  • Some nice features added to the Image Crawler
  • The Images Crawler
  • A nice service for my locals
  • An update to the Web Crawler
  • New similarity measures
  • The Web Crawler is Back!
  • Tracking Users: An Email Crawler on Steroids
  • The Email Crawler: A Tool for Gathering Emails
  • The Binary Distance Calculator – a tool for comparing binary sets
  • Fractalettes: A Fractal Design Strategy to Color Mining and Learning through Discovery
  • AZZOO and WAZZOO: New Similarity Measures for the 21st Century
  • The Binary Similarity Calculator
  • From Harlem Shake to Link Shake: The Qualified Links Shake
  • Web Vulnerabilities and Search Engines

Archives

  • May 2013
  • April 2013
  • March 2013
  • February 2013
  • January 2013
  • December 2012
  • November 2012
  • October 2012
  • September 2012
  • August 2012
  • July 2012
  • June 2012
  • May 2012
  • April 2012
  • March 2012
  • February 2012
  • January 2012
  • December 2011
  • November 2011
  • October 2011
  • September 2011
  • August 2011
  • July 2011
  • June 2011
  • May 2011
  • April 2011
  • February 2011
  • January 2011
  • December 2010
  • November 2010
  • October 2010
  • September 2010
  • August 2010
  • July 2010
  • June 2010
  • May 2010
  • April 2010
  • March 2010
  • February 2010
  • January 2010
  • December 2009
  • November 2009
  • October 2009
  • September 2009
  • August 2009
  • July 2009
  • June 2009
  • May 2009
  • April 2009
  • March 2009
  • February 2009
  • January 2009
  • December 2008
  • November 2008
  • October 2008
  • September 2008
  • August 2008
  • July 2008
  • June 2008
  • May 2008
  • April 2008
  • March 2008
  • February 2008
  • January 2008
  • December 2007
  • November 2007
  • October 2007
  • September 2007
  • August 2007
  • July 2007
  • June 2007
  • May 2007
  • April 2007

AIRWeb Course Conferences Data Mining Fractal Geometry Graduate Courses Hacking Homeland Security Human-Computer Interaction Internet Engineering IR Quizzes IR Tools IR Tutorials Latent Semantic Indexing Legacy Posts Machine Learning Marketing Research Miscellaneous Newsletters Programming Quack Science Queries Scripts Search Engines Architecture Course SEO Myths Software Spam Statistics and Mathematics Theses Vector Space Models Web Mining Course

Blog at WordPress.com. Theme: Chateau by Ignacio Ricci.