Chapter Statistics for "Backtalk of a Situation (or Situational Feedback)"

Based on a mining of Google Analytics and visitor profiling

Number of actual human readers. All robots and automated requests have been excluded. Here is

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How we calculate readership

Because of our online and tablet/iPad approach to publishing, we are able to precisely measure reading behaviour across hundreds of parameters in realtime: Anything from reading speed, drop-off points in the text, reader demographics, and much more.

Based on our server logs and the Google Analytics API, we calculate the number of readers as described in the calculation method below. A reader is not the same as a simple pageview and a reader is not the same as a website visitor (as described in our calculation method below). We calculate readership for two types of readers:

1. Readers who have read our whole encyclopedia, much the same way you read a printed book
2. Readers who have read an individual chapter

Calcalution method: How we define a reader

1. First we use the Google Analytics API to get a report of the number of unique human visitors to a chapter/page. Google runs its business on ads and thus completely relies on the ability to distinguish between a human visitor and an automated request. If not, you could earn millions on automating clicks on Google Ads.
2. We then compare that number to our Apache webserver logs, which report the much higher number of actual visits to a chapter/page (both human and automated). We calculate the difference in percent, which we call an "exaggeration factor", which we use in step 6 below.
3. With a large part of the visitors excluded, we further exclude any visitor who:
   1. has not remained on the page for at least 3 minutes (this factor is calculated by recording visit durations of 1000 randomly selected visitors) or has not printed the page (i.e. has not visited the printerfriendly version of the chapter/page)
   2. has not scrolled the page (this factor is calculated by recording scroll movements on 1000 randomly selected visitors)
4. We then further exclude "double readers", i.e. readers who read a portion of a chapter and then returns in, say, a week or a month to read the rest. Although this person's reading activity spans multiple server sessions, the person is only counted as a single reader. We categorize a "double reader" as a visitor who:
   1. visits a page, or multiple pages, across multiple server sessions
   2. qualifies to be defined as a reader, cf step 1-3 above, in all server sessions
   3. uses the same originating IP address
5. We then subtract 5% from the final number to counter-balance a last remaining factor, namely the situation where one reader reads a chapter on his/her tablet using a WiFi connection (and counted as one reader) but then picks up his other tablet using a 3G dongle (with another IP address) and re-reads some of the chapter. That will equal two readers, not one. We have no way of calculating how many times this situation arises, but to be on the safe side we subtract 5% from the final number.
6. We then take half of the "exaggeration factor" from step 2 and substract from the final number. We do this for no rational reason. We do it only as a further measure to be certain that our number of readers is not inflated.
7. To qualify as a reader who has read our whole encyclopedia - much the same way you read a printed book - that person must have qualified as a reader (cf. 1-6 above) of at least 80% of the encyclopedia chapters.

As a result, we have eliminated everything from automated requests to the more casual visitors. That leaves us with what we can safely call readers.

how we calculate readership.

Readers are mostly from these cities (Jan 1st to Jun 1st)

Readers are mostly from these continents (Jan 1st to Jun 1st)

Readers are mostly from these countries (Jan 1st to Jun 1st)

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Demographics

Data from Google Analytics, Facebook Insights, and our 2012 survey

* Users' self-reported data. Sample size 500.

* Users' self-reported data. Sample size 500.

* Users' self-reported data. Sample size 500.
** Not necessarily in a technology-related subject

* Users' self-reported data. Sample size 500.

 

Our readers work in the world's technology hotspots

 

Our readers are from diverse regions of the world - 180 countries

 

Our readership is global - both from Europe, the Americas, and Asia

Site statistics

Example readers

 

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Rinku from India uses our educational materials to advance her career in IT. She wanted to take a picture of herself with a printout of our logo. However, she can't afford a printer so she took a picture of herself with her laptop displaying our logo and emailed us her picture.

 

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Lu is from China and currently studies in the US:  For a girl from China, I fully understand the pain of buying a legal copy of a U.S. textbook."

 

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Idyawati is a Doctoral candidate at the International Islamic University of Malaysia. Using our site, she gets world-class educational materials for free. She can spend her money on buying an extra semester instead.

 

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Olga is associate professor in at Moscow University, Russia, and uses our materials because they are "of higher quality, faster to access, easier to reference, and well...free!"

 

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Miguel, Sandra, and Xavi are from the creative elite in Barcelona. They sent us their picture because they want to support the democratization of knowledge.

Example readers from our reader survey

The technology decision maker

Title

User Experience Lead

Age

46

Income

Over $150,000 per year

Education

Ph.D.

Purchasing budget

Over $1 million

Reason for using our site

"To brush up on the lingo used by my designers and external agencies"

 

 

The senior interaction designer

Title

Interaction Designer

Age

34

Income

$125,000 – $150,000

Education

MA/MS

Purchasing budget

$100,000 - $500,000

Reason for using our site

"I read new chapters on my way to work to develop my interaction design skills and exercise my brain cells"

 

 

 

The commercial classroom student

Title

Senior product designer

Age

37

Income

$100,000 – $125,000

Education

MA/MS

Purchasing budget

$100,000 - $500,000

Reason for using our site

"My company bought a five day course on user experience design and one of your chapters was part of the curriculum"

 

 

The professor

Title

Professor

Age

56

Income

$100,000 – $125,000

Education

Ph.D.

Purchasing budget

$100,000 - $500,000

Reason for using our site

"I teach a course on Human-Computer Interaction and use it as part of my curriculum"

 

 

 

Statistics for the whole encyclopedia project

Number of actual human readers of chapters. All robots and automated requests have been excluded. Here is

Close

How we calculate readership

Because of our online and tablet/iPad approach to publishing, we are able to precisely measure reading behaviour across hundreds of parameters in realtime: Anything from reading speed, drop-off points in the text, reader demographics, and much more.

Based on our server logs and the Google Analytics API, we calculate the number of readers as described in the calculation method below. A reader is not the same as a simple pageview and a reader is not the same as a website visitor (as described in our calculation method below). We calculate readership for two types of readers:

1. Readers who have read our whole encyclopedia, much the same way you read a printed book
2. Readers who have read an individual chapter

Calcalution method: How we define a reader

1. First we use the Google Analytics API to get a report of the number of unique human visitors to a chapter/page. Google runs its business on ads and thus completely relies on the ability to distinguish between a human visitor and an automated request. If not, you could earn millions on automating clicks on Google Ads.
2. We then compare that number to our Apache webserver logs, which report the much higher number of actual visits to a chapter/page (both human and automated). We calculate the difference in percent, which we call an "exaggeration factor", which we use in step 6 below.
3. With a large part of the visitors excluded, we further exclude any visitor who:
   1. has not remained on the page for at least 3 minutes (this factor is calculated by recording visit durations of 1000 randomly selected visitors) or has not printed the page (i.e. has not visited the printerfriendly version of the chapter/page)
   2. has not scrolled the page (this factor is calculated by recording scroll movements on 1000 randomly selected visitors)
4. We then further exclude "double readers", i.e. readers who read a portion of a chapter and then returns in, say, a week or a month to read the rest. Although this person's reading activity spans multiple server sessions, the person is only counted as a single reader. We categorize a "double reader" as a visitor who:
   1. visits a page, or multiple pages, across multiple server sessions
   2. qualifies to be defined as a reader, cf step 1-3 above, in all server sessions
   3. uses the same originating IP address
5. We then subtract 5% from the final number to counter-balance a last remaining factor, namely the situation where one reader reads a chapter on his/her tablet using a WiFi connection (and counted as one reader) but then picks up his other tablet using a 3G dongle (with another IP address) and re-reads some of the chapter. That will equal two readers, not one. We have no way of calculating how many times this situation arises, but to be on the safe side we subtract 5% from the final number.
6. We then take half of the "exaggeration factor" from step 2 and substract from the final number. We do this for no rational reason. We do it only as a further measure to be certain that our number of readers is not inflated.
7. To qualify as a reader who has read our whole encyclopedia - much the same way you read a printed book - that person must have qualified as a reader (cf. 1-6 above) of at least 80% of the encyclopedia chapters.

As a result, we have eliminated everything from automated requests to the more casual visitors. That leaves us with what we can safely call readers.

how we calculate readership.

Readers are mostly from these cities

Top countries

Top continents

 

 

Join the technology elite and advance:

 

1.

Your career

 

2.

Your network

 

 3.

Your skills

 

 

Join the technology elite !

About our funding and business model