Iadb.org Traffic and Demographic Statistics by Quantcast

 

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iadb.org

Monthly Uniques 42.6K CO 259.5K Global
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  • Quantified

    Directly Measured Data

Information about the IDB Group and its activities, organization, members and partners, employment opportunities, locations and contacts. [Description from dmoz]

Inter-American Development Bank is like a mutual aid society that packs an economic punch. The institution was founded in 1959 to aid in the social and economic development of Latin America and the Caribbean. It provides grants and loans to help fund public and private projects, modernize public institutions, foment free trade, and reduce poverty. The bank is also involved in cross-border issues such as infrastructure and energy. Inter-American Development Bank is owned by its 47 member nations, which consist of 26 borrowing members in Central America, South America, and the Caribbean, plus nonborrowing members including the US, Canada, and 19 other countries. [Description from Hoover's]

This site reaches over 259K monthly people, of which 31,673 (12%) are in the U.S.


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IAB Standard Traffic Report  4/2/13 - 5/1/13

Data GLOBAL
Events Received 1,698,871
Multi-Events 18,573
Estimated Robot Events 3,847
Net Page Views 1,676,451
Estimated Auto-Refresh Events 0%
Net Sessions 554,804
Unique Cookies 298,263

This is the raw count of HTML pixel requests Quantcast has received, plus qualified Flash video play events.

This is the number of pixel requests received within one second of a previous one for the same user. These are typically caused by multiply-tagged iframes within a single page.

This is the number of pixel requests attributed to non-human activity.

This is the estimated number of human-requested pages, based on the raw event count corrected for multi-events and robots.

This is the estimated fraction of page views due to auto-refresh rather than user-initiated requests, and approximate auto-refresh frequency.

This is the number of qualified Flash video play events received. To be qualified, Quantcast must have been able to confirm the events are sent after the player has buffered the content, per IAB standards.

This is the number of user sessions, discounting robots. A session is a period of activity separated by at least a half-hour of inactivity.

This is the number of unique cookie IDs received, discounting robots.

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People from Sites & Syndicators

These percentages usually sum greater than 100% due to overlap in site and syndicated audiences.

Reading Demographic Graphs

1. Index

This compares audience composition of the site to the entire Internet population. The higher the index number, the more concentrated a site is in a particular demographic.

As an example, if a site indexes 100 for age 18-24, that means a given visitor to it is as likely to be 18-24 as any internet user chosen at random. An index of 200 means the visitor is twice as likely to be 18-24, 50 means half as likely, and so on.

2. Segments are represented with icons. Segments include gender, age, household income, and education.

3. Very High Indexes (over 200) are denoted with a plus symbol.

4. Internet Average is represented by the dotted vertical line.


Reading Demographic Graphs

This compares audience composition of the site to the entire Internet population. The higher the index number, the more concentrated a site is in a particular demographic.

As an example, if a site indexes 100 for age 18-24, that means a given visitor to it is as likely to be 18-24 as any internet user chosen at random. An index of 200 means the visitor is twice as likely to be 18-24, 50 means half as likely, and so on.

1. Segment refers to the demographic composition attribute.

2. Very High Indexes (over 200) are denoted with a plus symbol.

3. Internet Average is represented by the dotted vertical line.

4. Expand the data to see the numbers which make up the index calculation.

The expanded view shows the percentage composition, the Internet average and the multiple.

1. A Colored Bar indicates that a segment exceeds the Internet average, whereas a gray bar indicates the segment is below the Internet average. Internet average is represented by the dotted vertical line.

2. A Multiple is the percentage of the segment on this site divided by the average of the same segment on the entire Internet.

Example:
80% female segment on site ÷ 32% female internet average = 2.5x

This chart breaks down the site's audience for a demographic. All the segments collectively equal 100%.

As an example, if a site indexes 100 for age 18-24, that means a given visitor to it is as likely to be 18-24 as any internet user chosen at random. An index of 200 means the visitor is twice as likely to be 18-24, 50 means half as likely, and so on.

1. The Top-Indexing Segment is shown in color.


Understanding User Retention

This graph examines user retention patterns for a mobile app, which tells the story of how much of app's user base continues to use the app after installation over time.

1. The x-axis is comprised of cohorts based on when users installed the app. For example, if we look at the column "+3 Days", this means that regardless of whether users installed the app a week ago or a month ago, what ratio of these users have returned within three days after installation.

2. The gray bars indicate the average retention rate across all days the app was downloaded.

3. The yellow line represents the average retention rate by period of all apps measured by Quantcast.

4. Install grouping details can be found by clicking on the down arrow.

In the expanded view, each row shows the retention patterns based on a point in time. Click on each row to compare that cohort against the average of all users installing the app.

1. The average day row shows the general retention rate for the entire app.

2. The highlighted row shows the retention rate compared against the average. In this example, 29% of users who installed the app one month ago returned at some point within two days, compared to the average of 35%.

3. The Add Date button allows you to add custom dates to determine retention patterns.

4. The Close button collapses the details and returns you to the default view.


Understanding Visit Frequency

This chart shows the number of return visits for unique users over the last 30 days.

1. Toggle between visit patterns of Logged In and Non Logged In users. In order to enable the toggle, the publisher must designate that the app has a logged in user base. The Logged In number represents the visit frequency of users that have logged in order to use this app.

3. For example, over the last 30 days, 3,644 unique users visited 4-7 times.


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