Crowdgather Network

Monthly Uniques
2.6M US 5.2M Global

yuku.com

2.0M US 3.8M Global
  •  
  • Quantified

    Directly Measured Data

Workshop environment for serious writers/ poets. A community of experienced writers whose focus is on polishing poetry and prose for publication. [Description from dmoz]

This site reaches over 3.1 million monthly people, of which 1.6 million (52%) are in the U.S.The typical visitor watches Zap2It and uses Hotwire.

US Demographics:   [ Web ]


Gender

Largest Group and Index
Male


Segment These Sites vs. US Average IndexMultiple
Male
70% 
49% US Average
 
1421.42x
Female
30% 
51% US Average
  590.59x
US Average
Composition
 
Male 70%
 
Female 30%

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Age

Largest Group and Index
45-54


Segment These Sites vs. US Average IndexMultiple
< 18
12% 
18% US Average
  680.68x
18-24
10% 
13% US Average
  830.83x
25-34
17% 
17% US Average
  980.98x
35-44
21% 
19% US Average
 
1091.09x
45-54
21% 
17% US Average
 
1231.23x
55-64
12% 
10% US Average
 
1211.21x
65+
6% 
6% US Average
 
1071.07x
US Average
Composition
 
< 18 12%
 
18-24 10%
 
25-34 17%
 
35-44 21%
 
45-54 21%
 
55-64 12%
 
65+ 6%

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Children in Household

Largest Group and Index
No Kids


Segment These Sites vs. US Average IndexMultiple
No Kids
57% 
51% US Average
 
1121.12x
Has Kids
43% 
49% US Average
  880.88x
US Average
Composition
 
No Kids 57%
 
Has Kids 43%

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Household Income

Largest Group
$0-50k
Highest Index
$150k+


Segment These Sites vs. US Average IndexMultiple
$0-50k
45% 
51% US Average
  890.89x
$50-100k
31% 
29% US Average
 
1081.08x
$100-150k
14% 
12% US Average
 
1131.13x
$150k+
10% 
8% US Average
 
1191.19x
US Average
Composition
 
$0-50k 45%
 
$50-100k 31%
 
$100-150k 14%
 
$150k+ 10%

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Education Level

Largest Group
College
Highest Index
Grad School


Segment These Sites vs. US Average IndexMultiple
No College
33% 
45% US Average
  740.74x
College
48% 
41% US Average
 
1181.18x
Grad School
19% 
14% US Average
 
1321.32x
US Average
Composition
 
No College 33%
 
College 48%
 
Grad School 19%

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Ethnicity

Largest Group and Index
Caucasian


Segment These Sites vs. US Average IndexMultiple
Caucasian
82% 
76% US Average
 
1091.09x
African American
6% 
9% US Average
  620.62x
Asian
3% 
4% US Average
  820.82x
Hispanic
7% 
9% US Average
  740.74x
Other
1% 
1% US Average
  940.94x
US Average
Composition
 
Caucasian 82%
 
African American 6%
 
Asian 3%
 
Hispanic 7%
 
Other 1%

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Political Affiliation

Political Affiliation

This new metric describes the political affiliation of a web property's US audience. Independent includes anyone who identifies as Independent, or is unaffiliated with any party.

Highest Index
Democrat
Largest Group
Independent


Segment These Sites vs. US Average IndexMultiple
Republican
25% 
24% US Average
 
1041.04x
Democrat
34% 
30% US Average
 
1131.13x
Independent
41% 
46% US Average
  900.9x
US Average
Composition
 
Republican 25%
 
Democrat 34%
 
Independent 41%

Embed

Political Engagement

Political Engagement

This new metric describes the degree of political engagement for a web property's US audience.

Highest Index
Active
Largest Group
Somewhat Active


Segment These Sites vs. US Average IndexMultiple
Active
29% 
24% US Average
 
1211.21x
Somewhat Active
46% 
48% US Average
  970.97x
Inactive
25% 
28% US Average
  880.88x
US Average
Composition
 
Active 29%
 
Somewhat Active 46%
 
Inactive 25%

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Updated Jul 5, 2015 • Next: Jul 15, 2015 by 9AM PDT

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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 or mobile app to each platform population. The higher the index number, the more concentrated the property is in a particular demographic.

As an example, if a property 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 or mobile app to each platform population. The higher the index number, the more concentrated the property is in a particular demographic.

As an example, if a property 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 property divided by the average of the same segment on the entire Internet.

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


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

As an example, if a property 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.


Understanding Return Usage of Logged in Users

Digital brand offerings span across many device types and media channels. Quantcast allows brands to measure mobile web, online and app traffic. This feature allows a network property to demonstrate how logged in users migrate between these various platforms.

1. First Platform and First Cohort allow you to isolate a platform — for example mobile apps — and examine how users that start on mobile return over time to online, mobile web, apps or all of these platforms. The first cohort time range is for selecting a group of users you would like to track — for instance all users first seen within the course of a particular week an online ad campaign. Once defined, you can explore how this defined group of users returned, by platform, over time. A first-seen cohort may span up to 30 days.

2. Display Options allows you to choose available platforms to show return visits. More than one platform means that the logged in user returned on more than one platform (such as mobile apps and online) within the time period viewed. You can also select the amount of data points to review — 30, 60, or 90 days worth.

1. Bundled advertising inventory
Media properties often bundle together advertising inventory across platforms into a single package for their clients. By showing that customers are continuously engaged across multiple platforms, networks can demonstrate what packaging options make the most sense in all of the contexts and formats these platforms provide.

2. Measure efforts to migrate an audience from one platform to another
This feature is a great way to isolate marketing efforts made to drive usage from one platform to another by looking at historical changes in platform adoption.

3. Compare return usages nuances between platforms
Understand the nuances of usage pattern of customers on a particular platforms for product development decisions.



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