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Wetpaint Network

Monthly Uniques
13.4M US 16.1M Global

wetpaint.com

13.4M US 16.1M Global
  •  
  • Quantified

    Directly Measured Data

Free wiki hosting service with proprietary software, GUI editing interface, and instant site registration. URL for wikis is "http://yourtopic.wetpaint.com/". [Description from dmoz]

This site reaches over 13 million monthly people, of which 10 million (82%) are in the U.S.The typical visitor shops at shoplocal.com.

Related Links

US Demographics:   [ Web ]


Gender

Largest Group and Index
Female


Segment This Site vs. US Average IndexMultiple
Male
11% 
48% US Average
  230.23x
Female
89% 
52% US Average
 
1741.74x
US Average
Composition
 
Male 11%
 
Female 89%

Embed

Age

Largest Group and Index
< 18


Segment This Site vs. US Average IndexMultiple
< 18
30% 
18% US Average
 
1651.65x
18-24
10% 
12% US Average
  840.84x
25-34
18% 
17% US Average
 
1061.06x
35-44
22% 
19% US Average
 
1141.14x
45-54
13% 
17% US Average
  740.74x
55-64
5% 
10% US Average
  480.48x
65+
2% 
6% US Average
  290.29x
US Average
Composition
 
< 18 30%
 
18-24 10%
 
25-34 18%
 
35-44 22%
 
45-54 13%
 
55-64 5%
 
65+ 2%

Embed

Children in Household

Largest Group and Index
Has Kids


Segment This Site vs. US Average IndexMultiple
No Kids
38% 
51% US Average
  740.74x
Has Kids
62% 
49% US Average
 
1271.27x
US Average
Composition
 
No Kids 38%
 
Has Kids 62%

Embed

Household Income

Largest Group and Index
$0-50k


Segment This Site vs. US Average IndexMultiple
$0-50k
69% 
51% US Average
 
1361.36x
$50-100k
22% 
29% US Average
  740.74x
$100-150k
6% 
12% US Average
  500.5x
$150k+
4% 
8% US Average
  420.42x
US Average
Composition
 
$0-50k 69%
 
$50-100k 22%
 
$100-150k 6%
 
$150k+ 4%

Embed

Education Level

Largest Group and Index
No College


Segment This Site vs. US Average IndexMultiple
No College
50% 
45% US Average
 
1121.12x
College
41% 
41% US Average
 
1001.0x
Grad School
9% 
14% US Average
  630.63x
US Average
Composition
 
No College 50%
 
College 41%
 
Grad School 9%

Embed

Ethnicity

Largest Group and Index
African American


Segment This Site vs. US Average IndexMultiple
Caucasian
36% 
76% US Average
  470.47x
African American
53% 
9% US Average
5775.77x
Asian
2% 
4% US Average
  420.42x
Hispanic
8% 
9% US Average
  890.89x
Other
2% 
1% US Average
 
1111.11x
US Average
Composition
 
Caucasian 36%
 
African American 53%
 
Asian 2%
 
Hispanic 8%
 
Other 2%

Embed

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.

Largest Group and Index
Democrat


Segment This Site vs. US Average IndexMultiple
Republican
16% 
24% US Average
  670.67x
Democrat
55% 
30% US Average
 
1841.84x
Independent
29% 
46% US Average
  620.62x
US Average
Composition
 
Republican 16%
 
Democrat 55%
 
Independent 29%

Embed

Political Engagement

Political Engagement

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

Largest Group
Somewhat Active
Highest Index
Inactive


Segment This Site vs. US Average IndexMultiple
Active
23% 
24% US Average
  970.97x
Somewhat Active
43% 
48% US Average
  900.9x
Inactive
34% 
28% US Average
 
1201.2x
US Average
Composition
 
Active 23%
 
Somewhat Active 43%
 
Inactive 34%

Embed
Updated Feb 28, 2015 • Next: Mar 11, 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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