Ioffer.com Traffic and Demographic Statistics by Quantcast

 

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Rankings

ioffer.com

Monthly Uniques 2.1M US 8.2M Global
  •  

  • Quantified

    Directly Measured Data

iOffer - The Global Marketplace. Empowering real people to buy, sell and trade in a transparent, negotiable marketplace. In 2002, iOffer revolutionized eCommerce by launching a transparent, negotiable marketplace. Our mission was to disrupt the status quo â?? frenetic and rivalrous auction sitesâ??by empowering real people to buy, sell and trade on their own terms. iOffer has since evolved into the fastest growing destination for interactive social commerce. A vibrant global community, we connect visitors from over 190 countries in every language via millions of item listings. Virtually anything is available through spirited, open negotiationsâ??and if you canâ??t find it, weâ??ll find it for you with a Want Ad! From frugal fashionistas to thrifty gadgeteers, we invite everyone to experience iOffer and bargain on Clothing & Accessories, Electronics, Jewelry, Collectibles, and more.


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Web Demographics


Gender

Embed
segment this site vs. total internet indexmultiple
Male
49% 
49% internet average
  990.99x
Female
51% 
51% internet average
 
1011.01x
internet average
composition
 
 Male 49%
 
 Female 51%

}

Gender

female


Age

Embed
segment this site vs. total internet indexmultiple
< 18
25% 
18% internet average
 
1391.39x
18-24
17% 
12% internet average
 
1341.34x
25-34
19% 
17% internet average
 
1081.08x
35-44
17% 
19% internet average
  890.89x
45-54
13% 
17% internet average
  760.76x
55-64
6% 
10% internet average
  610.61x
65+
3% 
6% internet average
  570.57x
internet average
composition
 
 < 18 25%
 
 18-24 17%
 
 25-34 19%
 
 35-44 17%
 
 45-54 13%
 
 55-64 6%
 
 65+ 3%

}

Age

under 18


Age

Embed
segment this site vs. total internet indexmultiple
Male < 18
12% 
9% internet average
 
1271.27x
Male 18-24
9% 
6% internet average
 
1331.33x
Male 25-34
9% 
9% internet average
 
1061.06x
Male 35-44
8% 
10% internet average
  830.83x
Male 45-54
6% 
9% internet average
  710.71x
Male 55-64
3% 
5% internet average
  570.57x
Male 65+
2% 
2% internet average
  650.65x
internet average
composition
 
 Male < 18 12%
 
 Male 18-24 9%
 
 Male 25-34 9%
 
 Male 35-44 8%
 
 Male 45-54 6%
 
 Male 55-64 3%
 
 Male 65+ 2%

}

Age

male young adults


Age

Embed
segment this site vs. total internet indexmultiple
Female < 18
13% 
9% internet average
 
1511.51x
Female 18-24
8% 
6% internet average
 
1341.34x
Female 25-34
9% 
8% internet average
 
1101.1x
Female 35-44
9% 
9% internet average
  950.95x
Female 45-54
7% 
9% internet average
  810.81x
Female 55-64
3% 
5% internet average
  650.65x
Female 65+
2% 
3% internet average
  520.52x
internet average
composition
 
 Female < 18 13%
 
 Female 18-24 8%
 
 Female 25-34 9%
 
 Female 35-44 9%
 
 Female 45-54 7%
 
 Female 55-64 3%
 
 Female 65+ 2%

}

Age

female under 18


Children in Household

Embed
segment this site vs. total internet indexmultiple
No Kids
59% 
51% internet average
 
1171.17x
Has Kids
41% 
49% internet average
  830.83x
internet average
composition
 
 No Kids 59%
 
 Has Kids 41%

}

Children in Household

no kids


Household Income

Embed
segment this site vs. total internet indexmultiple
$0-50k
61% 
50% internet average
 
1221.22x
$50-100k
24% 
29% internet average
  830.83x
$100-150k
9% 
12% internet average
  710.71x
$150k+
6% 
8% internet average
  700.7x
internet average
composition
 
 $0-50k 61%
 
 $50-100k 24%
 
 $100-150k 9%
 
 $150k+ 6%

}

Household Income

less affluent


Education Level

Embed
segment this site vs. total internet indexmultiple
No College
47% 
45% internet average
 
1041.04x
College
42% 
41% internet average
 
1031.03x
Grad School
11% 
14% internet average
  790.79x
internet average
composition
 
 No College 47%
 
 College 42%
 
 Grad School 11%

}

Education Level

people with no college


Ethnicity

Embed
segment this site vs. total internet indexmultiple
Caucasian
56% 
76% internet average
  740.74x
African American
19% 
9% internet average
2092.09x
Asian
6% 
4% internet average
 
1531.53x
Hispanic
17% 
9% internet average
 
1781.78x
Other
2% 
1% internet average
 
1101.1x
internet average
composition
 
 Caucasian 56%
 
 African American 19%
 
 Asian 6%
 
 Hispanic 17%
 
 Other 2%

}

Ethnicity

African American


Updated May 17, 2013 • Next: May 29, 2013 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 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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