Goodreads for iOS Mobile App Traffic and Demographic Statistics by Quantcast

 

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Rankings

Goodreads Network

Monthly Uniques
16.4M US 34.1M Global

Goodreads for iOS Mobile App

808.6K US 1.3M Global
  •  
  • Quantified

    Directly Measured Data

Related Links


Updated Apr 24, 2014 • Next: Apr 25, 2014 by 9AM PDT
Last Month
For Mar 25, 2014 - Apr 23, 2014
Uniques Visits Installs Upgrades
Goodreads for iOS 2.5.3 (iOS) 628,218 3,165,632 220,370 423,097
Goodreads for iOS 2.5.2 (iOS) 250,568 785,625 42,919 29,287
Goodreads for iOS 2.4 (iOS) 27,605 115,002 5,924 1,920
Goodreads for iOS 2.2.5 (iOS) 12,167 47,835 2,840 489
Goodreads for iOS 2.2.4 (iOS) 9,282 36,852 2,014 174
See all 13 versions

US Demographics:   [ Mobile App ]

See All
Summary   ||   Gender   ||   Age   ||   Household   ||   Income   ||   Education   ||   Ethnicity
index
 
 
Male
 
  77
Female
 
 
122
 
 
 
< 18
 
  69
18-24
 
 
153
25-34
 
 
131
35-44
 
 
114
45-54
 
  85
55-64
 
  62
65+
 
  53
 
 
 
No Kids
 
 
119
Has Kids
 
  81
 
US average
index
 
 
$0-50k
 
 
112
$50-100k
 
  94
$100-150k
 
  85
$150k+
 
  72
 
 
 
No College
 
  73
College
 
 
128
Grad School
 
 
104
 
 
 
Caucasian
 
 
107
African American
 
  45
Asian
 
 
110
Hispanic
 
  92
Other
 
  93
 
US average


Updated Apr 23, 2014 • Next: Apr 30, 2014 by 9AM PDT

User Retention After Install

Percentage of visitors returning to the mobile app within a specific timeframe after the installation date. Click the expand button under graph to see usage patterns for specific installation days.

Date of Installation Install Day +2 Days +3 Days +1 Week +2 Weeks +1 Month +3 Months +6 Months
Average Day
421 days total
4,298,264 installs
100%
62%
59%
53%
48%
41%
25%
13%
6 months ago
October 25, 2013
6,225 installs
100%
63%
61%
55%
51%
43%
29%
3 months ago
January 25, 2014
10,777 installs
100%
55%
51%
44%
39%
31%
1 month ago
March 25, 2014
10,022 installs
100%
49%
43%
33%
25%
2 weeks ago
April 11, 2014
7,945 installs
100%
39%
33%
18%
1 week ago
April 18, 2014
8,708 installs
100%
33%
24%

Visit Frequency

The number of non-logged-in unique users grouped by their return visit counts over the last 30 days.

The number of logged-in unique users grouped by their return visit counts over the last 30 days.

Visits Not Logged In | Logged In
1   185,797
2-3   24,882
4-7   4,375
8-15   1,263
16-31   589
32-63   299
64-127   163
128-255   113
256-511   54
512+   32
1   316,380
2-3   200,890
4-7   112,144
8-15   65,232
16-31   37,773
32-63   22,147
64-127   12,739
128-255   7,420
256-511   4,097
512+   3,395

Top Countries

The number of visits per country over the last 30 days.

countries Visits % Of Total
1.
United States
4,246,449
64%
2.
United Kingdom
438,643
7%
3.
Canada
422,128
6%
4.
Australia
265,774
4%
5.
Philippines
110,283
2%
6.
Saudi Arabia
92,122
1%
7.
Mexico
74,293
1%
8.
Netherlands
53,312
1%
9.
Germany
51,231
1%
10.
India
46,930
1%

Top Device Models | Connections | Carriers | OS Versions

The number of unique users per device over the last 30 days.

device models Uniques % Of Total
1.
iPhone 5
170,478
21%
2.
iPhone 4S
141,812
18%
3.
iPhone 5S
102,371
13%
4.
iPad 2
78,398
10%
5.
iPhone 4
69,181
9%
6.
iPhone 5C
46,537
6%
7.
iPad mini
41,997
5%
8.
iPad 4th Gen
37,503
5%
9.
iPad 3rd Gen
35,538
4%
10.
iPod touch
31,112
4%
11.
iPad Air
23,602
3%
12.
iPad mini with Retina display
9,536
1%
13.
iPad
7,617
1%
14.
iPhone 3GS
3,512
<1%
15.
iOS Simulator
9
<1%
See all 15 device models

The number of visits per connection type over the last 30 days.

connections Visits % Of Total
1.
WiFi
3,158,651
74%
2.
Cellular Data
1,037,890
24%
3.
No Internet Connection
49,908
1%

The number of visits per carrier type over the last 30 days.

carriers Visits % Of Total
1.
WiFi
3,158,651
74%
2.
AT&T
456,024
11%
3.
Verizon Wireless
411,686
10%
4.
Sprintcom Inc
107,262
3%
5.
Disconnected
49,908
1%
6.
T-Mobile USA
40,697
1%
7.
Cellular South Inc
5,896
<1%
8.
Virgin Mobile
3,750
<1%
9.
US Cellular
2,804
<1%
10.
Tracfone Wireless
2,206
<1%
11.
Unrecognized Carrier
1,798
<1%
12.
nTELOS Communications Inc (Virginia PCS Alliance LC)
1,304
<1%
13.
Cricket Communications
1,072
<1%
14.
GCI Communications Corp.
757
<1%
15.
Celcom (Malaysia) Berhad
389
<1%
16.
Bluegrass Cellular LLC
288
<1%
17.
Telus Mobility
170
<1%
18.
Rogers Wireless
169
<1%
19.
Bell Mobility
169
<1%
20.
Vodafone Network Pty. Ltd.
102
<1%
21.
Union Telephone Company
92
<1%
22.
Cincinnati Bell Wireless LLC
89
<1%
23.
Telstra Corporation Ltd.
77
<1%
24.
Telcel
74
<1%
25.
North East Cellular Inc.
58
<1%
26.
Optus Mobile Pty. Ltd.
57
<1%
27.
Turkcell
56
<1%
28.
Etihad Etisalat Company (Mobily)
47
<1%
29.
Vodafone Libertel N.V.
41
<1%
30.
Nextel Communications Inc
41
<1%
31.
Fido Solutions
40
<1%
32.
SETEL GSM
39
<1%
33.
New Mexico RSA 4 East Ltd. Partnership
34
<1%
34.
Telsim GSM
31
<1%
35.
Iusacell / Unefon
30
<1%
36.
China Unicom
27
<1%
37.
West Central Wireless
24
<1%
38.
Iowa Wireless Services LLC
23
<1%
39.
MTS Mobility
23
<1%
40.
Telesc Cel
19
<1%
41.
Vodacom (Pty) Ltd.
18
<1%
42.
Saudi Telecom
17
<1%
43.
Base
16
<1%
44.
Movistar
13
<1%
45.
United Wireless Inc
12
<1%
46.
SD Mobitel
12
<1%
47.
Telkomsel
9
<1%
48.
Zain Bahrain
9
<1%
49.
Hutchison 3G UK Ltd.
9
<1%
50.
NTT DoCoMo Hokuriku Inc.
9
<1%
51.
STC Bahrain
9
<1%
52.
T-Mobile UK
9
<1%
53.
Telefónica Móviles España, SAU
8
<1%
54.
Vodafone Albania
8
<1%
55.
Vodafone Ltd.
8
<1%
56.
Aria
8
<1%
57.
MTN Network Ltd.
8
<1%
58.
O2 UK Ltd.
8
<1%
59.
Orange
8
<1%
60.
Telems Cel
7
<1%
61.
Comcel S.A. Occel S.A./Celcaribe
7
<1%
62.
Telecom New Zealand - UMTS Ntework
6
<1%
63.
Verizon Dominicana S.A.
6
<1%
64.
Cellular Properties Inc.
6
<1%
65.
Celtel
6
<1%
66.
Digicel Ltd
6
<1%
67.
Kaplan Telephone Company Inc.
6
<1%
68.
MTN Nigeria Communications
6
<1%
69.
Du
5
<1%
70.
Colombia Móvil S.A.
5
<1%
71.
Mobile Telecommunications Ltd.
5
<1%
72.
Servicios de Comunicaciones Personales Inalámbricas, S.A.
5
<1%
73.
Telemóvil El Salvador, S.A.
4
<1%
74.
Wataniya Telecom
4
<1%
75.
SaskTel
4
<1%
76.
Advantage Cellular Systems, Inc.
4
<1%
77.
MTPCS LLC
4
<1%
78.
BATELCO
4
<1%
79.
Starhub
4
<1%
80.
T-Mobile Deutschland GmbH
4
<1%
81.
Vodafone Czech Republic a.s.
3
<1%
82.
Vodafone Romania SA
3
<1%
83.
olleh Mobile
3
<1%
84.
Claro Puerto Rico
3
<1%
85.
Cellcom Israel Ltd.
3
<1%
86.
China Mobile
3
<1%
87.
EMTS
3
<1%
88.
Areeba-Sudan
3
<1%
89.
ATL Algar
3
<1%
90.
Orange Romania
3
<1%
91.
Smart Communications, Inc
3
<1%
92.
Swisscom Mobile AG
3
<1%
93.
T-Mobile Czech Republic a.s.
3
<1%
94.
Telcel, C.A.
3
<1%
95.
Teleacre Cel
3
<1%
96.
Telecommunication Company of Iran (TCI)
2
<1%
97.
Tess
2
<1%
98.
Total Access Communications Co (DTAC)
2
<1%
99.
3 Ireland
2
<1%
100.
Entel Telefónica Móvil
2
<1%
See top 100 carriers

The number of unique users per operating system over the last 30 days.

OS versions Uniques % Of Total
1.
iOS / 7.1
491,254
61%
2.
iOS / 7.0.4
98,447
12%
3.
iOS / 7.0.6
94,154
12%
4.
iOS / 6.1.3
35,239
4%
5.
iOS / 7.0.3
20,452
3%
6.
iOS / 7.0.2
18,484
2%
7.
iOS / 7.0
17,309
2%
8.
iOS / 6.1.6
14,307
2%
9.
iOS / 5.1.1
11,527
1%
10.
iOS / 7.1.1
7,496
1%
11.
iOS / 6.1.4
6,619
1%
12.
iOS / 6.0.1
4,911
1%
13.
iOS / 6.1.2
3,237
<1%
14.
iOS / 6.0
2,471
<1%
15.
iOS / 6.1.5
2,255
<1%
16.
iOS / 6.1
2,123
<1%
17.
iOS / 6.0.2
674
<1%
18.
iOS / 5.1
531
<1%
19.
iOS / 5.0.1
510
<1%
20.
iOS / 7.0.1
401
<1%
21.
iOS / 4.3.3
219
<1%
22.
iOS / 4.3.5
216
<1%
23.
iOS / 6.1.1
203
<1%
24.
iOS / 5.0
119
<1%
25.
iOS / 4.3.1
31
<1%
26.
iOS / 4.3.2
30
<1%
27.
iOS / 4.3
24
<1%
28.
iOS / 4.3.4
18
<1%
29.
iOS / 7.0.5
17
<1%
30.
iOS / 8.0
7
<1%
See all 30 OS versions

Visit Sources

The percentage of visits from all apps in this network in the past 30 days.

The percentage of visits to Goodreads for iOS by version in the past 30 days.

Mobile Apps | Versions of Goodreads for …
Goodreads for iOS   69%
Goodreads for Android   31%
2.5.3 (iOS)   75%
2.5.2 (iOS)   19%
2.4 (iOS)   3%
2.2.5 (iOS)   1%
2.2.4 (iOS)   1%
2.3 (iOS)   1%
2.5.1 (iOS)   1%
2.2.3 (iOS)   <1%
2.5 (iOS)   <1%
2.2.1 (iOS)   <1%

Top Events

Custom app event totals from Goodreads for iOS in the past 30 days.

events Counts
1.
/launched
3,574,200
2.
/home_jump_screen
2,482,774
3.
/book_view
2,257,962
4.
/search_view
1,515,915
5.
/myBooks_view
1,515,271
6.
/book_list_view
1,438,665
7.
/search
1,296,366
8.
/shelf
1,229,803
9.
/shelf_picker_view
1,137,908
10.
/updates_view
956,894
11.
/review_view
945,277
12.
/simple_web_vc
807,296
13.
/notifications
678,919
14.
/ratings
640,962
15.
/author_view
569,781
16.
/progress_view
449,696
17.
/user_view
444,581
18.
/barcode
385,115
19.
/sign_in_welcome
269,142
20.
/message_list
261,913
21.
/explore
256,971
22.
/friends_view
220,868
23.
/topic_show
210,744
24.
/challenge_my_status
205,014
25.
/rate_books
201,704
26.
/mybooks_search_view
201,018
27.
/recommendations
196,513
28.
/listType
177,762
29.
/message_show
159,988
30.
/group_list
143,536
31.
/manageEBooks
143,206
32.
/write_review_view
142,741
33.
/sign_in_view
122,247
34.
/findfriends_choice
105,592
35.
/read_statuses_show
100,207
36.
/write_comment_view
90,957
37.
/recs_genre_selector
90,787
38.
/listEbooks
85,908
39.
/sign_in
84,121
40.
/sign_up_view
77,568
41.
/fav_genres_edit
77,342
42.
/user_status_show
76,885
43.
/friends_requests_view
73,694
44.
/settings_view
73,629
45.
/messages
72,181
46.
/group_show
71,531
47.
/ereader_view
69,581
48.
/sign_up
66,711
49.
/challenge_friends_list
61,495
50.
/gr_web_view
61,487
51.
/friend_requests
56,795
52.
/recs_book_info
52,751
53.
/challenge_signup_page
50,675
54.
/folder_show
48,534
55.
/rate_books_genre_selector
46,622
56.
/error
43,058
57.
/add_fb_friends
40,795
58.
/message_new
37,373
59.
/event_view
30,707
60.
/profile_photo_edit
27,637
61.
/recs_shelf_selector
27,632
62.
/findfriends
27,339
63.
/fb_invites
23,563
64.
/recommendation_show
20,807
65.
/challenge
20,661
66.
/challenge_friend_status
16,473
67.
/likes_unlikes
12,973
68.
/findfriends_fb
12,258
69.
/friends_select_view
11,776
70.
/group_search
11,202
71.
/share_book
9,981
72.
/addressbook_invites
8,962
73.
/rec_book_to_friends
7,959
74.
/bookmark_view
6,862
75.
/eReaderChapters
6,552
76.
/notification_settings
6,303
77.
/book_random
5,965
78.
/fb_sign_in_ask
4,851
79.
/appearance_view
4,670
80.
/fb_sign_in_already_owned
4,475
81.
/recent_reviews
4,131
82.
/listopic_show
2,744
83.
/challenge_enter
1,588
84.
/topic_new
1,292
85.
/list_all_my_shelves
803
86.
/share_challenge
2
See all 86 events

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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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