Goodreads for iOS Mobile App Traffic and Demographic Statistics by Quantcast

 

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Rankings

Goodreads Network

Monthly Uniques
16.5M US 34.8M Global

Goodreads for iOS Mobile App

813.6K US 1.3M Global
  •  
  • Quantified

    Directly Measured Data

Related Links


Updated Apr 15, 2014 • Next: Apr 16, 2014 by 9AM PDT
Last Month
For Mar 16, 2014 - Apr 14, 2014
Uniques Visits Installs Upgrades
Goodreads for iOS 2.5.3 (iOS) 489,762 2,059,265 146,705 351,583
Goodreads for iOS 2.5.2 (iOS) 474,073 1,875,205 124,096 76,816
Goodreads for iOS 2.4 (iOS) 32,296 134,277 6,723 2,454
Goodreads for iOS 2.2.5 (iOS) 13,397 52,466 3,187 561
Goodreads for iOS 2.2.4 (iOS) 10,008 39,718 2,240 197
See all 13 versions

US Demographics:   [ Mobile App ]

See All
Summary   ||   Gender   ||   Age   ||   Household   ||   Income   ||   Education   ||   Ethnicity
index
 
 
Male
 
  74
Female
 
 
125
 
 
 
< 18
 
  92
18-24
 
 
131
25-34
 
 
136
35-44
 
 
106
45-54
 
  85
55-64
 
  62
65+
 
  45
 
 
 
No Kids
 
 
126
Has Kids
 
  73
 
US average
index
 
 
$0-50k
 
 
112
$50-100k
 
  91
$100-150k
 
  87
$150k+
 
  79
 
 
 
No College
 
  74
College
 
 
117
Grad School
 
 
131
 
 
 
Caucasian
 
 
110
African American
 
  43
Asian
 
  87
Hispanic
 
  80
Other
 
  97
 
US average


Updated Apr 12, 2014 • Next: Apr 23, 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
412 days total
4,215,312 installs
100%
62%
59%
53%
48%
41%
25%
13%
6 months ago
October 16, 2013
7,633 installs
100%
63%
60%
54%
50%
43%
27%
3 months ago
January 16, 2014
9,716 installs
100%
56%
52%
44%
39%
30%
1 month ago
March 16, 2014
11,775 installs
100%
48%
43%
35%
26%
0%
2 weeks ago
April 2, 2014
9,284 installs
100%
41%
35%
20%
1 week ago
April 9, 2014
9,348 installs
100%
30%
22%

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   191,218
2-3   26,420
4-7   4,551
8-15   1,337
16-31   608
32-63   303
64-127   177
128-255   103
256-511   62
512+   26
1   307,516
2-3   206,021
4-7   118,600
8-15   67,938
16-31   38,443
32-63   22,318
64-127   12,821
128-255   7,476
256-511   4,113
512+   3,354

Top Countries

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

countries Visits % Of Total
1.
United States
4,272,301
64%
2.
United Kingdom
433,145
7%
3.
Canada
419,681
6%
4.
Australia
256,893
4%
5.
Philippines
103,370
2%
6.
Saudi Arabia
97,846
1%
7.
Mexico
70,584
1%
8.
Netherlands
54,191
1%
9.
Germany
50,468
1%
10.
India
47,578
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
172,794
21%
2.
iPhone 4S
143,754
18%
3.
iPhone 5S
100,217
12%
4.
iPad 2
80,637
10%
5.
iPhone 4
71,059
9%
6.
iPhone 5C
45,526
6%
7.
iPad mini
42,672
5%
8.
iPad 4th Gen
38,111
5%
9.
iPad 3rd Gen
36,293
4%
10.
iPod touch
31,677
4%
11.
iPad Air
23,767
3%
12.
iPad mini with Retina display
9,485
1%
13.
iPad
7,909
1%
14.
iPhone 3GS
3,702
<1%
15.
iOS Simulator
16
<1%
See all 15 device models

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

connections Visits % Of Total
1.
WiFi
3,189,839
75%
2.
Cellular Data
1,033,533
24%
3.
No Internet Connection
48,929
1%

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

carriers Visits % Of Total
1.
WiFi
3,189,839
75%
2.
AT&T
454,807
11%
3.
Verizon Wireless
409,203
10%
4.
Sprintcom Inc
107,123
3%
5.
Disconnected
48,929
1%
6.
T-Mobile USA
40,151
1%
7.
Cellular South Inc
5,952
<1%
8.
Virgin Mobile
3,716
<1%
9.
US Cellular
2,642
<1%
10.
Tracfone Wireless
2,239
<1%
11.
Unrecognized Carrier
1,788
<1%
12.
nTELOS Communications Inc (Virginia PCS Alliance LC)
1,289
<1%
13.
Cricket Communications
1,184
<1%
14.
GCI Communications Corp.
717
<1%
15.
Celcom (Malaysia) Berhad
381
<1%
16.
Bluegrass Cellular LLC
278
<1%
17.
Telus Mobility
179
<1%
18.
Bell Mobility
171
<1%
19.
Rogers Wireless
161
<1%
20.
Union Telephone Company
109
<1%
21.
Telstra Corporation Ltd.
97
<1%
22.
Vodafone Network Pty. Ltd.
91
<1%
23.
Cincinnati Bell Wireless LLC
87
<1%
24.
Turkcell
76
<1%
25.
Optus Mobile Pty. Ltd.
72
<1%
26.
Telcel
71
<1%
27.
Nextel Communications Inc
57
<1%
28.
North East Cellular Inc.
54
<1%
29.
Etihad Etisalat Company (Mobily)
44
<1%
30.
SETEL GSM
41
<1%
31.
Telsim GSM
37
<1%
32.
Iusacell / Unefon
31
<1%
33.
Vodafone Libertel N.V.
29
<1%
34.
China Unicom
29
<1%
35.
Fido Solutions
28
<1%
36.
New Mexico RSA 4 East Ltd. Partnership
26
<1%
37.
West Central Wireless
22
<1%
38.
Iowa Wireless Services LLC
20
<1%
39.
MTS Mobility
18
<1%
40.
Vodacom (Pty) Ltd.
17
<1%
41.
Zain Bahrain
16
<1%
42.
T-Mobile UK
16
<1%
43.
Telesc Cel
15
<1%
44.
Base
15
<1%
45.
Saudi Telecom
15
<1%
46.
O2 UK Ltd.
13
<1%
47.
Orange
13
<1%
48.
SD Mobitel
13
<1%
49.
Movistar
11
<1%
50.
STC Bahrain
11
<1%
51.
NTT DoCoMo Hokuriku Inc.
10
<1%
52.
SingTel ST
10
<1%
53.
Vodafone Ltd.
9
<1%
54.
Aria
9
<1%
55.
Starhub
9
<1%
56.
Telkomsel
8
<1%
57.
Vodafone Albania
8
<1%
58.
Comcel S.A. Occel S.A./Celcaribe
8
<1%
59.
Hutchison 3G UK Ltd.
8
<1%
60.
Swisscom Mobile AG
8
<1%
61.
Telcel, C.A.
8
<1%
62.
United Wireless Inc
7
<1%
63.
Cellular Properties Inc.
7
<1%
64.
3G Radio System/Hutchison 3G
7
<1%
65.
MobileOne
7
<1%
66.
Telems Cel
6
<1%
67.
Verizon Dominicana S.A.
6
<1%
68.
Kaplan Telephone Company Inc.
6
<1%
69.
MTN Nigeria Communications
6
<1%
70.
Telemóvil El Salvador, S.A.
5
<1%
71.
olleh Mobile
5
<1%
72.
Du
5
<1%
73.
Digicel Ltd
5
<1%
74.
Mobile Telecommunications Ltd.
5
<1%
75.
Orange Romania
5
<1%
76.
Servicios de Comunicaciones Personales Inalámbricas, S.A.
5
<1%
77.
T-Mobile Czech Republic a.s.
5
<1%
78.
Telecom Personal S.A.
4
<1%
79.
Wataniya Telecom
4
<1%
80.
SaskTel
4
<1%
81.
Advantage Cellular Systems, Inc.
4
<1%
82.
Cellcom Israel Ltd.
4
<1%
83.
EMTS
4
<1%
84.
GSM900/SmarTone
4
<1%
85.
MTPCS LLC
4
<1%
86.
Smart Communications, Inc
4
<1%
87.
Smartcom
4
<1%
88.
T-Mobile Netherlands B.V.
4
<1%
89.
Telecom New Zealand - UMTS Ntework
3
<1%
90.
Telecsa S.A.
3
<1%
91.
Telefónica O2 Czech Republic a.s.
3
<1%
92.
Vodafone Czech Republic a.s.
3
<1%
93.
Vodafone Romania SA
3
<1%
94.
Total Access Communications Co (DTAC)
3
<1%
95.
Colombia Móvil S.A.
3
<1%
96.
Aircell Digilink India Ltd., UP (East)
3
<1%
97.
Etisalat
3
<1%
98.
Mobile Telecommunications Company
3
<1%
99.
MTN Network Ltd.
3
<1%
100.
ATL Algar
3
<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
459,812
57%
2.
iOS / 7.0.6
141,070
17%
3.
iOS / 7.0.4
113,517
14%
4.
iOS / 6.1.3
37,822
5%
5.
iOS / 7.0.3
22,142
3%
6.
iOS / 7.0.2
19,948
2%
7.
iOS / 7.0
18,451
2%
8.
iOS / 6.1.6
14,358
2%
9.
iOS / 5.1.1
12,031
1%
10.
iOS / 6.1.4
6,935
1%
11.
iOS / 6.0.1
5,167
1%
12.
iOS / 6.1.2
3,494
<1%
13.
iOS / 6.1.5
2,624
<1%
14.
iOS / 6.0
2,550
<1%
15.
iOS / 6.1
2,224
<1%
16.
iOS / 6.0.2
699
<1%
17.
iOS / 5.1
572
<1%
18.
iOS / 5.0.1
526
<1%
19.
iOS / 7.0.1
439
<1%
20.
iOS / 4.3.5
227
<1%
21.
iOS / 4.3.3
219
<1%
22.
iOS / 6.1.1
217
<1%
23.
iOS / 5.0
118
<1%
24.
iOS / 4.3.1
33
<1%
25.
iOS / 4.3.2
32
<1%
26.
iOS / 4.3
28
<1%
27.
iOS / 4.3.4
19
<1%
28.
iOS / 7.0.5
18
<1%
29.
iOS / 8.0
6
<1%
30.
iOS / 7.1.1
3
<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)   48%
2.5.2 (iOS)   44%
2.4 (iOS)   3%
2.2.5 (iOS)   1%
2.2.4 (iOS)   1%
2.5.1 (iOS)   1%
2.3 (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
3,588,368
2.
/book_view
2,270,086
3.
/home_jump_screen
1,614,318
4.
/myBooks_view
1,532,452
5.
/search_view
1,523,072
6.
/book_list_view
1,451,831
7.
/shelf
1,198,524
8.
/shelf_picker_view
1,148,105
9.
/updates_view
968,656
10.
/review_view
952,108
11.
/search
838,929
12.
/simple_web_vc
803,525
13.
/notifications
679,986
14.
/ratings
635,653
15.
/author_view
570,562
16.
/user_view
453,830
17.
/progress_view
453,344
18.
/barcode
390,708
19.
/sign_in_welcome
277,354
20.
/explore
260,919
21.
/message_list
257,752
22.
/friends_view
225,550
23.
/topic_show
208,870
24.
/mybooks_search_view
204,812
25.
/challenge_my_status
204,474
26.
/recommendations
197,427
27.
/listType
180,025
28.
/rate_books
166,063
29.
/message_show
155,225
30.
/manageEBooks
147,931
31.
/group_list
145,306
32.
/write_review_view
144,685
33.
/sign_in_view
127,154
34.
/findfriends_choice
110,192
35.
/read_statuses_show
100,849
36.
/recs_genre_selector
91,114
37.
/write_comment_view
89,860
38.
/listEbooks
88,178
39.
/sign_in
86,542
40.
/sign_up_view
80,457
41.
/user_status_show
75,548
42.
/settings_view
75,383
43.
/friends_requests_view
75,180
44.
/fav_genres_edit
73,990
45.
/ereader_view
71,722
46.
/group_show
71,703
47.
/sign_up
69,193
48.
/messages
68,357
49.
/challenge_friends_list
63,109
50.
/friend_requests
57,975
51.
/challenge_signup_page
53,038
52.
/recs_book_info
52,133
53.
/folder_show
48,618
54.
/error
47,335
55.
/rate_books_genre_selector
45,619
56.
/add_fb_friends
43,079
57.
/gr_web_view
40,764
58.
/message_new
35,358
59.
/event_view
31,480
60.
/findfriends
29,008
61.
/profile_photo_edit
27,674
62.
/recs_shelf_selector
27,664
63.
/challenge
21,691
64.
/recommendation_show
21,581
65.
/fb_invites
21,453
66.
/challenge_friend_status
18,007
67.
/likes_unlikes
13,244
68.
/friends_select_view
11,655
69.
/group_search
11,231
70.
/findfriends_fb
11,218
71.
/share_book
10,151
72.
/addressbook_invites
9,608
73.
/rec_book_to_friends
8,080
74.
/bookmark_view
7,334
75.
/eReaderChapters
6,795
76.
/notification_settings
6,181
77.
/book_random
6,098
78.
/fb_sign_in_ask
5,239
79.
/appearance_view
4,977
80.
/fb_sign_in_already_owned
4,884
81.
/recent_reviews
4,419
82.
/listopic_show
2,762
83.
/challenge_enter
2,127
84.
/topic_new
1,312
85.
/list_all_my_shelves
808
86.
/share_challenge
3
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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