Goodreads for iOS Mobile App Traffic and Demographic Statistics by Quantcast

 

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Rankings

Goodreads Network

Monthly Uniques
18.1M US 38.2M Global

Goodreads for iOS Mobile App

813.5K US 1.3M Global
  •  

  • Quantified

    Directly Measured Data

Related Links


Updated Mar 8, 2014 • Next: Mar 9, 2014 by 9AM PDT
Last Month
For Feb 6, 2014 - Mar 7, 2014 		Uniques Visits Installs Upgrades
Goodreads for iOS 2.5.2 (iOS) 581,488 2,739,527 213,887 386,907
Goodreads for iOS 2.5.1 (iOS) 239,251 733,749 50,130 140,903
Goodreads for iOS 2.4 (iOS) 105,089 428,442 18,767 11,168
Goodreads for iOS 2.5 (iOS) 29,694 100,544 4,194 12,624
Goodreads for iOS 2.2.5 (iOS) 20,118 80,407 4,650 1,103
See all 13 versions

US Demographics:   [ Mobile App ]

See All
Summary   ||   Gender   ||   Age   ||   Household   ||   Income   ||   Education   ||   Ethnicity
index
 
 
 Male
 
  67
Female
 
 
131
 
 
 
 < 18
 
  93
18-24
 
 
124
25-34
 
 
140
35-44
 
 
105
45-54
 
  82
55-64
 
  64
65+
 
  46
 
 
 
 No Kids
 
 
125
Has Kids
 
  74
 
US average
index
 
 
 $0-50k
 
  96
$50-100k
 
 
108
$100-150k
 
 
101
$150k+
 
  92
 
 
 
 No College
 
  94
College
 
 
102
Grad School
 
 
114
 
 
 
 Caucasian
 
 
110
African American
 
  46
Asian
 
  81
Hispanic
 
  79
Other
 
  97
 
US average


Updated Mar 7, 2014 • Next: Mar 19, 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
374 days total
3,843,193 installs
100%
63%
59%
53%
48%
41%
25%
12%
6 months ago
September 9, 2013
8,431 installs
100%
56%
52%
45%
39%
33%
19%
—
3 months ago
December 9, 2013
8,344 installs
100%
57%
53%
46%
41%
33%
—
—
1 month ago
February 9, 2014
11,635 installs
100%
46%
41%
32%
23%
—
—
—
2 weeks ago
February 23, 2014
11,670 installs
100%
39%
34%
20%
—
—
—
—
1 week ago
March 2, 2014
12,830 installs
100%
29%
21%
—
—
—
—
—

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   199,679
2-3   27,570
4-7   4,737
8-15   1,302
16-31   555
32-63   292
64-127   151
128-255   97
256-511   56
512+   30
1   323,596
2-3   209,521
4-7   116,313
8-15   65,705
16-31   36,384
32-63   20,809
64-127   11,758
128-255   6,668
256-511   3,759
512+   2,954

Top Countries

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

countries Visits % Of Total
1.
United States
4,229,333
65%
2.
United Kingdom
421,217
6%
3.
Canada
395,110
6%
4.
Australia
252,718
4%
5.
Philippines
92,026
1%
6.
Saudi Arabia
91,086
1%
7.
Mexico
68,370
1%
8.
Netherlands
53,431
1%
9.
Germany
48,773
1%
10.
India
44,189
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
178,539
22%
2.
iPhone 4S
154,675
19%
3.
iPad 2
85,834
11%
4.
iPhone 5S
85,239
10%
5.
iPhone 4
76,521
9%
6.
iPad mini
44,334
5%
7.
iPad 4th Gen
40,017
5%
8.
iPad 3rd Gen
38,393
5%
9.
iPhone 5C
37,320
5%
10.
iPod touch
31,529
4%
11.
iPad Air
22,004
3%
12.
iPad mini with Retina display
8,782
1%
13.
iPad
8,754
1%
14.
iPhone 3GS
4,296
1%
15.
iOS Simulator
26
<1%
See all 15 device models

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

connections Visits % Of Total
1.
WiFi
3,200,913
76%
2.
Cellular Data
981,349
23%
3.
No Internet Connection
47,071
1%

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

carriers Visits % Of Total
1.
WiFi
3,200,913
76%
2.
AT&T
432,301
10%
3.
Verizon Wireless
390,895
9%
4.
Sprintcom Inc
102,092
2%
5.
Disconnected
47,071
1%
6.
T-Mobile USA
35,072
1%
7.
Cellular South Inc
5,544
<1%
8.
Virgin Mobile
3,710
<1%
9.
US Cellular
2,299
<1%
10.
Tracfone Wireless
2,135
<1%
11.
Unrecognized Carrier
1,899
<1%
12.
nTELOS Communications Inc (Virginia PCS Alliance LC)
1,115
<1%
13.
Cricket Communications
975
<1%
14.
GCI Communications Corp.
536
<1%
15.
Celcom (Malaysia) Berhad
367
<1%
16.
Bluegrass Cellular LLC
227
<1%
17.
Bell Mobility
210
<1%
18.
Telus Mobility
198
<1%
19.
Rogers Wireless
145
<1%
20.
Telstra Corporation Ltd.
139
<1%
21.
Union Telephone Company
114
<1%
22.
Cincinnati Bell Wireless LLC
92
<1%
23.
Optus Mobile Pty. Ltd.
86
<1%
24.
Telcel
79
<1%
25.
North East Cellular Inc.
69
<1%
26.
Vodafone Libertel N.V.
66
<1%
27.
Iusacell / Unefon
53
<1%
28.
Nextel Communications Inc
50
<1%
29.
Telfort B.V.
43
<1%
30.
SingTel ST
39
<1%
31.
Vodafone Network Pty. Ltd.
37
<1%
32.
West Central Wireless
30
<1%
33.
Etisalat
28
<1%
34.
Vodafone Albania
27
<1%
35.
Fido Solutions
27
<1%
36.
SETEL GSM
25
<1%
37.
China Unicom
22
<1%
38.
Telesc Cel
21
<1%
39.
Iowa Wireless Services LLC
21
<1%
40.
New Mexico RSA 4 East Ltd. Partnership
21
<1%
41.
NTT DoCoMo Hokuriku Inc.
21
<1%
42.
SD Mobitel
21
<1%
43.
O2 UK Ltd.
19
<1%
44.
Orange
19
<1%
45.
Etihad Etisalat Company (Mobily)
18
<1%
46.
Areeba-Sudan
18
<1%
47.
Malaysian Mobile Services Sdn Bhd
18
<1%
48.
MobileOne
18
<1%
49.
Starhub
17
<1%
50.
Saudi Telecom
15
<1%
51.
T-Mobile UK
14
<1%
52.
Telkomsel
13
<1%
53.
3G Radio System/Hutchison 3G
13
<1%
54.
Comcel S.A. Occel S.A./Celcaribe
12
<1%
55.
Hutchinson Essar Ltd, Mumbai
12
<1%
56.
Base
12
<1%
57.
Swisscom Mobile AG
12
<1%
58.
Cellular Properties Inc.
11
<1%
59.
Globe Telecom
11
<1%
60.
Du
10
<1%
61.
MTS Mobility
10
<1%
62.
Telcel, C.A.
10
<1%
63.
Vodafone New Zealand GSM Network
9
<1%
64.
Telecom New Zealand - UMTS Ntework
6
<1%
65.
T-Mobile Czech Republic a.s.
6
<1%
66.
Telest Cel
5
<1%
67.
Vodacom (Pty) Ltd.
5
<1%
68.
SaskTel
5
<1%
69.
olleh Mobile
5
<1%
70.
Celtel (T) Ltd.
5
<1%
71.
Mobile Telecommunications Company
5
<1%
72.
MTN Nigeria Communications
5
<1%
73.
MTPCS LLC
5
<1%
74.
Telefónica O2 Czech Republic a.s.
4
<1%
75.
Tess
4
<1%
76.
Turkcell
4
<1%
77.
Vodafone Czech Republic a.s.
4
<1%
78.
Vodafone Ltd.
4
<1%
79.
Zain Bahrain
4
<1%
80.
3 Ireland
4
<1%
81.
GoMobile SamoaTel Ltd
4
<1%
82.
Movistar
4
<1%
83.
Omnitel Pronto Italia (OPI)
4
<1%
84.
Roshan
4
<1%
85.
Telecsa S.A.
3
<1%
86.
Telefónica Móviles Colombia S.A.
3
<1%
87.
Telekom Network Ltd.
3
<1%
88.
Bharti Airtel Ltd., Delhi
3
<1%
89.
Three
3
<1%
90.
Claro Puerto Rico
3
<1%
91.
Airadigm Communications
3
<1%
92.
Instituto Costarricense de Electricidad - ICE
3
<1%
93.
Mobile Telephone Networks (MTN) Pty Ltd
3
<1%
94.
NZ Communications - UMTS Network
3
<1%
95.
Oman Qatari Telecommunications Company (Nawras)
3
<1%
96.
Orange Austria Telecommunication GmbH
3
<1%
97.
Orange Romania
3
<1%
98.
Tele2 Sverige AB
3
<1%
99.
Telefónica Móviles España, SAU
2
<1%
100.
Viva
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 / 7.0.4
516,821
64%
2.
iOS / 7.0.6
246,689
30%
3.
iOS / 6.1.3
50,453
6%
4.
iOS / 7.0.3
38,916
5%
5.
iOS / 7.0.2
29,703
4%
6.
iOS / 7.0
25,705
3%
7.
iOS / 5.1.1
13,453
2%
8.
iOS / 6.1.5
11,188
1%
9.
iOS / 6.1.4
9,216
1%
10.
iOS / 6.1.6
6,837
1%
11.
iOS / 6.0.1
6,342
1%
12.
iOS / 6.1.2
4,351
1%
13.
iOS / 6.0
3,228
<1%
14.
iOS / 6.1
2,724
<1%
15.
iOS / 6.0.2
868
<1%
16.
iOS / 5.0.1
703
<1%
17.
iOS / 5.1
677
<1%
18.
iOS / 7.0.1
598
<1%
19.
iOS / 7.1
332
<1%
20.
iOS / 4.3.3
262
<1%
21.
iOS / 6.1.1
261
<1%
22.
iOS / 4.3.5
259
<1%
23.
iOS / 7.0.5
150
<1%
24.
iOS / 5.0
139
<1%
25.
iOS / 4.3.2
45
<1%
26.
iOS / 4.3
31
<1%
27.
iOS / 4.3.1
31
<1%
28.
iOS / 4.3.4
15
<1%
29.
iOS / 8.0
2
<1%
See all 29 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%
2.5.2 (iOS)   65%
2.5.1 (iOS)   17%
2.4 (iOS)   10%
2.5 (iOS)   2%
2.2.5 (iOS)   2%
2.3 (iOS)   1%
2.2.4 (iOS)   1%
2.2.3 (iOS)   1%
2.2.1 (iOS)   <1%
2.2.2 (iOS)   <1%

Top Events

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

events Counts
1.
/launched
3,547,669
2.
/book_view
2,215,977
3.
/myBooks_view
1,508,823
4.
/search_view
1,483,942
5.
/book_list_view
1,425,833
6.
/shelf_picker_view
1,121,479
7.
/shelf
1,093,530
8.
/updates_view
972,355
9.
/review_view
933,694
10.
/simple_web_vc
772,715
11.
/notifications
693,627
12.
/author_view
562,226
13.
/user_view
474,725
14.
/progress_view
446,224
15.
/ratings
430,178
16.
/barcode
387,946
17.
/sign_in_welcome
284,758
18.
/explore
265,092
19.
/message_list
243,408
20.
/friends_view
234,981
21.
/topic_show
215,396
22.
/mybooks_search_view
200,312
23.
/challenge_my_status
194,719
24.
/recommendations
185,431
25.
/listType
181,719
26.
/manageEBooks
158,848
27.
/group_list
153,931
28.
/write_review_view
143,237
29.
/message_show
143,006
30.
/sign_in_view
137,512
31.
/findfriends_choice
116,465
32.
/read_statuses_show
101,107
33.
/listEbooks
93,090
34.
/sign_in
90,789
35.
/write_comment_view
90,655
36.
/rate_books
88,036
37.
/recs_genre_selector
85,139
38.
/sign_up_view
83,086
39.
/settings_view
80,234
40.
/ereader_view
80,205
41.
/friends_requests_view
77,845
42.
/group_show
75,755
43.
/sign_up
71,475
44.
/user_status_show
70,476
45.
/messages
69,161
46.
/fav_genres_edit
64,151
47.
/friend_requests
60,330
48.
/challenge_friends_list
54,157
49.
/error
53,600
50.
/folder_show
52,250
51.
/challenge_signup_page
49,644
52.
/challenge_enter
49,279
53.
/recs_book_info
48,228
54.
/add_fb_friends
47,148
55.
/rate_books_genre_selector
41,444
56.
/message_new
35,872
57.
/event_view
33,544
58.
/findfriends
31,984
59.
/profile_photo_edit
29,516
60.
/recs_shelf_selector
25,348
61.
/challenge_friend_status
23,403
62.
/challenge
23,020
63.
/recommendation_show
20,699
64.
/fb_invites
16,751
65.
/likes_unlikes
13,242
66.
/friends_select_view
11,783
67.
/group_search
11,388
68.
/addressbook_invites
10,821
69.
/share_book
10,530
70.
/bookmark_view
8,653
71.
/findfriends_fb
8,626
72.
/rec_book_to_friends
8,479
73.
/eReaderChapters
7,565
74.
/notification_settings
6,497
75.
/book_random
6,060
76.
/fb_sign_in_ask
5,915
77.
/fb_sign_in_already_owned
5,639
78.
/appearance_view
5,611
79.
/recent_reviews
4,345
80.
/listopic_show
2,995
81.
/topic_new
1,346
82.
/list_all_my_shelves
916
83.
/share_challenge
283
84.
/search
10
85.
/book_search
3
See all 85 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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