The aim is to find profiles that are profitable for the App Store and Google Play markets. The Goal is to help developers make data-driven decisions involving the kinds of Apps they build.
Our company only builds free apps wiwth main source of revenue with in-app ads. The goal again is to analyze data to help developers which types of Apps attract more users on Google Play and the App Store.
We are using approximately 10,000 Android Apps and 7,000 iOS apps as our sample data for analysis.
from csv import reader
### Android Dataset ###
opened_file = open('datasets/googleplaystore.csv', encoding='utf-8')
read_file = reader(opened_file)
android = list(read_file)
android_header = android[0]
android = android[1:]
### iOS Dataset ###
opened_file = open('datasets/AppleStore.csv', encoding='utf-8')
read_file = reader(opened_file)
ios = list(read_file)
ios_header = ios[0]
ios = ios[1:]
def explore_data(dataset, start, end, rows_and_columns=False):
dataset_slice = dataset[start:end]
for row in dataset_slice:
print(row)
print('\n')
if rows_and_columns:
print('Number of rows: ', len(dataset))
print('Number of columns: ', len(dataset[0]))
Sample Exploration
print(f'Android Data\n{android_header}\n\n')
explore_data(android, 0, 2, True)
print(f'iOS Data\n{ios_header}\n\n')
explore_data(ios, 0, 2, True)
Android Data ['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver'] ['Photo Editor & Candy Camera & Grid & ScrapBook', 'ART_AND_DESIGN', '4.1', '159', '19M', '10,000+', 'Free', '0', 'Everyone', 'Art & Design', 'January 7, 2018', '1.0.0', '4.0.3 and up'] ['Coloring book moana', 'ART_AND_DESIGN', '3.9', '967', '14M', '500,000+', 'Free', '0', 'Everyone', 'Art & Design;Pretend Play', 'January 15, 2018', '2.0.0', '4.0.3 and up'] Number of rows: 10841 Number of columns: 13 iOS Data ['id', 'track_name', 'size_bytes', 'currency', 'price', 'rating_count_tot', 'rating_count_ver', 'user_rating', 'user_rating_ver', 'ver', 'cont_rating', 'prime_genre', 'sup_devices.num', 'ipadSc_urls.num', 'lang.num', 'vpp_lic'] ['284882215', 'Facebook', '389879808', 'USD', '0.0', '2974676', '212', '3.5', '3.5', '95.0', '4+', 'Social Networking', '37', '1', '29', '1'] ['389801252', 'Instagram', '113954816', 'USD', '0.0', '2161558', '1289', '4.5', '4.0', '10.23', '12+', 'Photo & Video', '37', '0', '29', '1'] Number of rows: 7197 Number of columns: 16
There is a wrong entry for 10473th row as the rating is 19 when it's supposed to be out of 5. We are also going to delete non-English apps and non-free apps.
print(android_header)
print('\n')
print(android[10472])
['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver'] ['Life Made WI-Fi Touchscreen Photo Frame', '1.9', '19', '3.0M', '1,000+', 'Free', '0', 'Everyone', '', 'February 11, 2018', '1.0.19', '4.0 and up']
print(len(android))
# If statement just to make sure we don't delete another row by accident
if android[10472][0] == 'Life Made WI-FI Touchscreen Photo Frame':
del android[10472] # only run this once
print(len(android))
10840 10840
See if that row is gone:
print(android_header)
print('\n')
print(android[10472])
['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver'] ['osmino Wi-Fi: free WiFi', 'TOOLS', '4.2', '134203', '4.1M', '10,000,000+', 'Free', '0', 'Everyone', 'Tools', 'August 7, 2018', '6.06.14', '4.4 and up']
duplicate_apps = []
unique_apps = []
for app in android:
name = app[0]
if name in unique_apps:
duplicate_apps.append(name)
else:
unique_apps.append(name)
print(f'Number of dupilicate apps: {len(duplicate_apps)}')
print('\n')
print('Examples of duplicate apps:', duplicate_apps[:5])
Number of dupilicate apps: 1181 Examples of duplicate apps: ['Quick PDF Scanner + OCR FREE', 'Box', 'Google My Business', 'ZOOM Cloud Meetings', 'join.me - Simple Meetings']
Higher the number of reviews, the more recent the data should be. Let's keep only the row with the highest number of reviews and remove the other entries for any given app.
android_header
['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver']
# Reviews are in index 3
reviews_max = {}
for app in android:
name = app[0]
n_reviews = float(app[3])
# If duplicate has less than current reviews,
# the dupilicate's reviews equals the current reviews (max reviews)
if name in reviews_max and reviews_max[name] < n_reviews:
reviews_max[name] = n_reviews
elif name not in reviews_max:
reviews_max[name] = n_reviews
# Our original length - 1181(duplicates)
# should equal the dictionary reviews_max length
print(f'Expected length: {len(android) - 1181}')
print(f'Actual length: {len(reviews_max)}')
Expected length: 9659 Actual length: 9659
Now we can use reviews_max
dictionary to remove the duplicates. For the duplicate cases, we'll only keep the entries with the highest number of reviews. We need to take account the case where duplicates have the same number of reviews. (but what about the duplicates with the same number of reviews and different data in other parameters?)
android_clean = []
already_added = []
for app in android:
name = app[0]
n_reviews = float(app[3])
if (reviews_max[name] == n_reviews) and (name not in already_added):
android_clean.append(app)
already_added.append(name) # make sure this is inside of the if block
Let's quickly explore the new data set and confirm the number of rows is 9,659.
explore_data(android_clean, 0, 2, True)
['Photo Editor & Candy Camera & Grid & ScrapBook', 'ART_AND_DESIGN', '4.1', '159', '19M', '10,000+', 'Free', '0', 'Everyone', 'Art & Design', 'January 7, 2018', '1.0.0', '4.0.3 and up'] ['U Launcher Lite – FREE Live Cool Themes, Hide Apps', 'ART_AND_DESIGN', '4.7', '87510', '8.7M', '5,000,000+', 'Free', '0', 'Everyone', 'Art & Design', 'August 1, 2018', '1.2.4', '4.0.3 and up'] Number of rows: 9659 Number of columns: 13
9659 rows confirmed.
Some apps are not directed toward English-speaking audience.
def is_english(string):
non_ascii = 0
for character in string:
if ord(character) > 127:
non_ascii += 1
if non_ascii > 3:
return False
else:
return True
print(is_english('Docs To Go™ Free Office Suite'))
print(is_english('Instachat 😜'))
True True
Although very few apps might get past this filter, for now it is good enough.
Below, we use is_english()
function to filter out the non-English apps for both datasets
android_english = []
ios_english = []
for app in android_clean:
name = app[0]
if is_english(name):
android_english.append(app)
for app in ios:
name = app[1]
if is_english(name):
ios_english.append(app)
explore_data(android_english, 0, 2, True)
print('\n')
explore_data(ios_english, 0, 2, True)
['Photo Editor & Candy Camera & Grid & ScrapBook', 'ART_AND_DESIGN', '4.1', '159', '19M', '10,000+', 'Free', '0', 'Everyone', 'Art & Design', 'January 7, 2018', '1.0.0', '4.0.3 and up'] ['U Launcher Lite – FREE Live Cool Themes, Hide Apps', 'ART_AND_DESIGN', '4.7', '87510', '8.7M', '5,000,000+', 'Free', '0', 'Everyone', 'Art & Design', 'August 1, 2018', '1.2.4', '4.0.3 and up'] Number of rows: 9614 Number of columns: 13 ['284882215', 'Facebook', '389879808', 'USD', '0.0', '2974676', '212', '3.5', '3.5', '95.0', '4+', 'Social Networking', '37', '1', '29', '1'] ['389801252', 'Instagram', '113954816', 'USD', '0.0', '2161558', '1289', '4.5', '4.0', '10.23', '12+', 'Photo & Video', '37', '0', '29', '1'] Number of rows: 6183 Number of columns: 16
android_final = []
ios_final = []
for app in android_english:
price = app[7]
if price == '0':
android_final.append(app)
for app in ios_english:
price = app[4]
if price == '0.0':
ios_final.append(app)
print(len(android_final))
print(len(ios_final))
8864 3222
We're left with 8864 Android apps and 3222 iOS apps, which should be enough for our analysis.
As mentioned in the introduction, our goal is to determine kinds of apps that are likely to attract more users.
To minimize risks and overhead, our validation strategy for an app idea is comprised of three steps:
Because our end goal is to add the App on both markets, we need to find app profiles that are successful on both markets.
Let's begin the anaysis by getting a sense of the most common genres for each market.
def freq_table(dataset, index):
table = {}
total = 0
for row in dataset:
total += 1
value = row[index]
if value in table:
table[value] += 1
else:
table[value] = 1
table_percentages = {}
for key in table:
percentage = (table[key] / total) * 100
table_percentages[key] = percentage
return table_percentages
def display_table(dataset, index):
table = freq_table(dataset, index)
table_display = []
for key in table:
key_val_as_tuple = (table[key], key)
table_display.append(key_val_as_tuple)
table_sorted = sorted(table_display, reverse = True)
for entry in table_sorted:
print(entry[1], ':', entry[0], '%')
We start by examining the frequency table for the prime_genre column of the App Store data set.
display_table(ios_final, -5) # prime_genre
Games : 58.16263190564867 % Entertainment : 7.883302296710118 % Photo & Video : 4.9658597144630665 % Education : 3.662321539416512 % Social Networking : 3.2898820608317814 % Shopping : 2.60707635009311 % Utilities : 2.5139664804469275 % Sports : 2.1415270018621975 % Music : 2.0484171322160147 % Health & Fitness : 2.0173805090006205 % Productivity : 1.7380509000620732 % Lifestyle : 1.5828677839851024 % News : 1.3345747982619491 % Travel : 1.2414649286157666 % Finance : 1.1173184357541899 % Weather : 0.8690254500310366 % Food & Drink : 0.8069522036002483 % Reference : 0.5586592178770949 % Business : 0.5276225946617008 % Book : 0.4345127250155183 % Navigation : 0.186219739292365 % Medical : 0.186219739292365 % Catalogs : 0.12414649286157665 %
We can see that among the free English apps, more than a half (58.16%) are games. Entertainment apps are close to 8%, followed by photo and video apps, which are close to 5%. Only 3.66% of the apps are designed for education, followed by social networking apps which amount for 3.29% of the apps in our data set.
The general impression is that App Store (at least the part containing free English apps) is dominated by apps that are designed for fun (games, entertainment, photo and video, social networking, sports, music, etc.), while apps with practical purposes (education, shopping, utilities, productivity, lifestyle, etc.) are more rare. However, the fact that fun apps are the most numerous doesn't also imply that they also have the greatest number of users — the demand might not be the same as the offer.
Let's continue by examining the Genres and Category columns of the Google Play data set (two columns which seem to be related).
display_table(android_final, 1) # Category
FAMILY : 18.907942238267147 % GAME : 9.724729241877256 % TOOLS : 8.461191335740072 % BUSINESS : 4.591606498194946 % LIFESTYLE : 3.9034296028880866 % PRODUCTIVITY : 3.892148014440433 % FINANCE : 3.7003610108303246 % MEDICAL : 3.531137184115524 % SPORTS : 3.395758122743682 % PERSONALIZATION : 3.3167870036101084 % COMMUNICATION : 3.2378158844765346 % HEALTH_AND_FITNESS : 3.0798736462093865 % PHOTOGRAPHY : 2.944494584837545 % NEWS_AND_MAGAZINES : 2.7978339350180503 % SOCIAL : 2.6624548736462095 % TRAVEL_AND_LOCAL : 2.33528880866426 % SHOPPING : 2.2450361010830324 % BOOKS_AND_REFERENCE : 2.1435018050541514 % DATING : 1.861462093862816 % VIDEO_PLAYERS : 1.7937725631768955 % MAPS_AND_NAVIGATION : 1.3989169675090252 % FOOD_AND_DRINK : 1.2409747292418771 % EDUCATION : 1.1620036101083033 % ENTERTAINMENT : 0.9589350180505415 % LIBRARIES_AND_DEMO : 0.9363718411552346 % AUTO_AND_VEHICLES : 0.9250902527075812 % HOUSE_AND_HOME : 0.8235559566787004 % WEATHER : 0.8009927797833934 % EVENTS : 0.7107400722021661 % PARENTING : 0.6543321299638989 % ART_AND_DESIGN : 0.6430505415162455 % COMICS : 0.6204873646209386 % BEAUTY : 0.5979241877256317 %
The landscape seems significantly different on Google Play: there are not that many apps designed for fun, and it seems that a good number of apps are designed for practical purposes (family, tools, business, lifestyle, productivity, etc.). However, if we investigate this further, we can see that the family category (which accounts for almost 19% of the apps) means mostly games for kids.
Even so, practical apps seem to have a better representation on Google Play compared to App Store. This picture is also confirmed by the frequency table we see for the Genres column:
display_table(android_final, -4) # genres
Tools : 8.449909747292418 % Entertainment : 6.069494584837545 % Education : 5.347472924187725 % Business : 4.591606498194946 % Productivity : 3.892148014440433 % Lifestyle : 3.892148014440433 % Finance : 3.7003610108303246 % Medical : 3.531137184115524 % Sports : 3.463447653429603 % Personalization : 3.3167870036101084 % Communication : 3.2378158844765346 % Action : 3.1024368231046933 % Health & Fitness : 3.0798736462093865 % Photography : 2.944494584837545 % News & Magazines : 2.7978339350180503 % Social : 2.6624548736462095 % Travel & Local : 2.3240072202166067 % Shopping : 2.2450361010830324 % Books & Reference : 2.1435018050541514 % Simulation : 2.0419675090252705 % Dating : 1.861462093862816 % Arcade : 1.8501805054151623 % Video Players & Editors : 1.7712093862815883 % Casual : 1.7599277978339352 % Maps & Navigation : 1.3989169675090252 % Food & Drink : 1.2409747292418771 % Puzzle : 1.128158844765343 % Racing : 0.9927797833935018 % Role Playing : 0.9363718411552346 % Libraries & Demo : 0.9363718411552346 % Auto & Vehicles : 0.9250902527075812 % Strategy : 0.9138086642599278 % House & Home : 0.8235559566787004 % Weather : 0.8009927797833934 % Events : 0.7107400722021661 % Adventure : 0.6768953068592057 % Comics : 0.6092057761732852 % Beauty : 0.5979241877256317 % Art & Design : 0.5979241877256317 % Parenting : 0.4963898916967509 % Card : 0.45126353790613716 % Casino : 0.42870036101083037 % Trivia : 0.41741877256317694 % Educational;Education : 0.39485559566787 % Board : 0.3835740072202166 % Educational : 0.3722924187725632 % Education;Education : 0.33844765342960287 % Word : 0.2594765342960289 % Casual;Pretend Play : 0.236913357400722 % Music : 0.2030685920577617 % Racing;Action & Adventure : 0.16922382671480143 % Puzzle;Brain Games : 0.16922382671480143 % Entertainment;Music & Video : 0.16922382671480143 % Casual;Brain Games : 0.13537906137184114 % Casual;Action & Adventure : 0.13537906137184114 % Arcade;Action & Adventure : 0.12409747292418773 % Action;Action & Adventure : 0.10153429602888085 % Educational;Pretend Play : 0.09025270758122744 % Simulation;Action & Adventure : 0.078971119133574 % Parenting;Education : 0.078971119133574 % Entertainment;Brain Games : 0.078971119133574 % Board;Brain Games : 0.078971119133574 % Parenting;Music & Video : 0.06768953068592057 % Educational;Brain Games : 0.06768953068592057 % Casual;Creativity : 0.06768953068592057 % Art & Design;Creativity : 0.06768953068592057 % Education;Pretend Play : 0.056407942238267145 % Role Playing;Pretend Play : 0.04512635379061372 % Education;Creativity : 0.04512635379061372 % Role Playing;Action & Adventure : 0.033844765342960284 % Puzzle;Action & Adventure : 0.033844765342960284 % Entertainment;Creativity : 0.033844765342960284 % Entertainment;Action & Adventure : 0.033844765342960284 % Educational;Creativity : 0.033844765342960284 % Educational;Action & Adventure : 0.033844765342960284 % Education;Music & Video : 0.033844765342960284 % Education;Brain Games : 0.033844765342960284 % Education;Action & Adventure : 0.033844765342960284 % Adventure;Action & Adventure : 0.033844765342960284 % Video Players & Editors;Music & Video : 0.02256317689530686 % Sports;Action & Adventure : 0.02256317689530686 % Simulation;Pretend Play : 0.02256317689530686 % Puzzle;Creativity : 0.02256317689530686 % Music;Music & Video : 0.02256317689530686 % Entertainment;Pretend Play : 0.02256317689530686 % Casual;Education : 0.02256317689530686 % Board;Action & Adventure : 0.02256317689530686 % Video Players & Editors;Creativity : 0.01128158844765343 % Trivia;Education : 0.01128158844765343 % Travel & Local;Action & Adventure : 0.01128158844765343 % Tools;Education : 0.01128158844765343 % Strategy;Education : 0.01128158844765343 % Strategy;Creativity : 0.01128158844765343 % Strategy;Action & Adventure : 0.01128158844765343 % Simulation;Education : 0.01128158844765343 % Role Playing;Brain Games : 0.01128158844765343 % Racing;Pretend Play : 0.01128158844765343 % Puzzle;Education : 0.01128158844765343 % Parenting;Brain Games : 0.01128158844765343 % Music & Audio;Music & Video : 0.01128158844765343 % Lifestyle;Pretend Play : 0.01128158844765343 % Lifestyle;Education : 0.01128158844765343 % Health & Fitness;Education : 0.01128158844765343 % Health & Fitness;Action & Adventure : 0.01128158844765343 % Entertainment;Education : 0.01128158844765343 % Communication;Creativity : 0.01128158844765343 % Comics;Creativity : 0.01128158844765343 % Casual;Music & Video : 0.01128158844765343 % Card;Action & Adventure : 0.01128158844765343 % Books & Reference;Education : 0.01128158844765343 % Art & Design;Pretend Play : 0.01128158844765343 % Art & Design;Action & Adventure : 0.01128158844765343 % Arcade;Pretend Play : 0.01128158844765343 % Adventure;Education : 0.01128158844765343 %
The difference between the Genres and the Category columns is not crystal clear, but one thing we can notice is that the Genres column is much more granular (it has more categories). We're only looking for the bigger picture at the moment, so we'll only work with the Category column moving forward.
Up to this point, we found that the App Store is dominated by apps designed for fun, while Google Play shows a more balanced landscape of both practical and for-fun apps. Now we'd like to get an idea about the kind of apps that have most users.
One way to find out what genres are the most popular (have the most users) is to calculate the average number of installs for each app genre. For the Google Play data set, we can find this information in the Installs
column, but for the App Store data set this information is missing
. As a workaround, we'll take the total number of user ratings
as a proxy
, which we can find in the rating_count_tot app
.
genres_ios = freq_table(ios_final, -5) # we are using this as a list not a dict
# list_genres = []
# for row in ios_final:
# genres = row[-5]
# list_genres.append(genres)
# set_genres = set(list_genres)
# print(set_genres)
genre_listed = []
for genre in genres_ios:
total = 0
len_genre = 0
for app in ios_final:
genre_app = app[-5]
if genre_app == genre:
n_ratings = float(app[5])
total += n_ratings
len_genre += 1
avg_n_ratings = total / len_genre
# print(genre, ':', avg_n_ratings)
key_val_as_tuple = (avg_n_ratings, genre)
genre_listed.append(key_val_as_tuple)
genre_sorted = sorted(genre_listed, reverse = True)
for entry in genre_sorted:
print(entry[1], ':', entry[0])
Navigation : 86090.33333333333 Reference : 74942.11111111111 Social Networking : 71548.34905660378 Music : 57326.530303030304 Weather : 52279.892857142855 Book : 39758.5 Food & Drink : 33333.92307692308 Finance : 31467.944444444445 Photo & Video : 28441.54375 Travel : 28243.8 Shopping : 26919.690476190477 Health & Fitness : 23298.015384615384 Sports : 23008.898550724636 Games : 22788.6696905016 News : 21248.023255813954 Productivity : 21028.410714285714 Utilities : 18684.456790123455 Lifestyle : 16485.764705882353 Entertainment : 14029.830708661417 Business : 7491.117647058823 Education : 7003.983050847458 Catalogs : 4004.0 Medical : 612.0
On average, navigation apps have the highest number of user reviews, but this figure is heavily influenced by Waze and Google Maps, which have close to half a million user reviews together:
for app in ios_final:
if app[-5] == 'Navigation':
print(app[1], ':', app[5]) # print name and number of ratings
Waze - GPS Navigation, Maps & Real-time Traffic : 345046 Google Maps - Navigation & Transit : 154911 Geocaching® : 12811 CoPilot GPS – Car Navigation & Offline Maps : 3582 ImmobilienScout24: Real Estate Search in Germany : 187 Railway Route Search : 5
The same pattern applies to social networking apps, where the average number is heavily influenced by a few giants like Facebook, Pinterest, Skype, etc. Same applies to music apps, where a few big players like Pandora, Spotify, and Shazam heavily influence the average number.
Our aim is to find popular genres, but navigation, social networking or music apps might seem more popular than they really are. The average number of ratings seem to be skewed by very few apps which have hundreds of thousands of user ratings, while the other apps may struggle to get past the 10,000 threshold. We could get a better picture by removing these extremely popular apps for each genre and then rework the averages, but we'll leave this level of detail for later.
Reference apps have 74,942 user ratings on average, but it's actually the Bible and Dictionary.com which skew up the average rating:
for app in ios_final:
if app[-5] == 'Reference':
print(app[1], ':', app[5])
Bible : 985920 Dictionary.com Dictionary & Thesaurus : 200047 Dictionary.com Dictionary & Thesaurus for iPad : 54175 Google Translate : 26786 Muslim Pro: Ramadan 2017 Prayer Times, Azan, Quran : 18418 New Furniture Mods - Pocket Wiki & Game Tools for Minecraft PC Edition : 17588 Merriam-Webster Dictionary : 16849 Night Sky : 12122 City Maps for Minecraft PE - The Best Maps for Minecraft Pocket Edition (MCPE) : 8535 LUCKY BLOCK MOD ™ for Minecraft PC Edition - The Best Pocket Wiki & Mods Installer Tools : 4693 GUNS MODS for Minecraft PC Edition - Mods Tools : 1497 Guides for Pokémon GO - Pokemon GO News and Cheats : 826 WWDC : 762 Horror Maps for Minecraft PE - Download The Scariest Maps for Minecraft Pocket Edition (MCPE) Free : 718 VPN Express : 14 Real Bike Traffic Rider Virtual Reality Glasses : 8 教えて!goo : 0 Jishokun-Japanese English Dictionary & Translator : 0
However, this niche seems to show some potential. One thing we could do is take another popular book and turn it into an app where we could add different features besides the raw version of the book. This might include daily quotes from the book, an audio version of the book, quizzes about the book, etc. On top of that, we could also embed a dictionary within the app, so users don't need to exit our app to look up words in an external app.
This idea seems to fit well with the fact that the App Store is dominated by for-fun apps. This suggests the market might be a bit saturated with for-fun apps, which means a practical app might have more of a chance to stand out among the huge number of apps on the App Store.
Other genres that seem popular include weather, book, food and drink, or finance. The book genre seem to overlap a bit with the app idea we described above, but the other genres don't seem too interesting to us:
Weather apps — people generally don't spend too much time in-app, and the chances of making profit from in-app adds are low. Also, getting reliable live weather data may require us to connect our apps to non-free APIs.
Food and drink — examples here include Starbucks, Dunkin' Donuts, McDonald's, etc. So making a popular food and drink app requires actual cooking and a delivery service, which is outside the scope of our company.
Finance apps — these apps involve banking, paying bills, money transfer, etc. Building a finance app requires domain knowledge, and we don't want to hire a finance expert just to build an app.
Now let's analyze the Google Play market a bit.
For the Google Play market, we actually have data about the number of installs, so we should be able to get a clearer picture about genre popularity. However, the install numbers don't seem precise enough — we can see that most values are open-ended (100+, 1,000+, 5,000+, etc.):
display_table(android_final, 5) # the Installs columns
1,000,000+ : 15.726534296028879 % 100,000+ : 11.552346570397113 % 10,000,000+ : 10.548285198555957 % 10,000+ : 10.198555956678701 % 1,000+ : 8.393501805054152 % 100+ : 6.915613718411552 % 5,000,000+ : 6.825361010830325 % 500,000+ : 5.561823104693141 % 50,000+ : 4.7721119133574 % 5,000+ : 4.512635379061372 % 10+ : 3.5424187725631766 % 500+ : 3.2490974729241873 % 50,000,000+ : 2.3014440433213 % 100,000,000+ : 2.1322202166064983 % 50+ : 1.917870036101083 % 5+ : 0.78971119133574 % 1+ : 0.5076714801444043 % 500,000,000+ : 0.2707581227436823 % 1,000,000,000+ : 0.22563176895306858 % 0+ : 0.04512635379061372 % 0 : 0.01128158844765343 %
One problem with this data is that is not precise. For instance, we don't know whether an app with 100,000+ installs has 100,000 installs, 200,000, or 350,000. However, we don't need very precise data for our purposes — we only want to get an idea which app genres attract the most users, and we don't need perfect precision with respect to the number of users.
We're going to leave the numbers as they are, which means that we'll consider that an app with 100,000+ installs has 100,000 installs, and an app with 1,000,000+ installs has 1,000,000 installs, and so on.
To perform computations, however, we'll need to convert each install number to float — this means that we need to remove the commas and the plus characters, otherwise the conversion will fail and raise an error. We'll do this directly in the loop below, where we also compute the average number of installs for each genre (category).
categories_android = freq_table(android_final, 1)
categories_listed = []
for category in categories_android:
total = 0
len_category = 0
for app in android_final:
category_app = app[1]
if category_app == category:
n_installs = app[5]
n_installs = n_installs.replace(',','')
n_installs = n_installs.replace('+','')
total += float(n_installs)
len_category += 1
avg_n_installs = total / len_category
key_val_as_tuple = (avg_n_installs, category)
categories_listed.append(key_val_as_tuple)
categories_sorted = sorted(categories_listed, reverse = True)
for entry in categories_sorted:
print(entry[1], ':', entry[0])
COMMUNICATION : 38456119.167247385 VIDEO_PLAYERS : 24727872.452830188 SOCIAL : 23253652.127118643 PHOTOGRAPHY : 17840110.40229885 PRODUCTIVITY : 16787331.344927534 GAME : 15588015.603248259 TRAVEL_AND_LOCAL : 13984077.710144928 ENTERTAINMENT : 11640705.88235294 TOOLS : 10801391.298666667 NEWS_AND_MAGAZINES : 9549178.467741935 BOOKS_AND_REFERENCE : 8767811.894736841 SHOPPING : 7036877.311557789 PERSONALIZATION : 5201482.6122448975 WEATHER : 5074486.197183099 HEALTH_AND_FITNESS : 4188821.9853479853 MAPS_AND_NAVIGATION : 4056941.7741935486 FAMILY : 3695641.8198090694 SPORTS : 3638640.1428571427 ART_AND_DESIGN : 1986335.0877192982 FOOD_AND_DRINK : 1924897.7363636363 EDUCATION : 1833495.145631068 BUSINESS : 1712290.1474201474 LIFESTYLE : 1437816.2687861272 FINANCE : 1387692.475609756 HOUSE_AND_HOME : 1331540.5616438356 DATING : 854028.8303030303 COMICS : 817657.2727272727 AUTO_AND_VEHICLES : 647317.8170731707 LIBRARIES_AND_DEMO : 638503.734939759 PARENTING : 542603.6206896552 BEAUTY : 513151.88679245283 EVENTS : 253542.22222222222 MEDICAL : 120550.61980830671
On average, communication apps have the most installs: 38,456,119. This number is heavily skewed up by a few apps that have over one billion installs (WhatsApp, Facebook Messenger, Skype, Google Chrome, Gmail, and Hangouts), and a few others with over 100 and 500 million installs:
for app in android_final:
if app[1] == 'COMMUNICATION' and (app[5] == '1,000,000,000+'
or app[5] == '500,000,000+'
or app[5] == '100,000,000+'):
print(app[0], ':', app[5])
WhatsApp Messenger : 1,000,000,000+ imo beta free calls and text : 100,000,000+ Android Messages : 100,000,000+ Google Duo - High Quality Video Calls : 500,000,000+ Messenger – Text and Video Chat for Free : 1,000,000,000+ imo free video calls and chat : 500,000,000+ Skype - free IM & video calls : 1,000,000,000+ Who : 100,000,000+ GO SMS Pro - Messenger, Free Themes, Emoji : 100,000,000+ LINE: Free Calls & Messages : 500,000,000+ Google Chrome: Fast & Secure : 1,000,000,000+ Firefox Browser fast & private : 100,000,000+ UC Browser - Fast Download Private & Secure : 500,000,000+ Gmail : 1,000,000,000+ Hangouts : 1,000,000,000+ Messenger Lite: Free Calls & Messages : 100,000,000+ Kik : 100,000,000+ KakaoTalk: Free Calls & Text : 100,000,000+ Opera Mini - fast web browser : 100,000,000+ Opera Browser: Fast and Secure : 100,000,000+ Telegram : 100,000,000+ Truecaller: Caller ID, SMS spam blocking & Dialer : 100,000,000+ UC Browser Mini -Tiny Fast Private & Secure : 100,000,000+ Viber Messenger : 500,000,000+ WeChat : 100,000,000+ Yahoo Mail – Stay Organized : 100,000,000+ BBM - Free Calls & Messages : 100,000,000+
If we removed all the communication apps that have over 100 million installs, the average would be reduced roughly ten times:
under_100_m = []
for app in android_final:
n_installs = app[5]
n_installs = n_installs.replace(',', '')
n_installs = n_installs.replace('+', '')
if (app[1] == 'COMMUNICATION') and (float(n_installs) < 100000000):
under_100_m.append(float(n_installs))
sum(under_100_m) / len(under_100_m)
3603485.3884615386
We see the same pattern for the video players category, which is the runner-up with 24,727,872 installs. The market is dominated by apps like Youtube, Google Play Movies & TV, or MX Player. The pattern is repeated for social apps (where we have giants like Facebook, Instagram, Google+, etc.), photography apps (Google Photos and other popular photo editors), or productivity apps (Microsoft Word, Dropbox, Google Calendar, Evernote, etc.).
Again, the main concern is that these app genres might seem more popular than they really are. Moreover, these niches seem to be dominated by a few giants who are hard to compete against.
The game genre seems pretty popular, but previously we found out this part of the market seems a bit saturated, so we'd like to come up with a different app recommendation if possible.
The books and reference genre looks fairly popular as well, with an average number of installs of 8,767,811. It's interesting to explore this in more depth, since we found this genre has some potential to work well on the App Store, and our aim is to recommend an app genre that shows potential for being profitable on both the App Store and Google Play.
Let's take a look at some of the apps from this genre and their number of installs:
for app in android_final:
if app[1] == 'BOOKS_AND_REFERENCE':
print(app[0], ':', app[5])
E-Book Read - Read Book for free : 50,000+ Download free book with green book : 100,000+ Wikipedia : 10,000,000+ Cool Reader : 10,000,000+ Free Panda Radio Music : 100,000+ Book store : 1,000,000+ FBReader: Favorite Book Reader : 10,000,000+ English Grammar Complete Handbook : 500,000+ Free Books - Spirit Fanfiction and Stories : 1,000,000+ Google Play Books : 1,000,000,000+ AlReader -any text book reader : 5,000,000+ Offline English Dictionary : 100,000+ Offline: English to Tagalog Dictionary : 500,000+ FamilySearch Tree : 1,000,000+ Cloud of Books : 1,000,000+ Recipes of Prophetic Medicine for free : 500,000+ ReadEra – free ebook reader : 1,000,000+ Anonymous caller detection : 10,000+ Ebook Reader : 5,000,000+ Litnet - E-books : 100,000+ Read books online : 5,000,000+ English to Urdu Dictionary : 500,000+ eBoox: book reader fb2 epub zip : 1,000,000+ English Persian Dictionary : 500,000+ Flybook : 500,000+ All Maths Formulas : 1,000,000+ Ancestry : 5,000,000+ HTC Help : 10,000,000+ English translation from Bengali : 100,000+ Pdf Book Download - Read Pdf Book : 100,000+ Free Book Reader : 100,000+ eBoox new: Reader for fb2 epub zip books : 50,000+ Only 30 days in English, the guideline is guaranteed : 500,000+ Moon+ Reader : 10,000,000+ SH-02J Owner's Manual (Android 8.0) : 50,000+ English-Myanmar Dictionary : 1,000,000+ Golden Dictionary (EN-AR) : 1,000,000+ All Language Translator Free : 1,000,000+ Azpen eReader : 500,000+ URBANO V 02 instruction manual : 100,000+ Bible : 100,000,000+ C Programs and Reference : 50,000+ C Offline Tutorial : 1,000+ C Programs Handbook : 50,000+ Amazon Kindle : 100,000,000+ Aab e Hayat Full Novel : 100,000+ Aldiko Book Reader : 10,000,000+ Google I/O 2018 : 500,000+ R Language Reference Guide : 10,000+ Learn R Programming Full : 5,000+ R Programing Offline Tutorial : 1,000+ Guide for R Programming : 5+ Learn R Programming : 10+ R Quick Reference Big Data : 1,000+ V Made : 100,000+ Wattpad 📖 Free Books : 100,000,000+ Dictionary - WordWeb : 5,000,000+ Guide (for X-MEN) : 100,000+ AC Air condition Troubleshoot,Repair,Maintenance : 5,000+ AE Bulletins : 1,000+ Ae Allah na Dai (Rasa) : 10,000+ 50000 Free eBooks & Free AudioBooks : 5,000,000+ Ag PhD Field Guide : 10,000+ Ag PhD Deficiencies : 10,000+ Ag PhD Planting Population Calculator : 1,000+ Ag PhD Soybean Diseases : 1,000+ Fertilizer Removal By Crop : 50,000+ A-J Media Vault : 50+ Al-Quran (Free) : 10,000,000+ Al Quran (Tafsir & by Word) : 500,000+ Al Quran Indonesia : 10,000,000+ Al'Quran Bahasa Indonesia : 10,000,000+ Al Quran Al karim : 1,000,000+ Al-Muhaffiz : 50,000+ Al Quran : EAlim - Translations & MP3 Offline : 5,000,000+ Al-Quran 30 Juz free copies : 500,000+ Koran Read &MP3 30 Juz Offline : 1,000,000+ Hafizi Quran 15 lines per page : 1,000,000+ Quran for Android : 10,000,000+ Surah Al-Waqiah : 100,000+ Hisnul Al Muslim - Hisn Invocations & Adhkaar : 100,000+ Satellite AR : 1,000,000+ Audiobooks from Audible : 100,000,000+ Kinot & Eichah for Tisha B'Av : 10,000+ AW Tozer Devotionals - Daily : 5,000+ Tozer Devotional -Series 1 : 1,000+ The Pursuit of God : 1,000+ AY Sing : 5,000+ Ay Hasnain k Nana Milad Naat : 10,000+ Ay Mohabbat Teri Khatir Novel : 10,000+ Arizona Statutes, ARS (AZ Law) : 1,000+ Oxford A-Z of English Usage : 1,000,000+ BD Fishpedia : 1,000+ BD All Sim Offer : 10,000+ Youboox - Livres, BD et magazines : 500,000+ B&H Kids AR : 10,000+ B y H Niños ES : 5,000+ Dictionary.com: Find Definitions for English Words : 10,000,000+ English Dictionary - Offline : 10,000,000+ Bible KJV : 5,000,000+ Borneo Bible, BM Bible : 10,000+ MOD Black for BM : 100+ BM Box : 1,000+ Anime Mod for BM : 100+ NOOK: Read eBooks & Magazines : 10,000,000+ NOOK Audiobooks : 500,000+ NOOK App for NOOK Devices : 500,000+ Browsery by Barnes & Noble : 5,000+ bp e-store : 1,000+ Brilliant Quotes: Life, Love, Family & Motivation : 1,000,000+ BR Ambedkar Biography & Quotes : 10,000+ BU Alsace : 100+ Catholic La Bu Zo Kam : 500+ Khrifa Hla Bu (Solfa) : 10+ Kristian Hla Bu : 10,000+ SA HLA BU : 1,000+ Learn SAP BW : 500+ Learn SAP BW on HANA : 500+ CA Laws 2018 (California Laws and Codes) : 5,000+ Bootable Methods(USB-CD-DVD) : 10,000+ cloudLibrary : 100,000+ SDA Collegiate Quarterly : 500+ Sabbath School : 100,000+ Cypress College Library : 100+ Stats Royale for Clash Royale : 1,000,000+ GATE 21 years CS Papers(2011-2018 Solved) : 50+ Learn CT Scan Of Head : 5,000+ Easy Cv maker 2018 : 10,000+ How to Write CV : 100,000+ CW Nuclear : 1,000+ CY Spray nozzle : 10+ BibleRead En Cy Zh Yue : 5+ CZ-Help : 5+ Modlitební knížka CZ : 500+ Guide for DB Xenoverse : 10,000+ Guide for DB Xenoverse 2 : 10,000+ Guide for IMS DB : 10+ DC HSEMA : 5,000+ DC Public Library : 1,000+ Painting Lulu DC Super Friends : 1,000+ Dictionary : 10,000,000+ Fix Error Google Playstore : 1,000+ D. H. Lawrence Poems FREE : 1,000+ Bilingual Dictionary Audio App : 5,000+ DM Screen : 10,000+ wikiHow: how to do anything : 1,000,000+ Dr. Doug's Tips : 1,000+ Bible du Semeur-BDS (French) : 50,000+ La citadelle du musulman : 50,000+ DV 2019 Entry Guide : 10,000+ DV 2019 - EDV Photo & Form : 50,000+ DV 2018 Winners Guide : 1,000+ EB Annual Meetings : 1,000+ EC - AP & Telangana : 5,000+ TN Patta Citta & EC : 10,000+ AP Stamps and Registration : 10,000+ CompactiMa EC pH Calibration : 100+ EGW Writings 2 : 100,000+ EGW Writings : 1,000,000+ Bible with EGW Comments : 100,000+ My Little Pony AR Guide : 1,000,000+ SDA Sabbath School Quarterly : 500,000+ Duaa Ek Ibaadat : 5,000+ Spanish English Translator : 10,000,000+ Dictionary - Merriam-Webster : 10,000,000+ JW Library : 10,000,000+ Oxford Dictionary of English : Free : 10,000,000+ English Hindi Dictionary : 10,000,000+ English to Hindi Dictionary : 5,000,000+ EP Research Service : 1,000+ Hymnes et Louanges : 100,000+ EU Charter : 1,000+ EU Data Protection : 1,000+ EU IP Codes : 100+ EW PDF : 5+ BakaReader EX : 100,000+ EZ Quran : 50,000+ FA Part 1 & 2 Past Papers Solved Free – Offline : 5,000+ La Fe de Jesus : 1,000+ La Fe de Jesús : 500+ Le Fe de Jesus : 500+ Florida - Pocket Brainbook : 1,000+ Florida Statutes (FL Code) : 1,000+ English To Shona Dictionary : 10,000+ Greek Bible FP (Audio) : 1,000+ Golden Dictionary (FR-AR) : 500,000+ Fanfic-FR : 5,000+ Bulgarian French Dictionary Fr : 10,000+ Chemin (fr) : 1,000+ The SCP Foundation DB fr nn5n : 1,000+
for app in android_final:
if app[1] == 'BOOKS_AND_REFERENCE' and (app[5] == '1,000,000,000+'
or app[5] == '500,000,000+'
or app[5] == '100,000,000+'):
print(app[0], ':', app[5])
Google Play Books : 1,000,000,000+ Bible : 100,000,000+ Amazon Kindle : 100,000,000+ Wattpad 📖 Free Books : 100,000,000+ Audiobooks from Audible : 100,000,000+
However, it looks like there are only a few very popular apps, so this market still shows potential. Let's try to get some app ideas based on the kind of apps that are somewhere in the middle in terms of popularity (between 1,000,000 and 100,000,000 downloads):
for app in android_final:
if app[1] == 'BOOKS_AND_REFERENCE' and (app[5] == '1,000,000+'
or app[5] == '5,000,000+'
or app[5] == '10,000,000+'
or app[5] == '50,000,000+'):
print(app[0], ':', app[5])
Wikipedia : 10,000,000+ Cool Reader : 10,000,000+ Book store : 1,000,000+ FBReader: Favorite Book Reader : 10,000,000+ Free Books - Spirit Fanfiction and Stories : 1,000,000+ AlReader -any text book reader : 5,000,000+ FamilySearch Tree : 1,000,000+ Cloud of Books : 1,000,000+ ReadEra – free ebook reader : 1,000,000+ Ebook Reader : 5,000,000+ Read books online : 5,000,000+ eBoox: book reader fb2 epub zip : 1,000,000+ All Maths Formulas : 1,000,000+ Ancestry : 5,000,000+ HTC Help : 10,000,000+ Moon+ Reader : 10,000,000+ English-Myanmar Dictionary : 1,000,000+ Golden Dictionary (EN-AR) : 1,000,000+ All Language Translator Free : 1,000,000+ Aldiko Book Reader : 10,000,000+ Dictionary - WordWeb : 5,000,000+ 50000 Free eBooks & Free AudioBooks : 5,000,000+ Al-Quran (Free) : 10,000,000+ Al Quran Indonesia : 10,000,000+ Al'Quran Bahasa Indonesia : 10,000,000+ Al Quran Al karim : 1,000,000+ Al Quran : EAlim - Translations & MP3 Offline : 5,000,000+ Koran Read &MP3 30 Juz Offline : 1,000,000+ Hafizi Quran 15 lines per page : 1,000,000+ Quran for Android : 10,000,000+ Satellite AR : 1,000,000+ Oxford A-Z of English Usage : 1,000,000+ Dictionary.com: Find Definitions for English Words : 10,000,000+ English Dictionary - Offline : 10,000,000+ Bible KJV : 5,000,000+ NOOK: Read eBooks & Magazines : 10,000,000+ Brilliant Quotes: Life, Love, Family & Motivation : 1,000,000+ Stats Royale for Clash Royale : 1,000,000+ Dictionary : 10,000,000+ wikiHow: how to do anything : 1,000,000+ EGW Writings : 1,000,000+ My Little Pony AR Guide : 1,000,000+ Spanish English Translator : 10,000,000+ Dictionary - Merriam-Webster : 10,000,000+ JW Library : 10,000,000+ Oxford Dictionary of English : Free : 10,000,000+ English Hindi Dictionary : 10,000,000+ English to Hindi Dictionary : 5,000,000+
This niche seems to be dominated by software for processing and reading ebooks, as well as various collections of libraries and dictionaries, so it's probably not a good idea to build similar apps since there'll be some significant competition.
We also notice there are quite a few apps built around the book Quran, which suggests that building an app around a popular book can be profitable. It seems that taking a popular book (perhaps a more recent book) and turning it into an app could be profitable for both the Google Play and the App Store markets.
However, it looks like the market is already full of libraries, so we need to add some special features besides the raw version of the book. This might include daily quotes from the book, an audio version of the book, quizzes on the book, a forum where people can discuss the book, etc.
In this project, we analyzed data about the App Store and Google Play mobile apps with the goal of recommending an app profile that can be profitable for both markets.
We concluded that taking a popular book (perhaps a more recent book) and turning it into an app could be profitable for both the Google Play and the App Store markets. The markets are already full of libraries, so we need to add some special features besides the raw version of the book. This might include daily quotes from the book, an audio version of the book, quizzes on the book, a forum where people can discuss the book, etc.