Google Paly Store Data Analysis Using QlikView

Subesha Sasmal
7 min readNov 15, 2020
Various apps in Google Play store

Introduction:

The Google Play Store is the largest and most demanded Android App store. It is a digital distribution service operated and developed by Google allowing users to browse and download applications. It is the official App store offering various categories of apps including music, books, television shows, movies, games, finance and social media.

We took a sample dataset and analyzed about 10,808 apps in 33 categories using BI tool QlikView. The analysis provides useful insights about the success of an app. The developers should keep few things in mind like price, size and target audience before launching an App into the market. User reviews play an important role in the success of an app. Developers should continuously keep an eye on the reviews and address customer needs from time to time.

Overview of Dashboard
Dashboard in a glance

Objective:

The project aims to analyze the raw data set on Google Play Store and provides a meaningful insights in terms of App downloads, ratings and categories by creating dashboard using QlikView which is one of the fastest evolving BI tool. We have studied various aspects of the data on the basis of observations and analysis such as number of Apps, total installations, type of apps available in a particular category, user reviews and overall ratings of the apps.

Overview of Dataset:

We analyzed the Google Play Store dataset for review and analysis. About 10,800 rows of data provides ample insight about various apps, their popularity, user ratings, reviews by various age groups and customer inclination towards paid and free apps. Here’s a glimpse at the raw dataset:

Data set as seen in MS Excel

How Data Visualization Helps?

Google Play Store is the biggest App store with having 2.7 million number of apps as of second quarter of 2020. It is a quite tedious task to visualize the success of an app in the market without having a proper market analysis. The success of an app depends on various factors like size, paid/free app, ratings and number of installations to begin with. A well thought-out strategy helps an app to reach to its success.

Data Visualization helps in studying a number of factors like number of users in a particular category, competition level, price range and target audience and plan market strategy accordingly.

Features of Data Set:

  1. App Name: The column is all about name of applications.
  2. Apps Category: The apps are categorized into 33 categories.
  3. Rating: User ratings given to each app.
  4. Reviews: Number of reviews received for each app.
  5. Installs: Number of downloads/installs for each app.
  6. Type: There are both free and paid apps.
  7. Price: Paid apps price mentioned in USD.
  8. Content Rating: Ratings provided by a particular age group.
  9. Genres: This column describes about genre of an app.
  10. Current Version: Current version of an app.
  11. Android Version: Minimum Android version an app supports.

Data Cleaning:

Data cleaning is the first and most important part before we analyze a dataset. Usually raw data comes with duplicate entries, typo errors and special characters in them. We started with replacing typo errors with meaningful words like ‘None’ in stead of ‘NaN’. There were some outliers in the ratings field like a rating of 19. Since the highest rating is 5 we changed 19 to the maximum rating to 5.

Subject of Analysis:

We have taken below subjects under our analysis .

  1. Share of Each Category Apps Downloaded in Percentage

The Pie chart shows the percentage of apps in each category. In other words it indicates the share of target audience in different categories. Family, Game and Tools are the top three type of categories occupying about 37% of total audience. Price-wise, paid apps also tops in the family category. It signifies that the target audience is willing to pay and download app in this category. A detailed analysis of the dashboard gives many different insightful ideas about the market trend and customer behavior.

2. Rating Given By a Particular Age Category

The future and success of an app depends on the user ratings after the app is launched in the market. Developers should keep an eye on the reviews and rating given by the users and address their issues immediately. The younger generation are more active in comparison to older generations. The number of users are more in the older generations in comparison to the younger generation but number ratings are more in the younger generation. It signifies that younger generations are more aware and proactive. Developers should keep this in mind while handling reviews for apps targeting the younger audience.

3. Share of Ratings

App ratings is an impressive factor for user of any age group. This gives assurance about the standard and quality of the app. Above pie chart gives a clear view of the share of ratings of the apps. Top four ratings occupy about 47% of the total ratings. Family, Game and Tools category apps stand in the top three categories of ratings. Developers should keep the app quality factor in mind while launching a new app in these categories since the competition is very tough and users are more aware about their requirements.

4. Number of Reviews vs. Number of Ratings

Above bar chart clearly shows that users are more tend to give reviews than ratings. Few words in detail helps developers more than the ratings to look into the matter in depth and address the issue. This indicates that the users are more aware and have detailed knowledge about the issue they are talking about. It is important for developers to take the reviews into consideration and address the concern of users.

5. Free vs. Paid Apps and Pricing Strategy

Pricing plays an important role while choosing a target audience. Younger audiences are more likely to go for free apps than paid apps. A significant number of apps are available free in the Google Play Store. Professional category apps like medical, personalization and tools top the paid category apps. Apps targeting the younger audience and socialization are available free in the Paly store.

6. Top Fifteen Reviews by Category

Above bar chart shows top fifteen category of apps having most reviews. Developers should keep in mind the awareness of the target audience. The top five category are Family, Game, Tools, Medical and Business. The list signifies that the target audience is professionals and more aware about their requirements.

7. Top 50 Genres of Apps Downloaded

Above chart gives an interesting insight about the needs of the society. Surprisingly, there are more number of apps downloaded in the professional category than the casual purpose. Education, Medical, Business and Productivity are some of the most downloaded apps in the professional category. The target audience is tend to pay and download app in the professional segment than the leisure segment.

Conclusion:

A detailed analysis shows that people are more inclined towards their profession and productivity than just entertainment and being social. Also, these are the target audience who agree to pay and download the app. A developer should be more competitive in the terms of service and price to beat the competition in the professional segment. Younger generations are more aware about their needs and vocal about their issues. Developers should take their reviews seriously and address the issues to beat the competition and increase the number of downloads in the Play Store.

Acknowledgement:

Myself Subesha Sasmal and my team-mate Sultan Shaikh made this analysis and created this blog as part of the project work “BI tool — QlikView”. The workshop was conducted by Prof. Rocky Jagtiani at Suven Consultants. We express our sincere thanks to Rocky sir for giving us the opportunity to join the workshop under his mentorship.

Dataset Reference: GooglePalyStore.xls and GooglePalyStore_User_Reviews.xls

Project Analysis Reference: Google_Playstore_Project.qvw

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Subesha Sasmal

My endless curiosity and interest to venture into an unchartered territory of Data Science and AI has landed me somewhere in the realm of AI.