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Bolivan Teikeng
Bolivan Teikeng

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Scientific Market Analysis: Google Play Store App Performance

#datascience #python #pandas #dataanalysis

Scientific Market Analysis: Google Play Store App Performance

1. Introduction & Assumptions

As part of the strategic planning for My MobApp Studio, we conducted a data-driven market study on the Google Play Store dataset to identify business opportunities for our upcoming mobile app.

Initial Assumptions (Hypotheses):

  1. H1: Free applications represent the overwhelming majority of total downloads compared to paid applications.
  2. H2: The FAMILY and GAME categories dominate overall market installations.
  3. H3: Paid applications in the FAMILY category have lower adoption rates, with downloads concentrated in a few specific niche genres.

2. Experimental Methodology & Cleaning

We analyzed the official Google Play Store dataset containing thousands of Android applications.

Data Pre-processing Steps:

  1. Removed duplicate entries to prevent skewed statistics.
  2. Cleaned numerical variables:
    • Stripped + and , symbols from the Installs column and converted values to floats.
    • Removed $ signs from Price and converted strings to numeric values.
  3. Handled missing data (NaN) across all features to ensure clean quantitative evaluation.

3. Results & Data Insights

Market Size Overview

  • Total Market Installations: Hundreds of billions of app downloads worldwide.
  • Category Distribution: GAME, COMMUNICATION, and TOOLS hold the largest percentage of total installations.

Family Category & Paid Apps Focus

  • Top Paid Family Apps: Popular paid family applications maintain steady installation numbers despite pricing barriers.
  • Popular Paid Family Genres: Niche categories such as Educational games and Casual games drive the majority of paid family app downloads.

Pricing Insights

  • Mean Price per Category: Finance and Business categories show higher average prices due to specialized enterprise utility.
  • Most Expensive Apps: Outliers are predominantly niche utility apps or luxury/status applications.

4. Conclusion & Strategic Recommendations

Key Findings:

  • Free-to-Play Model: Launching a free app with in-app monetization or ads yields significantly higher initial market reach than a paid model.
  • Target Category: Entering FAMILY or GAME offers the highest volume of potential users.

Next Experiments to Conduct:

  1. Sentiment Analysis: Analyze user review text to identify common pain points in competing apps.
  2. Monetization Optimization: Evaluate price elasticity for paid features vs. ad-supported models within the FAMILY category.

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