yonilev/GooglePlayStoreApps

📱 Google Play Store 2020 — What Made an App Go Viral?

A data-driven EDA of 9,436 apps released in 2020, exploring the patterns behind viral success on the Play Store.

🎬 Video Walkthrough

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Can't see the video? [Click here to watch](https://www.loom.com/share/3b2dc51bcf384a339d3d3328766e4705)

🔬 Research Question

"What made an app released in 2020 go viral?"

Defined as reaching 1M+ installs by June 2021 — within 6–18 months of launch.

2020 was chosen deliberately: the COVID-19 pandemic drove unprecedented mobile app adoption, and since the data was collected in June 2021, apps from 2020 had a consistent 6–18 month measurement window.

📊 Key Visualizations

1. The Winner-Takes-All Market

86% of apps never exceed 10K installs. Viral apps (<1%) are a thin but real right tail.

2. Does Quality = Success? (Surprising Answer: No)

Rating and Installs show a weak negative linear correlation (r = −0.31). Viral apps attract polarising reviews — millions of users means more critics.

3. Monetization Strategy Matters

Ad-based and Hybrid (ads + IAP) apps reach significantly higher install counts. The price barrier for Premium apps dramatically limits reach.

4. The Gap Between Tiers is Enormous

Each tier is roughly 1,000x the previous — a textbook power-law gap.

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🔑 Key Findings

1. 1.The market is winner-takes-all. 86% of apps sit in the Low tier. Viral apps represent less than 1% of 2020 launches.
2. 2.Monetization is the strongest predictor. Ad-based and Hybrid models (ads + IAP) significantly outperform Pure Free and Premium.
3. 3.Higher ratings do NOT predict more installs (r = −0.31). Quality alone is not the driver — distribution and visibility are.
4. 4.Having a rating at all is a strong proxy for traction. Rated apps contain virtually all Medium and Viral tier apps.
5. 5.Fresher apps win. Regular updates correlate negatively with dayssinceupdate (r = −0.25).
6. 6.The Rating–Installs relationship is category-specific. A global r = −0.31 masks very different dynamics per category.

🗂️ Dataset

Features in this dataset

📓 Notebook

The full analysis notebook is available here: 👉 Open The Notebook in Google Colab ---

❓ Questions & Answers

Q1: Is the app market democratic — can any app go viral? No. 86% of apps released in 2020 never exceeded 10K installs. The market is winner-takes-all: less than 1% of apps reached the Viral tier (1M+ installs), and their median install count is roughly 1,000x that of Medium-tier apps.

Q2: Does a higher rating mean more installs? Surprisingly, no. Rating and Installs show a weak negative linear correlation (r = −0.31). Viral apps attract polarising reviews — millions of users means more critics. Quality alone is not the driver; distribution and visibility are.

Q3: Does monetization strategy matter? Yes — it's the strongest predictor in the dataset. Ad-based and Hybrid (ads + IAP) apps reach significantly higher install counts than Pure Free or Premium apps. The price barrier of Premium apps dramatically limits reach.

Q4: Does having a rating at all matter? Yes, dramatically. Apps with a visible rating contain virtually all Medium and Viral tier apps. This reflects a chicken-and-egg dynamic: installs drive ratings, ratings drive visibility, visibility drives more installs.

Q5: Does the Rating–Installs relationship hold across all categories? No. The global r = −0.31 masks very different dynamics per category. In Tools and Business, there is almost no relationship. In Entertainment and Games, high-install apps cluster at specific rating bands.

🔧 Key Decisions

## 👤 Author

**Yonathan Levy**
Econ & Entrepreneurship with Data Science Specialization
Reichman Uni
Class of 2028