Dataset: Mobile App Usage Analytics

This dataset contains 200 rows of simulated data representing the usage performance of mobile apps across platforms, regions, and user demographics.

Each row corresponds to an individual app instance, capturing key engagement and performance metrics like daily user activity, session time, crash rates, and in-app purchase behavior.

Columns Overview:

• App Category: Type of app (Games, Finance, Education, Social)
• User Age Group: Primary user base (Teen, Adult, Senior)
• Platform: Mobile OS (Android or iOS)
• Region: Geographical user base
• Daily Active Users: Number of users who use the app daily
• Average Session Time: Time spent in the app per session (in minutes)
• Crash Rate (%): Frequency of app crashes (as a percentage)
• Total In-App Purchases: Number of purchases made within the app

Purpose:

Designed for data visualization, performance tracking, and behavior analysis using Power BI, Tableau, or Python. Useful for product managers, data analysts, and developers to assess app engagement and monetization patterns.

This is dataset snapshot

Get the Dataset Here: https://github.com/slidescope/data/blob/master/mobile_app_usage_analytics.csv

In the dataset

💡 Meaning of In-App Purchase (IAP):

An In-App Purchase (IAP) refers to any purchase made by a user within a mobile app, using real money, after the app has been downloaded or installed.

🔄 Examples of In-App Purchases: