App Usage Pattern Data
Buy and sell app usage pattern data data. Which apps get opened, how long, and in what order throughout the day. The screen time data Apple won't share.
No listings currently in the marketplace for App Usage Pattern Data.
Find Me This Data →Overview
What Is App Usage Pattern Data?
App usage pattern data captures which applications users open, for how long, and in what sequence throughout the day. This includes app status, usage time, app names, user interaction states, and smartphone use state. Collected primarily through Android APIs such as Usage Statistics API (US API) and Accessibility Service API (AS API), this data enables passive collection of fine-grained interaction metrics including user interface elements, interaction types, targets, and timestamps. The data represents the screen time and behavioral insights that operating systems like Apple restrict from third-party access, making it highly valuable for researchers and companies seeking to understand real-world mobile behavior at scale.
Market Data
Android Usage Statistics API (US API) and Accessibility Service API (AS API)
Primary Collection Method
Source: ACM Computing Surveys
App status, usage time, app name, user interaction state, smartphone use state, UI elements, interaction type, target, and timestamp
Data Granularity Available
Source: ResearchGate
30+ published studies using app usage pattern data for data-driven analytics
Research Applications
Source: ResearchGate
Who Uses This Data
What AI models do with it.do with it.
User Behavior Research
Academic and industrial researchers analyzing smartphone interaction patterns, notification responses, and how context influences app usage decisions.
Mobile App Analytics
App developers and product teams clustering user types by usage frequency and patterns to understand engagement, retention, and feature adoption.
Health & Wellness Studies
Researchers tracking activity patterns and mobile app usage to correlate with fitness, daily routines, and user habits across participant cohorts.
UI/UX Optimization
Design teams analyzing user interface interaction data, exploration patterns, and element hierarchy to improve app flow and user experience.
Pricing depends on the proposed terms
We do not have a verified, comparable price for your dataset. Consider the permitted uses, license term, exclusivity, provenance, coverage and quality. A seller asking price is a proposal, not an appraisal or guaranteed sale. Compare prices only when the source, date, currency, unit and license scope are known.
What Buyers Expect
What makes it valuable.valuable.
Fine-Grained Timestamp Accuracy
Precise logging of interaction times, app transitions, and event sequences to enable temporal behavior analysis and pattern detection.
Complete UI Interaction Capture
Documentation of user interface element interactions, hierarchy navigation, and exploration types alongside app-level usage to enable interaction design research.
Consistent Data Collection Methods
Use of standardized APIs (US API or AS API) and clear metadata about collection infrastructure to ensure reproducibility and comparability across studies.
Contextual Metadata
Supplementary data on device state, notification triggers, and surrounding context conditions to enable correlation with usage behavior.
Potential applications and organizations
Who's buying.buying.
Systematic surveys and studies analyzing smartphone APIs, user interaction patterns, and mobile behavior for peer-reviewed publications.
Clustering users by engagement frequency and usage patterns to optimize app features, retention, and user experience.
Correlating app usage patterns with activity data and daily routines to build behavior-prediction and wellness models.
FAQ
Common questions.questions.
How is app usage pattern data collected?
Primarily through Android APIs: Usage Statistics API (US API) collects app history, usage time, and device statistics; Accessibility Service API (AS API) captures detailed user interface interactions, element hierarchies, and interaction types. Both collect data passively without requiring active logging by the user.
What specific metrics can be captured?
App name, app status, total usage time, user interaction state, smartphone use state, UI element information and hierarchy, interaction type and target, timestamps of each event, and notification triggers. This granular data enables behavior sequencing and pattern analysis.
Who buys this data and why?
Academic researchers studying mobile behavior, app developers optimizing user engagement, health and wellness platforms correlating activity with mobile habits, and UX/design teams analyzing interaction patterns. The data provides insights comparable to Apple's internal screen time metrics.
What quality standards should sellers meet?
Buyers expect precise timestamps, complete UI interaction logs, consistent collection via standardized APIs, clear metadata about collection methods, and contextual information like device state and notifications. Data should support reproducible analysis and behavioral pattern detection.
Sell yourapp usage patterndata.
Describe your app usage pattern data and the uses you are authorized to offer. Price, legal suitability, and buyer interest require separate evaluation. No match or sale is guaranteed.
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