Provides sophisticated algorithms for detecting and classifying different types
of track skips, allowing for detailed analysis of user listening behavior.
Features:
Multiple specialized skip detection algorithms with confidence ratings
Position-based analysis with configurable thresholds
Skip pattern recognition for behavioral insights
Classification of skip types (preview, standard, near-completion)
Manual vs. automatic skip differentiation
Advanced edge case handling for reliable detection
Skip event tracking with timestamps and metadata
Behavior pattern analysis across listening sessions
This module forms the analytical core of the skip tracking system,
implementing various algorithms to detect and categorize different
types of skip behaviors. It analyzes playback state transitions to
determine when a user has skipped a track versus normal playback
progression, and provides confidence ratings for its determinations.
The skip detection system uses several factors to identify skips:
Description
Skip Detection Analytics Module
Provides sophisticated algorithms for detecting and classifying different types of track skips, allowing for detailed analysis of user listening behavior.
Features:
This module forms the analytical core of the skip tracking system, implementing various algorithms to detect and categorize different types of skip behaviors. It analyzes playback state transitions to determine when a user has skipped a track versus normal playback progression, and provides confidence ratings for its determinations.
The skip detection system uses several factors to identify skips: