Playlist Analysis

50+ Engagement Metrics

v9.3 analyzes playlists across 7 dimensions with over 50 individual metrics to provide comprehensive fraud assessment.

Curator Profile

Follower count, account age, verification status, profile completeness

Playlist Characteristics

Track count, duration, update frequency, description quality

Engagement Patterns

Follower growth, likes, shares, saves, skip rates

Temporal Analysis

Stream velocity, time-of-day patterns, weekly cycles

Geographic Distribution

Listener locations, concentration metrics, anomalies

Content Quality

Genre consistency, artist diversity, track quality scores

Network Relationships

Connections to other playlists, cross-promotion patterns

5-Tier Curator Classification

Tier 1: Official Spotify Playlists

Fraud Rate: <0.5%

Examples: Today's Top Hits, RapCaviar, New Music Friday
Characteristics: Verified account, millions of followers, editorial team
Trust Level: Highest - Safe for all commercial purposes
Identification: Spotify-branded account, verified badge

Tier 2: Verified Independent Curators

Fraud Rate: <2%

Examples: Established music blogs, major influencers, record labels
Characteristics: Verified badge, >100K followers, consistent quality
Trust Level: High - Reliable for playlist placement
Vetting: Manual verification by Spotify

Tier 3: Established Independent Curators

Fraud Rate: 5-10%

Characteristics: 10K-100K followers, active >1 year, good engagement
Trust Level: Moderate - Generally safe, occasional issues
Monitoring: Regular engagement quality checks recommended
Examples: Niche genre curators, regional tastemakers

Tier 4: Emerging Curators

Fraud Rate: 15-25%

Characteristics: <10K followers, newer accounts, inconsistent engagement
Trust Level: Low - High fraud risk, careful monitoring required
Red Flags: Rapid follower growth, suspicious engagement patterns
Examples: New playlist services, unverified promoters

Tier 5: Suspicious Accounts

Fraud Rate: >40%

Characteristics: Bot-like behavior, irregular patterns, fake engagement
Trust Level: None - Avoid completely
Warning Signs: Benford's Law violations, 24/7 streaming, click farm locations
Action: Report to Spotify, remove tracks immediately

Engagement Quality Analysis

Skip Rate Analysis

Human Listeners: 15-25% skip rate (natural behavior)
Bot Listeners: <5% skip rate (programmed to complete tracks)
Fraud Indicator: Skip rate <8% is highly suspicious
Context: Genre-dependent (EDM has lower skip rates naturally)

Completion Rate Analysis

Human Listeners: 60-80% completion (varies by track quality)
Bot Listeners: >95% completion (too consistent)
Fraud Indicator: >90% completion across all tracks
Analysis: Compare playlist-wide vs individual track completion

Listener Diversity

Unique Listeners Per Stream: Natural playlists have diverse listeners
Bot Farms: Same accounts streaming repeatedly
Fraud Indicator: <20% unique listeners per 100 streams
Network Analysis: Identify account clusters

Time-of-Day Patterns

Human Patterns: Peak during commute hours, evenings, weekends
Bot Patterns: Consistent 24/7 streaming without variation
Fraud Indicator: Flat time-of-day distribution
Geographic Correlation: Activity should match listener time zones

Playlist Health Indicators

Organic Growth

Gradual, steady follower increases over months

Consistent Updates

Regular refreshes (weekly or bi-weekly typical)

Engaged Followers

Likes, saves, and shares proportional to follower count

Genre Consistency

Coherent musical theme, not random tracks

Artist Diversity

Mix of established and emerging artists

Natural Engagement

Skip rates, completion rates within expected ranges

Combined Track + Playlist Analysis

When both AI detection and playlist intelligence are complete, you'll be able to analyze tracks in context of their playlist placements.

Scenario 1: AI Track on Fraudulent Playlist

Track AI Detection: Suno 80% confidence
Playlist Fraud Score: 85 (Critical)
Combined Risk: Extremely High
Interpretation: AI-generated track promoted through bot network
Recommendation: Report to platform, avoid engagement

Scenario 2: Human Track on Organic Playlist

Track AI Detection: Human 90% confidence
Playlist Fraud Score: 12 (Clean)
Combined Risk: Very Low
Interpretation: Legitimate artist on authentic playlist
Recommendation: Safe for all commercial purposes

Scenario 3: AI Track on Tier 1 Playlist

Track AI Detection: AIVA 75% confidence
Playlist Fraud Score: 2 (Clean - Official Spotify)
Combined Risk: Low
Interpretation: Licensed AI music on legitimate platform
Recommendation: Verify AIVA licensing terms