How Do I Analyze My Apple Music for Artists Data to Make Better Decisions?
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Apple Music : https://music.apple.com/us/artist/stephen-allen-music/1092692557
Why Data Analysis Matters
- Shows what’s working and what’s not in your releases
- Helps you identify your biggest fans, cities, and songs
- Supports smarter marketing, touring, and content decisions
- Increases chances of playlisting and fan growth by responding to trends
Key Metrics to Watch in AM4A
|
Metric |
What It Tells You |
|
Plays |
Total number of streams, including replays |
|
Listeners |
Unique users who streamed your music |
|
Shazams |
How often people are discovering your song in the real world |
|
Playlist Adds |
Which playlists your music is on, and how much traffic they drive |
|
Pre-Adds |
How many fans saved your song before release—important for playlist chances |
|
Geographic Data |
Where your fans are (cities, countries, regions) |
|
Top Songs |
Your best-performing tracks across all time or within a custom time range |
How to Use the Data to Improve Strategy
- Find Your Top Cities & Countries
- Target them with ads, content, and live shows
- Translate lyrics or do shoutouts for international fans
- Track Playlist Sources
- See which ones actually drive streams
- Pitch again with evidence of success
- Watch Shazam Trends
- Rising Shazams = buzz → push harder in that market
- Use the moment to fuel TikToks, Reels, or email blasts
- Compare Listener vs. Play Ratio
- A high play-per-listener ratio = fans replaying → strong engagement
- Promote those tracks more heavily
- Review Pre-Add Performance
- Strong pre-adds? Invest more in release day ads or retargeting
Mistakes to Avoid
- Ignoring low-performing tracks—ask why they didn’t connect
- Looking at just one number instead of patterns and relationships
- Failing to apply what you’ve learned in future release rollouts
Pro Tip:
Export your data monthly and build a simple spreadsheet to track growth over time. Look for patterns in song titles, artwork, or timing that led to spikes.