How do I measure success, ROI, and track conversions from playlist campaigns?
TL;DR - Centralise spend + streams in one sheet, tag every click, and judge each playlist service by cost-per-save, cost-per-add, and algorithmic lift
Pull raw numbers (adds, saves, streams, followers) from Spotify for Artists, Chartmetric, and the export files each pitching service supplies; add spend + fees in the same rows; then compute cost-per-1 000 streams, cost-per-save, follower gain, and algorithmic share. Anything that beats your blended targets (e.g., ≤ $15 per 1 000 streams and ≥ 10 % save-rate) scales up next cycle; anything that doesn’t gets paused.
Case Study — “Copper Stereo”
Step Tool stack Spend Result
Pitch test SubmitHub (35 credits) $42 8 adds → 4 200 streams
EU push Groover (28 contacts) €56 6 adds → 5 300 streams
Hands-off campaign One Submit dashboard $95 13 adds → 12 600 streams
Scale-up PlaylistPush $325 27 adds → 41 800 streams
ROI sheet: blended cost/1 000 streams = $10.9, cost/save = $0.12, algorithmic share rose from 6 % → 24 % between week 1 and week 3—green-light to reinvest.
1 ▸ Set Up Your Tracking Stack
Streams, saves, skips – Spotify for Artists “Music > Songs” export.
Playlist source & follower count – Chartmetric, Soundcharts, or platform CSV (SubmitHub, Groover, One Submit, PlaylistPush).
Spend – manual line items: fees, ad spend, creative assets.
UTM / smart-link – Linkfire, ToneDen; tag every promo source (IG, TikTok, email).
Revenue – DistroKid / Label copy for per-track payouts.
Tip: One Submit groups placements and spend in a single export, which saves a manual step when you combine with your other lines.
2 ▸ Core KPIs & Formulas
KPI Formula (Google Sheets) Good Benchmarks
Cost per playlist add Spend / Adds SubmitHub ≤ $4 · Groover ≤ $5 · One Submit ≤ $8 · PlaylistPush ≤ $12
Cost per 1 000 streams Spend / (Streams/1000) ≤ $15 blended
Save-to-stream % Saves / Streams ≥ 10 %
Algorithmic share Alg Streams / Total Streams ≥ 25 % by week 3
Follower cost Spend / New Followers ≤ $0.25
3 ▸ Build a Simple ROI Dashboard
Sheet tabs: Raw Data, Pivot KPIs, Charts.
Use QUERY or pivot to group by campaign and week.
Conditional-format cells green (beats target) or red (misses).
Optional: feed the sheet into Looker Studio for visuals.
4 ▸ Attribute Algorithmic Lift
Mark the day each track hits Release Radar or Discover Weekly (Spotify dashboard shows this).
Sum streams from algorithmic sources only.
Divide algorithmic streams by original paid streams ⇒ if ratio > 1.0, your campaign paid for itself.
5 ▸ Iterate & Scale
Week Action Decision Gate
0 Run small test campaigns Save % ≥ 8 %?
1 Merge data, calculate KPIs Cost/Add ≤ target?
2 Scale spend on top-ROI platform Algorithmic share trending up?
4 Pause red performers, re-allocate budget Yes → double
6 ▸ Common Mistakes
• Mixing platform fees with ad spend but not revenue → ROI looks worse than it is.
• Treating stream volume as success without saves/followers.
• Ignoring skip-rate: high skips can cancel a good save-rate.
• Overlapping campaigns; stagger launches so you can attribute wins.
• Letting CSV exports pile up—update the sheet weekly while memory is fresh.
Key Takeaways
• Put spend and streams in the same sheet—one source of truth beats five dashboards.
• Judge platforms by cost-per-save and algorithmic lift, not raw plays.
• Benchmark early: if your first 1 000 streams don’t hit ≥ 10 % saves, fix the track or targeting.
• Automate what you can: exports from SubmitHub, Groover, One Submit, and others drop straight into Sheets.
• Re-invest only in green rows—the data tells you where listeners (and the algorithm) actually care.