VidPropel's public research program turns useful aggregate creator patterns into benchmarks without publishing individual customer histories or inventing impressive-looking numbers before the evidence exists.
A periodic privacy-safe view of creator momentum signals across qualifying anonymous cohorts.
Minimum cohort: 50+ qualifying observations
Storage: Aggregated cohort rollups only; no public user-level history.
Status: waiting for a privacy-safe sample. No placeholder benchmark is shown.
Aggregate packaging patterns from qualifying thumbnail checks, reported only when the cohort is large enough to avoid exposing individual creators.
Minimum cohort: 50+ qualifying observations
Storage: Aggregate score buckets and counts only.
Status: waiting for a privacy-safe sample. No placeholder benchmark is shown.
Aggregate readiness patterns from pre-spend Video Doctor checks, without claiming that a score guarantees distribution or views.
Minimum cohort: 50+ qualifying observations
Storage: Aggregate readiness buckets and counts only.
Status: waiting for a privacy-safe sample. No placeholder benchmark is shown.
A cohort-level view for smaller channels once enough comparable observations exist.
Minimum cohort: 75+ qualifying observations
Storage: Cohort aggregates only; no public channel identities.
Status: waiting for a privacy-safe sample. No placeholder benchmark is shown.
✓ No invented customer counts, CTR lifts, view gains or conversion claims.
✓ Cohorts must clear minimum sample thresholds before public reporting.
✓ Benchmarks describe patterns, not guaranteed outcomes.
✓ Long-term public learning favors compact aggregates over raw event histories.
✓ Methodology and limitations stay visible beside the result.
Public benchmarks will appear only when they qualify. The free tools are available immediately.