Benchmark cohorts
How customers in your shape are actually performing
A real cohort table, not a marketing chart. Quarterly snapshot across 342 active workspaces. Aggregated, anonymised, opt-in. Methodology, confidence intervals, and the JSON behind every cell are linked below.
Workspaces
342
Opt-in to anonymous benchmarking
Median pacing accuracy
98.6%
Daily, 30-day rolling
Median forecast MAPE
3.8%
14-day horizon, all platforms
Snapshot window
2026 Q1
Refreshes 15th of each quarter
By spend band
| Cohort | N | Pacing accuracy |
|---|---|---|
| < €250k / mo | 84 | 97.2% |
| €250k – €1M / mo | 142 | 98.4% |
| €1M – €5M / mo | 76 | 98.9% |
| €5M – €25M / mo | 31 | 99.2% |
| > €25M / mo | 9 | 99.4% |
By industry
| Cohort | N | Pacing accuracy |
|---|---|---|
| E-commerce | 138 | 98.6% |
| Subscription / SaaS | 64 | 98.9% |
| Marketplace | 27 | 98.1% |
| Agency portfolio | 89 | 98.3% |
| DTC / lifestyle | 24 | 98.7% |
| Travel / hospitality | 10 | 97.6% |
By platform mix
| Cohort | N | Pacing accuracy |
|---|---|---|
| Google + Meta | 124 | 98.8% |
| Google + Meta + TikTok | 96 | 98.4% |
| + Spotify | 58 | 98.1% |
| + Spotify | 22 | 97.8% |
| Full coverage (5+) | 18 | 98.3% |
Methodology, in plain language
- Every metric is computed from the same definitions we use internally on /open-metrics — no marketing reframes.
- Cohorts under 9 workspaces are suppressed to protect customer identifiability.
- Confidence intervals are 95% bootstrap CIs over the cohort distribution; the median is reported, not the mean.
- The raw aggregations are published as JSON in /data-room. You may re-derive every cell yourself.