Cohort analysis
The Cohort analysis report compares engineering metrics side-by-side across user-defined segments of your organization. Define up to three cohorts based on team attributes, then see how each group performs relative to a baseline.
This report helps teams:
- Compare performance across segments — Measure how different teams, roles, locations, or any other attribute-based group stack up on key engineering metrics.
- Evaluate the impact of changes — See whether a new process, tool, or organizational change is moving the needle for a specific group compared to the rest of the organization.
- Identify areas for investment — Spot which segments are underperforming on cycle time, throughput, or developer experience so you can target support where it’s needed most.
- Benchmark against industry — Overlay industry P50/P75/P90 benchmarks on any metric to see how each cohort compares externally.

Setting up cohorts
The report starts with two groups: a Baseline and Cohort 1. You can add up to two more (three total in addition to the baseline) using the Add cohort button.
- Baseline — The reference group that all other cohorts are compared against. By default this is “All attributes across all users,” but you can customize it to any attribute set.
- Cohort 1–3 — Comparison groups. Select attributes to define each cohort’s membership.
Defining a cohort with attributes
Each cohort is defined by selecting one or more attributes from your organization’s attribute groups (e.g., Team, Location, Role). Attributes support both inclusion and exclusion:
- is / is any of — Include users matching the selected attribute values.
- is not / is not any of — Exclude users matching the selected attribute values.
You can combine multiple attribute groups within a single cohort for more targeted comparisons (e.g., “Team is Engineering and Location is not Remote”).
Metrics
Each metric is displayed as a tile in a responsive grid. Use the tiles dropdown (grid icon) to choose which metrics to display. Your tile selection is saved across sessions.
Available metrics
| Metric | Source | Description |
|---|---|---|
| TrueThroughput™ / PR throughput | System | Complexity-weighted throughput (when AI tools are enabled) or raw PR count per engineer per week |
| PR revert rate | System | Percentage of PRs that are reverted |
| PR cycle time | System | Time from first commit to PR merge |
| PR size | System | Lines of code per PR |
| Review comment density | System | Comments per PR |
| Review pushback | System | Reviews per PR before merge |
| Review turnaround | System | Time from review request to first review |
| Story points completed | System | Points completed per contributor (requires Jira connection) |
| Innovation ratio | System | Percentage of work allocated to feature development (when AI tools are enabled) |
| Defect ratio | System | Percentage of work allocated to bug fixes (when AI tools are enabled) |
| PR throughput (self-reported) | Snapshot | Self-reported throughput from developer surveys |
| DXI | Snapshot | Developer Experience Index score |
| Change failure (self-reported) | Snapshot | Self-reported change failure percentage |
| Allocation (self-reported) | Snapshot | Self-reported innovation ratio |
| Conditional drivers | Snapshot | Additional self-reported metrics based on your snapshot configuration (e.g., velocity, code maintainability, change confidence, focus time) |