Pull request analytics that measure how your changes really ship

Most dashboards stop at "PRs merged this week." That number tells you nothing about whether review is working. FeatureFactory measures the mechanics: PR size distribution, time-to-first-review, time-to-approval, review depth and revert rate - the signals that decide whether a change ships cleanly or blows up later.

Size is the lever most teams underuse. Large PRs get skimmed, sit longer, and revert more; small ones get read and merge fast. Once you can see the distribution across every repo, coaching toward smaller diffs stops being a vibe and becomes a measurable habit. See how it connects to PR quality analytics for per-PR scoring.

Turnaround is where velocity leaks. Splitting it into opened-to-first-review and first-review-to-approval shows exactly where changes wait. Take the product tour to see the full flow.

Merge velocity tells you how fast PRs go from opened to merged and whether throughput is trending up or down. But speed without quality is just faster mistakes, so we pair it with reviewer-quality signals - comment substance, lines inspected, requested changes - to distinguish deep reviews from reflexive approvals, all without ranking a single person.

Together they answer the question every engineering leader has: is our review process protecting us, or just adding latency? Everything aggregates across every repository and team into one view, then drills down to a single diff. Pair it with the Measure product and broader engineering metrics for context.

And because PRs are attributed to AI or human authorship, you can measure whether coding agents actually improve flow. If you are weighing tools, see how we compare to LinearB on depth of PR-level signal.