[rodrigoi]

Problem

Ratio metrics are the last type still attributing breakdowns from the exposure event; funnels, mean, and retention migrated in #61796, #62291, #62292.

Changes

This PR migrates ratio metrics to MetricBreakdownInjector, completing the per-type migration behind the experiment-metric-event-breakdowns flag.

Ratio support in the injector

Ratio is Σnumerator / Σdenominator over two event streams, pre-aggregated per entity before joining exposures. To keep one experiment unit in exactly one bucket (so per-breakdown rows sum to the overall result), the whole user is attributed by their numerator event: read off numerator_events, first touch via argMin in numerator_agg, carried through entity_metrics with any(). Winsorized ratio queries reuse the mean winsorization carry-through helper.

• products/experiments/backend/hogql_queries/metric_breakdown_injector.py
• products/experiments/backend/hogql_queries/experiment_query_runner.py
• products/experiments/backend/hogql_queries/experiment_ratio_query_builder.py

Migration complete

All four metric types now use the metric-event injector when the flag is on. Deleting the old BreakdownInjector is a follow-up once the flag rolls out.

Tests

Flag-on ratio cases in test_metric_breakdown.py (numerator attribution, winsorization, limit, Other bucket) plus injector unit tests.

• products/experiments/backend/hogql_queries/test/experiment_query_runner/test_metric_breakdown.py
• products/experiments/backend/hogql_queries/test/test_metric_breakdown_injector.py

How did you test this code?

pnpm turbo run backend:test --filter=@posthog/products-experiments

👉 Stay up-to-date with PostHog coding conventions for a smoother review.

Automatic notifications

• Publish to changelog?
• Alert Sales and Marketing teams?

Docs update

🤖 Agent context

Autonomy: Human-driven (agent-assisted)

Model: Opus 4.7 (implementation), Fable 5 (restack and PR description)
Manually refactored: yes

Skills used:

• /writing-tests (local)
• /writing-pull-requests (local)

Relevant decisions:

• Numerator-event attribution keeps each experiment unit in a single breakdown bucket, which is what makes per-breakdown results sum to the overall ratio.
• The denominator is never a breakdown source; a user can have denominator events in several buckets, which would double-count units.

[rodrigoi]

Warning

This pull request is not mergeable via GitHub because a downstack PR is open. Once all requirements are satisfied, merge this PR as a stack on Graphite.
Learn more

• feat(experiments): add ratio metrics to the metric breakdown injector #62293 👈 (View in Graphite)
• feat(experiments): add retention metrics to the metric breakdown injector #62292
• feat(experiments): add metric breakdown injector for mean metrics #62291
• feat(experiments): add metric breakdown injector for funnels #61796
• feat(experiments): add breakdown attribution to the metric row group #61788
• master

This stack of pull requests is managed by Graphite. Learn more about stacking.

[greptile-apps]

Comments Outside Diff (1)

1. products/experiments/backend/hogql_queries/test/experiment_query_runner/test_metric_breakdown.py, line 607-612 (link)

   Denominator-only bucket not asserted

   The test verifies Chrome is present but doesn't assert what bucket denominator-only users land in. Because these users have no numerator event, any(null) in entity_metrics yields null for their breakdown column. The final if(in_top, value, other) expression evaluates null IN (subquery) as null, which routes them to the BREAKDOWN_OTHER_STRING_LABEL bucket — they are not dropped, and their denominator_value is included in "Other". Adding an assertion like self.assertIn([BREAKDOWN_OTHER_STRING_LABEL], breakdown_values) would lock in this behavior and prevent a silent regression if the attribution logic changes.

   Prompt To Fix With AI

   This is a comment left during a code review.
   Path: products/experiments/backend/hogql_queries/test/experiment_query_runner/test_metric_breakdown.py
   Line: 607-612
   
   Comment:
   **Denominator-only bucket not asserted**
   
   The test verifies Chrome is present but doesn't assert what bucket denominator-only users land in. Because these users have no numerator event, `any(null)` in `entity_metrics` yields null for their breakdown column. The final `if(in_top, value, other)` expression evaluates `null IN (subquery)` as null, which routes them to the `BREAKDOWN_OTHER_STRING_LABEL` bucket — they are *not* dropped, and their `denominator_value` is included in "Other". Adding an assertion like `self.assertIn([BREAKDOWN_OTHER_STRING_LABEL], breakdown_values)` would lock in this behavior and prevent a silent regression if the attribution logic changes.
   
   How can I resolve this? If you propose a fix, please make it concise.

Prompt To Fix All With AI

Fix the following 1 code review issue. Work through them one at a time, proposing concise fixes.

---

### Issue 1 of 1
products/experiments/backend/hogql_queries/test/experiment_query_runner/test_metric_breakdown.py:607-612
**Denominator-only bucket not asserted**

The test verifies Chrome is present but doesn't assert what bucket denominator-only users land in. Because these users have no numerator event, `any(null)` in `entity_metrics` yields null for their breakdown column. The final `if(in_top, value, other)` expression evaluates `null IN (subquery)` as null, which routes them to the `BREAKDOWN_OTHER_STRING_LABEL` bucket — they are *not* dropped, and their `denominator_value` is included in "Other". Adding an assertion like `self.assertIn([BREAKDOWN_OTHER_STRING_LABEL], breakdown_values)` would lock in this behavior and prevent a silent regression if the attribution logic changes.

_{Reviews (1): Last reviewed commit: "feat(experiments): add ratio metrics to ..." | Re-trigger Greptile}

[scheduled-actions-posthog]

This PR hasn't seen activity in a week! Should it be merged, closed, or further worked on? If you want to keep it open, please remove the stale label – otherwise this will be closed in another week. If you want to permanently keep it open, use the waiting label.

[trunk-io]

   

View Full Report ↗︎ ⋅ Docs

[greptile-apps]

_{Reviews (2): Last reviewed commit: "feat(experiments): add ratio metrics to ..." | Re-trigger Greptile}

[github-actions]

🤖 CI report

⚠️ Backend coverage — 98.0% of changed backend lines covered — 25 uncovered

🧪 Backend test coverage

Patch coverage — changed backend lines (products + core): ████████████████████ 98.0% (1,316 / 1,341)

File	Patch	Uncovered changed lines
products/experiments/backend/hogql_queries/metric_breakdown_injector.py	88.7%	60, 74, 239–240, 242–243, 245–249, 251–255, 259, 264, 308, 355, 431, 450, 481, 500
products/experiments/backend/hogql_queries/test/test_metric_breakdown_injector.py	99.7%	351

🤖 Agents: add a test covering the lines above, or note why under "How did you test this code?". Machine-readable gap list: the patch-coverage artifact on this run (gh run download 31864211158 -n patch-coverage), or the coverage-data block at the end of this comment.

Per-product line coverage (touched products)

Product	Coverage	Lines
platform_features	██░░░░░░░░░░░░░░░░░░ 12.1%	7 / 58
warehouse_sources_queue	███████░░░░░░░░░░░░░ 36.1%	91 / 252
batch_exports	████████░░░░░░░░░░░░ 39.2%	8,862 / 22,581
demo	███████████░░░░░░░░░ 56.3%	1,497 / 2,661
data_tools	█████████████░░░░░░░ 66.2%	90 / 136
tasks	██████████████░░░░░░ 70.2%	38,633 / 55,017
ai_gateway	███████████████░░░░░ 75.0%	9 / 12
signals	█████████████████░░░ 83.1%	28,098 / 33,794
apm	█████████████████░░░ 83.9%	1,222 / 1,457
cdp	█████████████████░░░ 84.2%	3,914 / 4,649
actions	█████████████████░░░ 86.6%	717 / 828
wizard	█████████████████░░░ 86.7%	1,090 / 1,257
data_modeling	█████████████████░░░ 86.9%	9,631 / 11,082
notebooks	█████████████████░░░ 87.2%	8,547 / 9,806
cohorts	██████████████████░░ 87.6%	6,528 / 7,452
product_tours	██████████████████░░ 87.9%	1,303 / 1,482
managed_warehouse	██████████████████░░ 88.8%	6,659 / 7,503
data_warehouse	██████████████████░░ 88.8%	12,468 / 14,043
business_knowledge	██████████████████░░ 89.0%	4,384 / 4,928
exports	██████████████████░░ 89.2%	7,597 / 8,520
engineering_analytics	██████████████████░░ 89.4%	6,839 / 7,649
dashboards	██████████████████░░ 89.5%	6,221 / 6,954
visual_review	██████████████████░░ 89.5%	5,870 / 6,558
mcp_analytics	██████████████████░░ 90.4%	3,968 / 4,388
alerts	██████████████████░░ 90.6%	4,676 / 5,163
links	██████████████████░░ 90.6%	183 / 202
streamlit_apps	██████████████████░░ 90.7%	2,630 / 2,901
conversations	██████████████████░░ 90.8%	19,958 / 21,989
error_tracking	██████████████████░░ 91.2%	11,345 / 12,435
stamphog	██████████████████░░ 91.3%	4,505 / 4,936
slack_app	██████████████████░░ 92.4%	11,278 / 12,212
managed_migrations	███████████████████░ 92.6%	1,556 / 1,681
early_access_features	███████████████████░ 92.9%	1,347 / 1,450
notifications	███████████████████░ 92.9%	1,060 / 1,141
web_analytics	███████████████████░ 92.9%	16,337 / 17,578
ai_observability	███████████████████░ 93.1%	17,445 / 18,744
mcp_store	███████████████████░ 93.1%	7,411 / 7,957
canvas	███████████████████░ 93.2%	3,328 / 3,572
posthog_ai	███████████████████░ 93.2%	1,326 / 1,422
surveys	███████████████████░ 93.3%	5,943 / 6,373
reminders	███████████████████░ 93.4%	468 / 501
marketing_analytics	███████████████████░ 93.5%	16,413 / 17,559
approvals	███████████████████░ 93.5%	3,491 / 3,734
product_analytics	███████████████████░ 93.6%	7,126 / 7,614
review_hog	███████████████████░ 94.1%	9,383 / 9,973
legal_documents	███████████████████░ 94.1%	1,926 / 2,047
endpoints	███████████████████░ 94.3%	8,814 / 9,349
workflows	███████████████████░ 94.4%	8,084 / 8,564
tracing	███████████████████░ 94.4%	2,678 / 2,837
skills	███████████████████░ 94.7%	3,869 / 4,085
annotations	███████████████████░ 95.1%	732 / 770
data_quality	███████████████████░ 95.3%	1,457 / 1,529
logs	███████████████████░ 95.5%	12,644 / 13,244
messaging	███████████████████░ 95.6%	3,423 / 3,580
experiments	███████████████████░ 95.6%	30,226 / 31,608
replay_vision	███████████████████░ 95.9%	21,571 / 22,492
customer_analytics	███████████████████░ 96.1%	13,646 / 14,199
revenue_analytics	███████████████████░ 96.3%	1,887 / 1,960
user_interviews	███████████████████░ 96.5%	2,638 / 2,734
feature_flags	███████████████████░ 96.6%	18,993 / 19,653
access_control	███████████████████░ 96.7%	873 / 903
growth	███████████████████░ 96.7%	6,494 / 6,717
warehouse_sources	████████████████████ 97.5%	393,119 / 403,174
data_catalog	████████████████████ 97.8%	2,747 / 2,808
analytics_platform	████████████████████ 98.1%	2,254 / 2,298
metrics	████████████████████ 98.2%	2,491 / 2,536
pulse	████████████████████ 98.4%	2,017 / 2,049
live_debugger	████████████████████ 99.2%	613 / 618
field_notes	████████████████████ 99.4%	158 / 159

Report-only. Patch coverage = changed backend lines covered vs origin/master. Sorted lowest first.
Known gaps: lines covered only by Temporal tests show as uncovered; core line numbers may drift if master changed the same file.

[andehen]

Findings from a review of the full stack (#61788, #61796, #62291, #62292, #62293), placed on the PR where each belongs. Prefixes: should-fix, suggestion, nit.