# Review Google Ads dayparting against actual performance

> Tier: recipe. Operating recipe: real tool sequence, core rules, known traps.

Hour-and-day performance against the campaign's schedule settings.

**Intent.** Whether the schedule matches when conversions actually happen.

## When to use

- Lead-gen accounts with opening hours.
- After 'we should advertise less at night' opinions.

## When not to use

- Smart bidding campaigns where schedules mostly gate rather than bid: read what the strategy honours first.

## Sources

Required: Google Ads

## Preconditions

- The account is ticked in the dashboard, confirmed via list_accounts.

## Inputs

- `window`: Analysis window. Default: last 30 days.

## Procedure

1. Run the hour/day segmentation query over a long window. — tools: `google_ads_run_gaql`
2. Read the campaign's current schedule. — tools: `google_ads_get_campaigns`

## Decision rules

- **When** Conversions cluster in hours the schedule excludes → **conclude** The schedule fights the data: quantify the excluded conversions.
- **When** Night hours convert at lower CPA than office hours → **conclude** Do not cut them on instinct: cheap hours are often cheap because competitors sleep.

## Evidence requirements

- Every figure carries its account, metric and window.
- Anything below a readable sample size is reported as unjudged, not as zero.

## Human approval boundary

- The readout changes nothing. Any change it motivates goes through Safe Writes: preview, human confirmation, then apply.

## Failure modes

- Conversion time is recorded at click or at conversion depending on the report: name which one the table uses.

## Output

- **Readout**: The figures, with windows and accounts named.
- **Flags**: What deserves a deeper skill or a human decision.