Joshua Franklin Wiedeman

Dayparting

Dayparting limits ad delivery to the hours and days when your audience is most likely to convert. You cut spend in weak hours and keep it in strong ones. It matters most for businesses where timing drives results, such as B2B, restaurants, appointment services, and anything that depends on phone calls.

How it works

Intent changes during the day. A B2B buyer is working at 10am and off at 10pm. A food delivery customer is active at 5pm, not 6am. By default, platforms serve ads around the clock. Dayparting moves spend away from hours that rarely convert. Note that automated bidding already adjusts by time of day. In Google Ads, ad schedule bid adjustments are ignored by Smart Bidding strategies such as target CPA and target ROAS. With those strategies, you can only include or exclude hours.

How to do it

  1. Pull performance by hour and day. In Google Ads, use the “Day & hour” report. In Meta, use the time-of-day breakdown. Use several weeks of data.
  2. Find weak windows: hours with high CPA or almost no conversions.
  3. Set the schedule. In Google Ads, add an ad schedule in campaign settings. In Meta, ad set scheduling requires a lifetime budget.
  4. If you use manual bidding, apply bid adjustments: lower bids in weak hours instead of switching off completely. With Smart Bidding, only exclude hours that clearly waste money.
  5. Set the schedule in the time zone where most customers are, or split campaigns by time zone.
  6. Review the schedule each month or each season.

What to measure

  • CPA by hour of day: chart CPA across all 24 hours to see peaks and dead zones.
  • Conversion rate by day of week: compare each weekday against the weekly average.
  • Share of spend in peak hours: divide spend in your best hours by total daily spend.

Best practices

  • For call-driven businesses, match the schedule to the hours someone can answer the phone.
  • Check the account time zone before setting hours.
  • Once a quarter, run without a schedule for a short period to see whether patterns have changed.

Common pitfalls

  • Deciding with too little data. Hourly data is noisy, and one week is not enough.
  • Switching off hours completely when a lower bid would still capture cheap conversions.
  • Adding schedule bid adjustments to Smart Bidding campaigns, where they have no effect.