skill-117-ad-schedule-waste-analysis

Skill 117: Ad Schedule Waste Analysis

Purpose

Identify time periods with high spend but low or zero conversions to optimize ad scheduling. Time-based optimization can reduce waste by 10-20% while maintaining conversion volume.

Data Requirements

Data Source: Custom GAQL Required

GAQL Query:

SELECT
  campaign.name,
  segments.hour,
  segments.day_of_week,
  metrics.impressions,
  metrics.clicks,
  metrics.cost_micros,
  metrics.conversions,
  metrics.conversions_value
FROM campaign
WHERE segments.date DURING LAST_30_DAYS
  AND campaign.status = 'ENABLED'
  AND metrics.impressions > 0
ORDER BY campaign.name, segments.day_of_week, segments.hour

Run via /google-ads:get-custom with query name ad_schedule_analysis.

Analysis Steps

1. Pull Hourly Performance: Get performance by hour and day of week
2. Analyze Day-of-Week Patterns: Identify high-CPA days, zero-conversion days
3. Analyze Hour-of-Day Patterns: Find zero-conversion hours, off-hours waste
4. Create Performance Heatmap: Identify worst day/hour combinations

Thresholds

Condition	Severity
Day with zero conversions and >$100 spend	Critical
Hours with zero conversions (multiple days)	Warning
Weekend CPA >2x weekday CPA	Warning
Off-hours (12am-6am) spend >10% of budget	Info

Output

Short (default):

## Ad Schedule Waste Analysis
**Account:** [name] | **Period:** Last 30 days | **Account CPA:** $[amount]

### Day-of-Week Performance
| Day | Spend | Conv | CPA | vs. Avg |
|-----|-------|------|-----|---------|
| [worst day] | $[amount] | [count] | $[amount] | +[%] |

### Zero-Conversion Periods
- **[day] [hours]**: $[amount] spent, 0 conversions
- **Off-hours (12am-6am)**: $[amount] spent, [count] conversions

### Recommendations
1. Exclude [time periods] - Save $[amount]/month
2. Reduce bids -50% on [days/hours] with high CPA
3. Increase bids +20% on [best performing periods]

Detailed adds:

• Full day-of-week performance table
• Hour-of-day performance table
• Performance heatmap (day x hour)
• Bid adjustment schedule recommendations