skill-152-historical-performance-benchmarking-seasonal-planning

Skill 152: Historical Performance Benchmarking for Seasonal Planning

Purpose

Pull and analyze prior-year performance data for seasonal periods to establish data-driven targets and budget recommendations. Historical benchmarking transforms seasonal planning from guesswork into informed strategy, preventing over- or under-investment during critical periods.

Data Requirements

Data Source: Custom GAQL Required

Standard 30-day export cannot provide prior-year comparisons. Need multi-year historical data for accurate benchmarking.

GAQL Query (Prior Year Seasonal Period):

SELECT
  campaign.name,
  campaign.advertising_channel_type,
  segments.date,
  metrics.impressions,
  metrics.clicks,
  metrics.cost_micros,
  metrics.conversions,
  metrics.conversions_value,
  metrics.average_cpc
FROM campaign
WHERE campaign.status IN ('ENABLED', 'PAUSED')
  AND segments.date BETWEEN '[PRIOR_YEAR_START]' AND '[PRIOR_YEAR_END]'

Run via /google-ads:get-custom for each seasonal period needing analysis (e.g., Black Friday 2025 to plan for 2026).

Analysis Steps

1. Identify key seasonal periods: Map all major events requiring historical analysis
2. Pull multi-year data: Query same periods across 2-3 years for trend analysis
3. Calculate benchmarks: Compute volume metrics (impressions, clicks, conversions) and efficiency metrics (CTR, CPC, CPA, ROAS)
4. Analyze trends: Identify growth rates, efficiency changes, and market shifts year-over-year
5. Set targets: Establish realistic targets based on historical trends plus growth assumptions

Thresholds

Condition	Severity
Major event planned without historical benchmark data	Critical
YoY efficiency decline >20% without acknowledged market shift	Warning
Budget target significantly higher than historical spend capacity	Warning
No multi-year comparison (single year data only)	Warning
Historical data unavailable (new account/campaign)	Info