Analyzes 36+ months of search volume history from the Google Ads API to detect seasonal patterns. Uses sophisticated algorithms to identify local spikes, elevated plateaus, and multi-year consistency. Helps you time content publishing, ad campaigns, and inventory planning around predictable demand cycles.
@seasonalityGets 36-month search volume data from Google Ads API
Identifies months with volume significantly above neighbors
Finds extended periods of elevated search interest
Checks if patterns repeat across multiple years
Assigns seasonality scores (0-100) based on strength and consistency
keywordstextRequiredKeywords to analyze (one per line or comma-separated)regionselect (11 options)OptionalTarget country Default: USKeyword: "winter coats" ✓ Seasonal — Score: 94/100 Peak months: OCT (score: 88), NOV (score: 94), DEC (score: 82) Plateau: SEP-JAN (15% above baseline) Avg volume: 49,500 — Peak volume: 135,000 (NOV) Consistency: 3/3 years Keyword: "running shoes" ✗ Not seasonal — Score: 12/100 Volume is stable year-round (±8% variation) Avg volume: 74,000 Keyword: "sunscreen" ✓ Seasonal — Score: 89/100 Peak months: MAY (score: 78), JUN (score: 89), JUL (score: 86) Avg volume: 33,100 — Peak volume: 90,500 (JUN) Consistency: 3/3 years
Seasonality analysis per keyword
KeywordHas SeasonalitySeasonal MonthsMonth ScoresAvg Monthly SearchesStart using this workflow right now — just describe your task in natural language.
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