Seasonality Detector
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.
Try Seasonality Detector
@seasonality
How it works
01
Fetch History
Gets 36-month search volume data from Google Ads API
02
Spike Detection
Identifies months with volume significantly above neighbors
03
Plateau Detection
Finds extended periods of elevated search interest
04
Consistency Validation
Checks if patterns repeat across multiple years
05
Score Calculation
Assigns seasonality scores (0-100) based on strength and consistency
Parameters
ParameterTypeRequiredDescription
keywordstextRequiredKeywords to analyze (one per line or comma-separated)regionselect (11 options)OptionalTarget country Default: USExample queries
Detect seasonality for running shoes, winter coats, sunscreen
@seasonality keywords: summer dresses, winter boots, beach gear in US
Find seasonal patterns for holiday-related keywords
When is peak season for "Christmas gift ideas"?
Example output
Keyword: "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
Output formats
CSV
Seasonality analysis per keyword
KeywordHas SeasonalitySeasonal MonthsMonth ScoresAvg Monthly SearchesUse cases
Time content publishing around seasonal demand peaks
Plan ad spend allocation across the year
Identify evergreen vs. seasonal keywords
Optimize inventory and promotions for e-commerce