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FORECAST.ETS.SEASONALITY Function
Summary
The FORECAST.ETS.SEASONALITY function analyzes historical time series data to automatically detect and return the length of the seasonal pattern. This advanced forecasting tool uses Exponential Triple Smoothing (ETS) algorithms to identify repeating cycles in your data without manual pattern specification.
Syntax
FORECAST.ETS.SEASONALITY(values, timeline, [data_completion], [aggregation])Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| values | Range/Array |
Yes | The historical values to analyze for seasonal patterns |
| timeline | Range/Array |
Yes | Date/time values corresponding to the historical data |
| data_completion | Number |
No | 0=Connect points, 1=Zero, 2=Interpolate (default=0) |
| aggregation | Number |
No | 1=Average, 2=Sum, 3=Count, 4=Min, 5=Max (default=1) |
Using the FORECAST.ETS.SEASONALITY Function
FORECAST.ETS.SEASONALITY helps determine the optimal seasonal period length before using other ETS forecasting functions. It examines your time series data and identifies repeating patterns, making it essential for accurate sales forecasting, inventory planning, and trend analysis.
Common FORECAST.ETS.SEASONALITY Examples
Detect Monthly Sales Seasonality
=FORECAST.ETS.SEASONALITY(B2:B25, A2:A25)Analyzes 2 years of monthly sales data and returns 12 if monthly seasonality is detected.
Handle Missing Data with Interpolation
=FORECAST.ETS.SEASONALITY(sales_data, dates, 2)Uses interpolation (2) for missing sales values during seasonality detection.
Daily Data with Average Aggregation
=FORECAST.ETS.SEASONALITY(daily_sales, daily_dates,,1)Detects weekly patterns (7) in daily sales data using average aggregation.
Frequently Asked Questions
Common Errors and Solutions
#VALUE!
Cause: Values and timeline arrays have different sizes or contain non-numeric data
Solution: Ensure both ranges contain the same number of elements and timeline has valid dates
#NUM!
Cause: Insufficient data points or no clear seasonal pattern
Solution: Provide more historical data (at least 2 full cycles)
#VALUE!
Cause: Invalid data_completion or aggregation parameter
Solution: Use only valid numbers: data_completion (0,1,2), aggregation (1-5)
Notes
- Returns integer representing seasonal periods (1=no seasonality, 7=weekly, 12=monthly, etc.)
- Available only in Excel 2016+ and Microsoft 365
- Use result as seasonality parameter in FORECAST.ETS
- Maximum timeline length: 10,000 points
- Performs AAA ETS model selection automatically
Compatibility
Available in: Excel 2016, Excel 2019, Excel 2021, Excel for Microsoft 365
Not available in: Excel 2013 and earlier, Excel for Mac 2011, Excel Online (limited)
Content last reviewed: December 9, 2025
Update frequency: As needed
Excel versions tested: Excel 2016+, Excel for Microsoft 365