Calculate seasonality indices for monthly data to identify seasonal patterns in sales, demand, or other time-series data. Indices show how each month compares to the annual average.

Seasonality Indices:
Jan: 0.74, Feb: 0.82, Mar: 0.93, Apr: 1.16, May: 1.38, Jun: 1.27, Jul: 1.13, Aug: 1.06, Sep: 0.94, Oct: 0.83, Nov: 0.80, Dec: 0.95

Peak months: May, Jun, Jul, Aug, Apr
Low months: Jan, Feb, Nov, Oct, Mar

Formula: Index = Monthly Average ÷ Overall Average. Sum of all indices = 12. Values > 1 indicate above-average months.

What is a Seasonality Index?

A seasonality index (or seasonal coefficient) quantifies how a particular season — such as a month or quarter — compares to the average season [citation:6]. It is a fundamental tool in time-series analysis and business forecasting [citation:2][citation:5].

Seasonality Index = (Average for Season) ÷ (Overall Average)

The index value indicates relative performance [citation:4]:

• Index = 1 — the season is exactly average
• Index > 1 — above-average season (e.g., peak sales months)
• Index < 1 — below-average season (e.g., low demand months)

Seasonality indices are essential for:

• Sales forecasting — predicting future demand based on historical patterns [citation:4]
• Inventory management — optimizing stock levels for seasonal products [citation:7]
• Marketing strategy — timing promotions and campaigns effectively
• Resource planning — staffing and budgeting for seasonal fluctuations

For reliable results, use at least 2-3 years of historical data to smooth out anomalies and identify consistent patterns [citation:4][citation:7].

How to Use This Calculator

1. Enter Monthly Data: Input 12 monthly values separated by commas in the text area. For example: 70, 72, 85, 101, 123, 108, 99, 92, 80, 65, 69, 82
2. Calculate: Click the “Calculate Indices” button or press Enter.
3. Reset: Use the “Reset” button to restore the default example.
4. Interpretation: Results show each month’s seasonality index. Months with indices above 1.0 are peak periods; below 1.0 are low periods. For example, if May has an index of 1.38, sales in May are 38% above the annual average.