Seasonality is a phenomenon that occurs each calendar year. The same behavior can be observed each year. A good forecasting model will be able to incorporate the effect of seasonality in its forecasts. Christmas is a great example of seasonality, where retailers have come to expect higher sales over the festive period.

Seasonality can extend into months but is usually only observed over days or weeks. When looking at time series where the periodicity is hours, you may find a seasonality effect for certain hours of the day. Some of the reasons for seasonality include holidays, climate, and changes in social habits. For example, travel companies usually run far fewer services on Christmas Day, citing a lack of demand. During most holidays people love to travel, but this lack of demand on Christmas Day could be attributed to social habits, where people tend to stay at home or have already traveled. Social habit becomes a driving factor in the seasonality of journeys undertaken on Christmas Day therefore.

It's easier for the forecaster when a particular seasonal event occurs on a fixed calendar date each year; the issue comes when some popular holidays depend on lunar movement, such as Easter, Diwali, and Eid. These holidays may occur in different weeks or months over the years, which will shift the seasonality effect. Also, if some holidays fall closer to other holiday periods, it may lead to individuals taking extended holidays and travel sales may increase more than expected in such years. The coffee shop near the office may also experience lower sales for a longer period. Changes in the weather can also impact seasonality; for example, a longer, warmer summer may be welcome in the UK, but this would impact retail sales in the autumn as most shoppers wouldn't need to buy a new wardrobe. In hotter countries, sales of air-conditioners would increase substantially compared to the summer months' usual seasonality. Forecasters could offset this unpredictability in seasonality by building in a weather forecast variable. We will explore similar challenges in the chapters ahead.

Seasonality shouldn't be confused with a cyclic effect. A cyclic effect is observed over a longer period of generally two years or more. The property sector is often associated with having a cyclic effect, where it has long periods of growth or slowdown before the cycle continues.