Strategic planning in tourism requires a clear distinction between seasonal factors and seasonal patterns. Seasonal factors are numerical values derived from time series decomposition that quantify how specific periods deviate from a baseline average. In contrast, seasonal patterns offer a qualitative framework for understanding recurring fluctuations, helping managers anticipate long-term shifts in demand and operational capacity. The chapter details methods for data decomposition, including additive and multiplicative models, and surveys standard techniques such as Census X-11, TRAMO-SEATS, and the Holt-Winters method. It introduces waveforms to illustrate variations in seasonal timing and intensity, including horizontal and vertical shifts and stretches that reflect evolving traveler behaviors. Economic reasoning is applied to these patterns, highlighting how income elasticity, exchange rates, and climate variability interact with market cycles. The chapter also addresses the labor market implications of seasonality, noting the recruitment challenges and employment instability that arise in tourism-dependent regions. By 2 recognizing these patterns as fundamental economic forces, stakeholders can implement adaptive pricing and workforce strategies to maintain resilience in an increasingly volatile global landscape. This distinction between the “how much” and the “when” of seasonality provides practitioners with a precise vocabulary for managing destination sequences.