Forecasts are equal to the value of the last observation.
Use STL decomposition (Seasonal-Trend decomposition using LOESS) to break down the user's data into Trend, Seasonality, and Remainder components. Forecasting: Principles and Practice
Display a leaderboard using the book's recommended error metrics like MAE (Mean Absolute Error) and RMSE (Root Mean Squared Error) to identify which benchmark is hardest to beat. Forecasts are equal to the value of the last observation
Forecasts are equal to the last observed value from the same season. Forecasting: Principles and Practice