Several techniques can be applied to analyze time series data in email marketing: - Moving Averages: Helps to smooth out short-term fluctuations and highlight longer-term trends. - Exponential Smoothing: Gives more weight to recent observations, making it useful for predicting short-term trends. - ARIMA Models: Combines autoregression, differencing, and moving averages to model and forecast time series data. - Seasonal Decomposition: Breaks down the time series into seasonal, trend, and residual components.