# Intuition about Exponential Smoothing parameters?

If I use Triple Exponential Smoothing with Additive Seasonality and let a statistical program optimize alpha, beta and gamma for me, is there something I can conclude about my data based on the resulting parameters?

E.g. my alpha tends to be close to 0 and my beta close to one for several data sets. (I don't see anything tendency in gamma)

When looking at the formula for level L for example, L is

Lt = α × (Xt − St−L) + (1 − α) × (Lt−1 + Tt−1)

And when alpha is close to zero, the first addend more or less gets omitted. Same with a beta close to one, the second addend gets or less omitted in:

Tt = β × (Lt − Lt−1) + (1 − β) × Tt−1

Could I say a high beta tends to ignore the previous trend, making the trend depend more on the Level, and similar with a low alpha that level does not depend on seasonality? Or am I overinterpreting?

I am relatively new to time series forecasting.