Your question is Seasonality Versus Product Issue Detection. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You're monitoring a key product metric and notice a drop that could be normal weekly or monthly seasonality, or it could reflect a real issue in the product. You need to separate expected time-based variation from a true underlying change.
How would you use time-based trends to separate seasonality from a real product issue?