How to incorporate static information(time independent) to sequential(time dependent) data
You can add those data as feature to each activity. If you consider data as a table, basically you add more columns (features) to it. For this, you should consider also using one hot encoding as well.
I have a dataset that keeps a record of customer's activities on a website in a sequence. I have to predict whether the customer makes a purchase or not given his sequence of interactions with the site with LSTM network. However, I also have to incorporate some static info(like whether he is a prior client or not, his nationality,his gender etc.) about customer in the same LSTM network. How should I incorporate these static info. in my model?