How to incorporate multi-task in CTR/recommendation model (deep & wide/ xDeepFM etc)?

I am building a rank algorithm for an e-commerce website that ranks the product based on likely hood of purchase and I have formulated this problem into a binary classification problem. Given each visitor information and predict on the purchase event propensity score of each product then sort.

But because a purchase event is a lower-funnel event and I would like also to optimize for other metrics for example click-through-rate, add to cart, purchase, repurchase, etc.

Currently, the model is xDeepFM and I am thinking of adding a multi-task layer to balance the above event and I am wondering if anybody else has tried this before and whats things to be considered in this scenario? thank you!