The RecSys 2022 Challenge was a session-based recommendation task in the fashion domain. The dataset was supplied by Dressipi. Given session data consisting of views and purchases, as well as content data representing the fashion characteristics of the items, the task was to predict which item was purchased at the end of the session. The challenge ran for 3 months with a public leaderboard and final result on a separate hidden test set. There were over 300 teams that submitted a solution to the leaderboard and about 50 that submitted a solution for the final test set. The winning team achieved a MRR score of 0.216 which means that the correct target item was on average ranked 5th in the list of predictions. We identify some interesting common themes among the solutions in this paper and the winning approaches are presented in the workshop.