Another popular branch of techniques is content-based filtering. The algorithms start with a description of items, and they don't need to take account of different users at the same time. For each user, the algorithms recommend items that are similar to its past purchases.
Here are the steps to perform a recommendation:
User profiles are based on their purchases, so the algorithms recommend items similar to past purchases.