This is kind of a low effort post but I’ll bite. I think your issue, if you’re only now building a platform, is lack of data. Recommender systems typically require data, be it history of the users’ interactions or at least data about the items being recommended. If you are creating a platform entirely from cold start this will be a challenge. If your items have semantic meaning, maybe generate text embeddings for the names/descriptions and then on the product page add a tab such as “Similar items…” which retrieves the top 5 neighbors per those text embeddings. Boom, recommender system.
This is kind of a low effort post but I’ll bite. I think your issue, if you’re only now building a platform, is lack of data. Recommender systems typically require data, be it history of the users’ interactions or at least data about the items being recommended. If you are creating a platform entirely from cold start this will be a challenge. If your items have semantic meaning, maybe generate text embeddings for the names/descriptions and then on the product page add a tab such as “Similar items…” which retrieves the top 5 neighbors per those text embeddings. Boom, recommender system.