train-test split is required to evaluate all of metrics?

I have a hybrid recommender system. I use Precision to evaluate the result of recommender system, I think its not essential to split my data to train and test because I don't have any machine learning algorithm in my recommender system and I don't use MSE or RMSE or others error measurement. are you agree with me? or you think I have to split my data in train and test dataset?