how to predict content based demand
Welcome to the site. I would encourage you to think about your problem in a different way. You are focused on "what sold today" whereas you should be focused on "who bought what over a historical timeline". 

What you're looking for is known as a recommender system and there are (generally speaking) two types:


Content-based - what should you recommend based on attributes of products. The algorithm is basically saying, "You bought breakfast cereal, here are other products that might go with your cereal . . ."
Community-based - what should you recommend based on attributes of people who bought products. The algorithm is basically saying, "You are a female, under 30, with no kids. Other females, under 30 with no kids also liked these products . . ."


I will assume that you don't have info on your customers so let's focus on the content-based recommenders. You are on the right track by thinking about the attributes of products, but you should be thinking about them both (1) over a longer timeline than just yesterday and (2) how the products and their attributes relate to each other. The people who need attribute X might also need attribute Y and that is (most likely) across multiple products and will generate higher demand for those products. 

Start researching content-based recommender systems in your language/tool of choice and you will end up with the desired algorithm. From there you can also think about user data collection and then move into a community-based recommender over the long term.