Data scientist and entrepreneur with a focus on building innovative products and teams. Founder at Bitten Labs (data science consultancy and innovation lab). Previously head of data science at Litle & Co, acquired by Vantiv.
I've been producing paid information products for years in a variety of industries, usually with a significant analytics/data science component. I currently run a consulting firm that helps companies build products that use data and analytics, and would be happy to chat. I don't charge for calls on Clarity, so zero commitment.
The solution that is best for you depends on many things - what other features there will be besides just profile pages, what kind of scale you anticipate in the near term, your technical fluency or willingness to partner with a more technical person, etc. CMSs like Wordpress and Drupal are great for certain things, but customizations still take a lot of time and some technical fluency so the total cost/pain of implementation may end up being significantly higher than a custom coding job. It's really easy to stand up a basic and extensible profile page system with a modern framework (e.g. Meteor, Ruby on Rails, Django), so if you have enough technical fluency or are willing to partner with someone who does I generally tend to recommend starting there.
I'm a data scientist and look into questions like this frequently. Until recently, I ran the data science organization at a payment processor, where we answered questions like this for merchants on a daily basis, and also built products at scale to help inform merchants' decision making.
The question here really is: can you predict these sales numbers well enough to inform specific buying and manufacturing decisions? Sales numbers are difficult to predict precisely for many reasons (week to week fluctuations can be pretty high, seasonality can be a big factor depending on what you're selling, it's very helpful but often difficult to separate sales from existing and new customers, etc.), but as long as you can predict them well enough and far enough in advance to make better decisions you can create a positive financial impact. The point is that this isn't so much a question about predicting the sales as well as you can, but a question about optimizing your decision making process.
Therefore, I'd encourage you to engage the help of someone who has experience in solving operational business problems using data. One of the first things a good data person should do is help you quantify the size of the problem - how much money you can save by doing this analysis. This will help you determine how much time and money to put into it to make sure that the project has a positive return on investment.