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Hi there,
I'm interested in the solution of Optimize Marketing with Machine Learning (https://learn.microsoft.com/en-us/azure/architecture/solution-ideas/articles/optimize-marketing-with-machine-learning). It would be very helpful if someone could give me more insides into this solution.
I'm wondering whether I can use this for my use-case (campaign planning) and if so, how it would look like.
Kind regards,
Jerom
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Hi, thanks for reaching out. It depends on the ML problem you're trying to solve. This document provides guidance on how to select an algorithm. Below are some references. If you'd like to see us expand the article with more information, submit GitHub Feedback. Hope this helps!
Hi, thanks for helping me out. I'm looking for a type of algorithm that optimizes my sales (or say, net profit) given two (or more) input variables, namely a product and a budget. In other words: given a magazine I want to promote and the corresponding budget, I want to know which channels I can use best, so that net profit is optimized. Of course, I have enough data to train the model.
Thank you in advance!
Based on your inquiry, it seems you are trying to predict values (sales, prices) and categories (channels). So regression and classification algorithms would be appropriate. This document helps you to determine which algorithm to choose based on your business scenario but you'd have to build the optimization solution yourself. For a complete solution as suggested in the document, the best option is to submit GitHub Feedback. I will also share your feedback internally to determine if we have any existing solutions or share opportunity to create one for your scenario.
Thank you very much. I agree that regression and/or classification algorithms would be appropriate, and I understand that the optimization should be done by myself. However, as you already suggest, if there would be any existing solution which I could use for this particular problem, I would be very greatful. Thank you for asking around internally!