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On my website, there are fully-priced items and discounted items (discounted items can be fully-priced also, so this is a time dependent analysis). I need to source discounted items from the existing fully-priced items, but I am unsure which items to source and provide as a discounted item in order to increase sales of discounted items. I also offer multiple items that are the same thing (e.g. 5 types of 'Bose Headphones') so differentiating which should go on sale is important.

My first attempt was to look at metrics such as:

  1. What items sold the most as discounted vs normal (I am assuming there is an incremental value in having the item discounted).
  2. What items had the most views (I am assuming a correlation between high views and things people want).
  3. What items had the work 'discount, deal or cheap' with the search (I guessed this indicated they wanted it cheaper).
  4. Who is likely to visit over the next week (based on previous visits) and try to customise the discounts for them.

and conduct a multiple regression analysis. However, this doesn't really tell me what products are "better" to source as a deal in order to maximise revenue.

Another approach is to use a linear programming method with the objective function as max(revenue) but then I am still unsure how this helps select the products themselves.

Once this is solved, the next piece would be to understand the propensity of purchase as a discounted product vs not, but this is more straightforward when you have 2 cohorts, which is what I am trying to figure out here.

Does anyone have any ideas on how else this problem can be approached?

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