Hell ya I love what we got going in here. @OP let me know when you make progress and share your code, would ya?

Never ask ‘how can I do X using Y’

Ask ‘how can I do X’

Well, you could calculate distance of all product names or descriptions using some textdistance metric, e.g., rapidfuzz, and then apply clustering on that distance matrix. Resulting clusters would correspond to the products. If you had product images, you could do with some image distance metric.

That’s not really an ML problem. It’s a search problem. You’d need an index (or at least db) of all e-commerce products. Then you can potentially use ML to find competitors, but I feel like for this you don’t need ML — a simple if statement for the two products being of the same type will suffice.

First of all, do you already have the data? Scraping and maintaining an updated product list is an entirely separate task and it is not easy.

If you have already scrapped the data, what data do you have? Just title, or you have the description, brand, model number, images? There was a kaggle competition on matching two products on Shopee for price match guarantee(based on titles and images). You can look at some of the winning solutions.

https://www.kaggle.com/competitions/shopee-product-matching

I looked at your post history. You are tring to sell your price monitoring tool but it seems like you dont have a working prototype based on this question?