Shops used to curate their catalogs by in-house testing products from various suppliers. If a supplier comes up with a better toaster, they can send samples to the most relevant shops and convince them to stock it.

> Then, one day a new toaster comes out, and it might be even better than the old best-seller. How would it get sufficient traction to be recommended by the algorithm?

This is a solved problem. Recommendation algorithms aren't just "highest average rating", they take into account number of ratings, recent trends, etc.

Even if some ads improve this experience, Amazon is orders of magnitude past that threshold into hostility and toxicity. You have to scroll through pages of sponsored results to find anything worthwhile.

Same way youtube gets people to view new videos. By showing a few people the video and if they like it then show it to more people. Obviously for something as expensive as a product launch you'd weight it a bit more towards the new product than a youtube video but still.