Comment by pyduan | Hacker News Reader

Comment by pyduan | Hacker News Reader

This is great. For a weekend project this looks and feels very polished.

Possible suggestions: it looks like it is 'just' retrieving one's list of subscribed subreddits then displaying manually curated lists for each category, which means every user who is subscribed to a subreddit will be shown the same products in this category.

I don't know if you are planning on continuing work on this project, but if you are adding more items implementing an actual recommender system could do wonders (for example, by looking at what users with similar subscriptions have favorited). I feel the Reddit-browsing demographic is one that would be very receptive to this type of thing since some subreddits are all about about social-based discovery.

I'm willing to guess one can learn a surprising lot about one's preferences by looking at their Reddit subscriptions. For example, you may be able to guess the clothing style of someone who is subscribed to r/malefashionadvice, r/newyork, and r/finance, or that someone who reads both r/audiophile and r/metal might like different headphones than someone who participates a lot in r/classicalmusic.

Thanks for the great feedback!

An actual recommendation engine would be a lot of fun to build. It would be awesome to recommend products based on subreddit clusters, and similarities between users.

But I don't really want to build a giant AI that sifts through the entire Amazon catalog. I feel that it's a nicer user experience when you just offer a small selection of manually curated products, and some studies show that limiting the number of choices can make people more likely to buy something [1]. I used to list a few CDs and MP3 downloads, but deleted those after I decided that there are already much better music recommendation engines, and they're subscription based. My line of thinking is that I should just start doing a few categories really well, and then expand later.

[1]: http://blog.ted.com/2012/07/18/does-having-choice-make-us-ha...

You're arguing apples and oranges here. Yes, offering a smaller selection can increase conversion but that has nothing to do with how the curation process works on the backend to present the selection. Whether you do it by your method or by going full on AI, you can still present a limited selection. The only difference is how algorithmic the recommendations can be on an individual level

That's a good point. I guess my adverse reaction to building a proper recommendation engine is because I've never experienced one that works really well. I've never seen a decent product suggestion from Amazon and Google. But maybe the problem is that their suggestions are based on my search history, instead of my specific interests.

Can you build a useful algorithm without data? That sounds awesome, I just have no idea how one would create something like that (except by starting with something like this)

Reply on news.ycombinator.com