[ggiaco]

We're looking into ways to improve the ranking, so thanks for sharing that teej. We actually started with a normalized and more complex algo that was more along the lines of what you suggest, but the resulting feed had mostly random products and was not very helpful for more casual users. It also made it difficult to understand why a product was ranked. I think you're right that as it stands, we can do more to surface younger products. So far, we're doing it manually with "wildcards".

I mentioned in another comment that one of our bets is that since a user can only recommend a product once, over time the more obvious products should find it relatively more difficult to get new recommendations and newer products will surface.

e.g., if we did a filter of recommendations by YC companies (or more extreme - YC founders), then something like Slack would be popular the first month, but then have few remaining votes. Thoughts?

[teej]

You need to separate the concept of popular and trending. Make two lists. Have a popular list at a couple fixed time grains - all time, last year, last 30 days (what you have now). Then for your trending list use a z-score like described in this stack overflow post [0] to normalize. I honestly wouldn't invest a ton of time trying to do something fancier then that. You're trying to rank with one signal, you can't expect computers to perform magic.

I'd also consider a third list - highlighted. Have your team internally pick something new and interesting once a month. Finding novel and interesting things is something humans are really good at.

[0] - http://stackoverflow.com/questions/787496/what-is-the-best-w...

[ggiaco]

Thanks. Great link. It does seem that having multiple feeds is emerging as a consensus suggestion.