So I just looked at the quick start demo code. Did everyone notice the irony in it? We created some fake people and some fake orders and randomly let the people see the fake orders. Then we try to predict based on this data. A bit silly isn't it?
Best fake recommendations ever! But yeah we make the assumption the developer and their app (food delivery or otherwise) has some data (users, items, actions) on which to build a model. Otherwise you won't get very far...
I wish Seamless would innovate more. Recommended restaurants or meals would be awesome. Seamless has a total lock on the NYC market, but their website sucks, their ratings are highly unreliable (due to restaurants faking ratings), and they rarely add new features.
This is actually a pretty good idea. Seamless does have a program that allows selected affiliates to get data dumps from them, you could probably build it based on that.
On second thought, I think you can already do that on their website, just not in their iOS app yet.
What I meant to wish for is discrete ordering. I want one sushi roll from place A, a dessert from place B, and chicken from place C (all collected and delivered by one person). That's more of a job for the exploitative labour task5rrrrrrrrr category though.
Not so familiar with Keen IO. Looks like analytics-as-a-service for collecting and visualizing data. We're focused on helping developers build predictive features like recommendation, discovery, etc.
But anyway, the whole thing seems pretty cool.