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So, I really like this idea, and I've been with plenty of coffee subscriptions over the last few years. My issue/worry is that I don't make coffee at home on a

So, I really like this idea, and I've been with plenty of coffee subscriptions over the last few years. My issue/worry is that I don't make coffee at home on a daily rate. I have coffee at the office most weekdays, and then at home on the weekend, and then usually also on one day I work from home. For me, it would be really nice for your service to work out something like "You make 60g of coffee on Saturdays and Sundays, and then 30g's on Wednesday" and then work out when I'll be running out, and maybe order me a new bag to come in on Friday because it knows I'll likely run out on Saturday. This doesn't seem super hard to do, but does seem like something that's important to work out, since there's a lot of products that people don't use on with regular daily amount.

seizethecheese 8y ago
Interesting use case. This actually mirrors a lot of our customers, so it's important for our system to take this consumption pattern into account. After a few orders, the system will learn that you make 120g on weekends with sporadic weekday consumption.
- noirbot 8y ago
  That's really nice! One thought - it might be helpful to have some way to seed the system with what you at least think is "normal" consumption? The one other thing that springs to mind is having some way to mark vacations or other disruptions to schedule? Also potentially a way to mark that you refilled some other way? Often when I'm on a trip, I'll bring home some coffee from a local roaster, so having a way to feed that into the system would be nice.
  - seizethecheese 8y ago
    Interesting concept for seeding the system. We used to have something like that and dropped it because it wasn't too accurate. We do have a setting for turning off automatic re-ordering to handle vacations or unexpected bounties of coffee.
    - smurfysmurf 8y ago
      I like this idea, and good luck! Just wanted to give some input on this as I currently work on an ML project at Amazon. The more context possible from the user to define the space at the very beginning will increase accuracy exponentially (at the risk of a too much effort required for user onboarding). Finding that balance is important. Additionally, the user feedback is very important as well. incorporating a way to say yes a shipment came at the wrong time, or no it didn't will also improve model development. However both experiences should be lightweight and seamless - good luck!
      - seizethecheese 8y ago
        Thanks for the advice! I agree there's a tradeoff between asking the user too much and expecting the system to learn on it's own.
psalminen 8y ago
I am in the same boat. This kind of irregular is what has stopped me from automatically re-ordering a la Amazon subscriptions. It would be amazing if this was solved.
- seizethecheese 8y ago
  Glad to hear it. This is the problem we're addressing. E-commerce subscriptions don't actually work.

seizethecheese 8y ago

Interesting use case. This actually mirrors a lot of our customers, so it's important for our system to take this consumption pattern into account. After a few orders, the system will learn that you make 120g on weekends with sporadic weekday consumption.

noirbot 8y ago
That's really nice! One thought - it might be helpful to have some way to seed the system with what you at least think is "normal" consumption? The one other thing that springs to mind is having some way to mark vacations or other disruptions to schedule? Also potentially a way to mark that you refilled some other way? Often when I'm on a trip, I'll bring home some coffee from a local roaster, so having a way to feed that into the system would be nice.
- seizethecheese 8y ago
  Interesting concept for seeding the system. We used to have something like that and dropped it because it wasn't too accurate. We do have a setting for turning off automatic re-ordering to handle vacations or unexpected bounties of coffee.
  - smurfysmurf 8y ago
    I like this idea, and good luck! Just wanted to give some input on this as I currently work on an ML project at Amazon. The more context possible from the user to define the space at the very beginning will increase accuracy exponentially (at the risk of a too much effort required for user onboarding). Finding that balance is important. Additionally, the user feedback is very important as well. incorporating a way to say yes a shipment came at the wrong time, or no it didn't will also improve model development. However both experiences should be lightweight and seamless - good luck!
    - seizethecheese 8y ago
      Thanks for the advice! I agree there's a tradeoff between asking the user too much and expecting the system to learn on it's own.

psalminen 8y ago

I am in the same boat. This kind of irregular is what has stopped me from automatically re-ordering a la Amazon subscriptions. It would be amazing if this was solved.

seizethecheese 8y ago
Glad to hear it. This is the problem we're addressing. E-commerce subscriptions don't actually work.