Congrats on the launch. This is a really interesting space that I think has a ton of potential - I'm watching pretty closely to see what comes out of it. Have you heard of Outlier ( https://outlier.ai )? Do you have any thoughts? How does Orbiter compare to Outlier? (I haven't used Outlier but see it come up in anomaly detection discussion a lot recently).
Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
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Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#22Also, on metric drops I'm interested not just in the alerts but also in the narrowing down of what is causing the drop. For example, the first question we always ask is "could marketing blend be causing this". I imagine your ML can figure that out. You could also point out where to look, like "iOS 13 is fine, but there is a severe drop in conversion for iOS 12" or "Conversion dropped for app version 13.2 on Android".
Great stuff! I'd love to see if it works!
Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#23Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#24This is interesting. If you can deliver on this, I'm guessing you can deliver on a lot more. Figuring out what warrants an alert is a non-trivial problem, and it's in the same problem space as answering other business questions like "what is our true organic traffic". Also, on metric drops I'm interested not just in the alerts but also in the narrowing down of what is causing the drop. For example, the first question…
Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#25This is interesting. If you can deliver on this, I'm guessing you can deliver on a lot more. Figuring out what warrants an alert is a non-trivial problem, and it's in the same problem space as answering other business questions like "what is our true organic traffic". Also, on metric drops I'm interested not just in the alerts but also in the narrowing down of what is causing the drop. For example, the first question…
Funny, Actually I know a startup in Edinburgh that has figured out the “true organic traffic” and they’ve used ML to fix the data for marketing attribution model.
Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#26This is interesting. If you can deliver on this, I'm guessing you can deliver on a lot more. Figuring out what warrants an alert is a non-trivial problem, and it's in the same problem space as answering other business questions like "what is our true organic traffic". Also, on metric drops I'm interested not just in the alerts but also in the narrowing down of what is causing the drop. For example, the first question…
Also re: narrowing down what's causing the drop, that's definitely on the roadmap. We know teams have playbooks of things to check when they know something looks wrong, so we should be able to productize & automate this
Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#27Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers
#28This is what Maxly.coM used to do. They learned several valuable lessons and would be worth talking to one of the founders.