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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

#21

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).

Thank you! There's definitely a lot of growth and potential in this space and we're really excited too. We're focused on intelligent monitoring and alerting for metrics that the user cares about & defines. We also automate the diagnostic playbooks that teams use today after detecting an issue (eg check data, check user segments, check geographies, etc.) Outlier seems to focus on insights and less on monitoring/alerting. They comb through data to surface 4-5 "unexpected insights" about your customers or business every day in a FB feed-type product.

Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers

#22
This 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 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

#24
post #22

This 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

#25
post #22

This 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.

Was this ML attribution model output explainable / deterministic? I've seen some really complicated marketing attribution models in the past and hear it was something of a never-ending battle to understand and arrive at the "right" model.

Re: Launch HN: Orbiter (YC W20) – Autonomous data monitoring for non-engineers

#26
post #22

This 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…

Thanks! We'll rolling out slowly (kinda Superhuman onboarding style back in their old days) so definitely hope to get in touch with you soon :)

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

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