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Building a data team at a mid-stage startup

erikbern.com

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Re: Building a data team at a mid-stage startup

#71

Post by somberi »

lifeisstillgood wrote: post #69
zippy5 wrote: post #63

Earlier quoted context omitted.

So my assumption is that for a given business model, like e-commerce or Saas business much of the highest value analysis is fairly standardized and can be templated. For example breaking down conversion rate by weekly cohort is something that can be pretty easily be done in google analytics. The problem with English to sql translators or most coders in general are the assumptions we make, in particular about the unde…

can you point me at some of the vendors - I am missing a chunk of knowledge i suspect. Or is this - for exmaple - people taking google analytics and producing analysis on top of that.?

+1. @Zippy - May I ask for some of the vendors you refer to, please?

Also love the Uranium analogy.

Re: Building a data team at a mid-stage startup

#72

Post by nwsm »

czep wrote: post #24

This is so eerily familiar I swear I've had many of these exact conversations word for word. The only way this doesn't turn into a complete nightmare of a cluster is if the exec team "gets it". If so, you just might stand a chance at building a data team that gels with the rest of the org. But if the exec team simply hired you for window-dressing, expect to be treated like a scapegoat and a punching bag. Any mistakes…

This was my only complaint about this great article. The CEO was innately "data-driven" which opened a lot of doors.

OTOH, if the execs don't have this priority, no one gets hired to lead and scale a data team and the story never starts.

Re: Building a data team at a mid-stage startup

#73

Post by AtNightWeCode »

I really enjoyed reading this. Very well written. At companies I worked teams can never read data from the DW btw.

My experience with A/B tests is that they are way overrated.

On the poor data quality. You sit on a product like a call center. Frontend developers thinks it is an excellent idea to store all data in some doc db blob. Then business wants stats about number of calls based on users...

Be careful when putting tabular data into doc dbs.

Re: Building a data team at a mid-stage startup

#74

Post by [deleted] »

neighbour wrote: post #47
jabagonuts wrote: post #46

Really enjoyed this narrative, but what about the next phase? Going from mid-stage to mature startup? > Note that you took on a lot of “tech debt” earlier when you started dumping the production database tables straight into the data warehouse. How do you manage expectations when the year-long honeymoon is over, the business grows tremendously, and the centralized data warehouse reaches a breaking point?

Also thought this. Let's hope the author has a SQL in the works as I am keen to hear more.

[deleted]

Re: Building a data team at a mid-stage startup

#75

Post by grvdrm »

lifeisstillgood wrote: post #69
zippy5 wrote: post #63

Earlier quoted context omitted.

So my assumption is that for a given business model, like e-commerce or Saas business much of the highest value analysis is fairly standardized and can be templated. For example breaking down conversion rate by weekly cohort is something that can be pretty easily be done in google analytics. The problem with English to sql translators or most coders in general are the assumptions we make, in particular about the unde…

can you point me at some of the vendors - I am missing a chunk of knowledge i suspect. Or is this - for exmaple - people taking google analytics and producing analysis on top of that.?

+2 on that! would love to know about what you think is worth investigating @zippy5

Re: Building a data team at a mid-stage startup

#76

Post by alexpetralia »

plank_time wrote: post #35

This is probably the singly best written and most realistic article I’ve read on HN ever and I’ve been on HN for a long long time. It’s so realistic I wonder if the author took it from his diary or something. Everything about it is supersaturated with authenticity and teaches better than any other article I’ve read. Kudos to the author, and I would love to see this style of article take off.

His post on Berkson's Paradox is excellent!

Re: Building a data team at a mid-stage startup

#77

Post by jiaweihli »

lifeisstillgood wrote: post #69
zippy5 wrote: post #63

Earlier quoted context omitted.

So my assumption is that for a given business model, like e-commerce or Saas business much of the highest value analysis is fairly standardized and can be templated. For example breaking down conversion rate by weekly cohort is something that can be pretty easily be done in google analytics. The problem with English to sql translators or most coders in general are the assumptions we make, in particular about the unde…

can you point me at some of the vendors - I am missing a chunk of knowledge i suspect. Or is this - for exmaple - people taking google analytics and producing analysis on top of that.?

Highly recommend Heap [1] - they have a neat approach that doesn’t require you to ‘decide’ which analytics you want to track ahead of time.

Disclaimer: I was an early engineer at Heap.

[1] https://heap.io/

Re: Building a data team at a mid-stage startup

#78

Post by Dyac »

jiaweihli wrote: post #77
lifeisstillgood wrote: post #69

Earlier quoted context omitted.

can you point me at some of the vendors - I am missing a chunk of knowledge i suspect. Or is this - for exmaple - people taking google analytics and producing analysis on top of that.?

Highly recommend Heap [1] - they have a neat approach that doesn’t require you to ‘decide’ which analytics you want to track ahead of time. Disclaimer: I was an early engineer at Heap. [1] https://heap.io/

Heap might be good but they are crazy expensive. We were quoted something like a quarter million dollars. Good luck getting that signed off, plus you still need quite technical analysts to run the thing.

I've found https://contentsquare.com/ to be much better received by juniors and seniors alike, and it's a fraction of the cost of heap.

Re: Building a data team at a mid-stage startup

#79

Post by lifeisstillgood »

Dyac wrote: post #78
jiaweihli wrote: post #77

Earlier quoted context omitted.

Highly recommend Heap [1] - they have a neat approach that doesn’t require you to ‘decide’ which analytics you want to track ahead of time. Disclaimer: I was an early engineer at Heap. [1] https://heap.io/

Heap might be good but they are crazy expensive. We were quoted something like a quarter million dollars. Good luck getting that signed off, plus you still need quite technical analysts to run the thing. I've found https://contentsquare.com/ to be much better received by juniors and seniors alike, and it's a fraction of the cost of heap.

Ah, so these do do web analytics on users - ok. That makes much more sense.

Re: Building a data team at a mid-stage startup

#80

Post by jiaweihli »

Dyac wrote: post #78
jiaweihli wrote: post #77

Earlier quoted context omitted.

Highly recommend Heap [1] - they have a neat approach that doesn’t require you to ‘decide’ which analytics you want to track ahead of time. Disclaimer: I was an early engineer at Heap. [1] https://heap.io/

Heap might be good but they are crazy expensive. We were quoted something like a quarter million dollars. Good luck getting that signed off, plus you still need quite technical analysts to run the thing. I've found https://contentsquare.com/ to be much better received by juniors and seniors alike, and it's a fraction of the cost of heap.

I don’t know the specifics of what you were quoted, but a quarter million dollars (guessing per year?) does strike me as high.

Were you a later-stage startup by chance? The price point for pre-Series-C startups should be much, much lower.

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