I think the real power of Keen is the ability to gather analytics for your clients. If you're a platform (think Shopify), your customers probably want some sort of dashboard and reporting on their customers.

Keen makes this too easy with their embeddable JS visualizations: https://keen.io/docs/data-visualization/ and scoped keys for security: https://keen.io/docs/security/#scoped-key

Also checkout this comparison of Mixpanel & Keen: https://keen.io/blog/67519816958/mixpanel-vs-keen-io-whats-t...

[Disclosure - I work at Keen IO]

You're right that this is definitely one of our dominant use cases.

It's taken us by surprise to see just how much traction we've among B2B SaaS companies who just wanted to give reports their customers.

Glad the scoped keys are working out for you! If you could add one feature to our product, what would it be?

Advise on the mover.io landing page:

I scrolled down the entire page and still had no idea what mover.io is. You start with a tag line "The smarter way to move files"... I'm not sure what "move files" means exactly.

The next section is Why. I skimmed past this section because I want to know What before Why.

Then the next section is Testimonials. For what!

Then next is Services. Finally! The What! Although this needs to be laid out more cleanly, I shouldn't have to read about every product you offer before knowing what the "essence" of mover.io is.

Great advice, thank you. We'll definitely work on improving it.

I recently tried Keen.io for a project I'm working on, and it didn't work out - the metrics I was looking for were too complex (eg. the average lag between signup and the third time a user does a particular action) to do natively, and the suggestions for how to get that working in Keen (doing some calculations on the event data before sending out) I wasn't interested in.

Having said that, the guys at Keen were great to work with as I was sorting this out. The email I sent to their generic "contact us" address with some data modelling questions was answered promptly by one of the founders with solutions which, while I didn't like them, were interesting and would have worked out. They were also generous in letting me crash through the initial free quota while I was figuring out if the thing worked out for my use.

So while I didn't sign up as a paying customer with them (and I've stopped sending them events), it was among the most pleasant interactions I've had with a prospective analytics vendor in a long while - well done guys!

I'm glad you had a pleasant experience -- it's too bad it didn't work out.

You may be interested in an upcoming feature we currently have in private beta, which does this:

    your events  ---->  Keen IO  ---->  your S3 bucket on AWS

We have a great, standard format for representing the events in files in S3. If you were using that feature, you could just write an Elastic MapReduce job to perform these sorts of custom calculations (we'll be open-sourcing a bunch of these sorts of scripts). Another option would be to pay one of our partners to write this analysis code for you.

I wonder: would that feature be interesting to you? Would it have perhaps allowed us to win your business?

I'm not sure it would have (without trying it), but it certainly would have kept you in the game for a bit longer since I'm a-OK with EMR jobs for my analysis (or presumably being able to download those files and load them into my own Hadoop cluster).

I was hoping for a bit more insightful answer to the question "why choose Keen in particular".

Because I also chose Keen.io, but the primary reason was that I couldn't find any competing product that would allow us to provide customized analytics to clients of our SaaS platform.

Keen is nice though, but I'm surprised that I couldn't find much competition.

I suppose the answer to that question is that it enabled us to very quickly send our transfer logs into a system that a non-technical person could easily play with. Being somewhat technical helps as well because I can easily create little dashboards (and blog posts!) with great visualizations without having to dive into some nasty graphing code.

There ARE alternatives out there, but they're crazy expensive and usually designed to analyze things like Hadoop data.

Ok that second chart is kinda a mess due to too much data, and an only partially visible legend.

But it raises a question for me on the draw order used. Is that the default draw order? As while I could be wrong it appears to be alphabetical same as the legend order. If this is the default it seems like a poor default.

Now not considering that most people will want attention drawn based on the data itself some how. It seems that if you are going to do the legend in alphabetical order the draw order for the lines should be reverse alphabetical order to ensure that the lines which are most visible (drawn on top) are also most likely to be in the top part of the legend.

I just am curious if this is a poor default or just a quickly made example chart. Or maybe it is a great default and I am missing something.

This reminds me of parsing log files, pumping them into elasticsearch and analyzing them with kibana [0]

[0] http://www.elasticsearch.org/overview/kibana/

Keen has actually has customers do something like this to add context to log files and make searching them more flexible.