1. Empirically, we've found that our customers rarely fall back on custom attributes. The vast majority of queries run in Heap (>75%) operate on automatically-captured events. To me, this suggests we've either: 1) cut out a significant portion of implementation work, or 2) enabled analysis that was previously blocked by implementation work. If either (or both) are true, it's a win, and suggests that automatic event-tracking produces salient data out-of-the-box.
2. That said, some metrics are important and do require manual instrumentation. Coincidentally enough, we're about to launch a feature that solves the problem you mention and requires no extra implementation work. We're excited about it. Want to try it out on newrelic.com?
We get this question so frequently that we've created a page dedicated to answering it: https://heapanalytics.com/docs/other-tools. It describes how Heap compares to Google Analytics, Flurry, Mixpanel, and KISSMetrics.
At the core, Heap's main differentiator is that it automatically capture everything, such as clicks, taps, form submissions, and pageviews. This lets you analyze data retroactively, without writing any code. Every other analytics tool requires you to define events of interest upfront.
Feel free to ping me directly at matin@heapanalytics.com if you have more questions! Happy to go into more depth.
Let me say that this kind of personal-attention is not unlike the experience you'll have using the product. And THAT is the main difference. Heap really makes you feel like you're the most important user in the world.
I use it in conjunction with GA for most projects. GA mostly for the track-record (in case a potential buyer or investor asks for GA access during their due-diligence process). But Heap is where I go when I really need to understand what my users are doing. It's really nice to be able to look at one user at a time and see "okay this guy clicked this exact button, and then went over here and clicked this one 10 seconds later". That kind of deep analytics comes out of the box, which is nice.
Heap is taking a new approach to web and iOS analytics: just capture everything. Whereas other analytics tools require you to define events upfront, Heap lets you run instant, retroactive analytics without writing code.
=== The Role ===
Your creativity and intelligence are much more important to us than your experience with our stack. We're eager to meet all types of engineers, regardless of where you live or what tools you use day-to-day.
We’d like to get to know you if:
* You enjoy teaching yourself whatever is necessary to build something.
* You plow through obstacles.
* You’ve written 10,000 lines of code that look really embarrassing in retrospect.
* You’ve written 10,000 lines of good code since then.
* You communicate ideas with clarity and precision.
* You make decisions with a preference for empiricism and measurement.
* You like fruit, sunshine, and bad jokes.
Our stack is Node + Redis + Postgres + Backbone + D3. Some things we're working on:
* Data capture. We’re integrating with more clients and frameworks, including Android, AngularJS, and Backbone.js, all with virtually no performance overhead or integration cost.
* Real-time infrastructure. We support an expressive set of queries that allow our users to slice and dice the data in arbitrary ways. The results need to come back with sub-second latencies and reflect up-to-the-minute data.
* Data visualization. Simple pre-generated graphs just don't cut it. There's an enormous number of ways to organize the data. Existing tools only scratch the surface.
Heap was in Y Combinator’s W13 batch. Soon after, we raised a $2M seed round from Ron Conway, Ram Shriram, Sam Altman, Garry Tan, Alexis Ohanian, Harj Taggar, and others.
We work in SF but are absolutely open to remote engineers. Email us at jobs@heapanalytics.com with reasons as to why you'd make a great fit.
Heap is taking a new approach to web and iOS analytics: just capture everything. Whereas other analytics tools require you to define events upfront, Heap lets you run instant, retroactive analytics without writing code.
=== The Role ===
Your creativity and intelligence are much more important to us than your experience with our stack. We're eager to meet all types of engineers, regardless of where you live or what tools you use day-to-day.
We’d like to get to know you if:
* You enjoy teaching yourself whatever is necessary to build something.
* You plow through obstacles.
* You’ve written 10,000 lines of code that look really embarrassing in retrospect.
* You’ve written 10,000 lines of good code since then.
* You communicate ideas with clarity and precision.
* You make decisions with a preference for empiricism and measurement.
* You like fruit, sunshine, and bad jokes.
Our stack is Node + Redis + Postgres + Backbone + D3. Some things we're working on:
* Data capture. We’re integrating with more clients and frameworks, including Android, AngularJS, and Backbone.js, all with virtually no performance overhead or integration cost.
* Real-time infrastructure. We support an expressive set of queries that allow our users to slice and dice the data in arbitrary ways. The results need to come back with sub-second latencies and reflect up-to-the-minute data.
* Data visualization. Simple pre-generated graphs just don't cut it. There's an enormous number of ways to organize the data. Existing tools only scratch the surface.
Heap was in Y Combinator’s W13 batch. Soon after, we raised a $2M seed round from Ron Conway, Ram Shriram, Sam Altman, Garry Tan, Alexis Ohanian, Harj Taggar, and others.
We work in SF but are absolutely open to remote engineers. Email us at jobs@heapanalytics.com with reasons as to why you'd make a great fit.
I like this approach. Is closer to what web developers are used to: We included analytics on every page, we don't need to create reports until we find a problem or something to optimize... and we still can do forensics.
2 side notes:
– Asked who did this in our app, he told me it was really easy to add mixpanel on "every event". But anyway, he would prefer that it was automatic... and not having to do it again on every view we include.
– As said on my previous comment, for this you need it to be cheap. If not, im creating a problem instead of a solution. At this scenario, mixpanel' people looks less exprensive than heap' sessions.
A question:
Does a "pay for the metrics you use" model makes sense?
Collect everything, what you pay is some sort of multiplier of (metrics used in reports or segments per user). It would be great, at least for this scenario.
I read in the first comment (from mixpanel founder) that the hard part is not collecting data but making them work as formulas.
That makes you able to not storing the data that has not been included on any report or segment for more than a month or something like that if you want to reduce costs.
(Disclaimer: I'm a founder at Heap. We build mobile analytics, so I'm far from impartial.)
Amazon's main purpose in building an analytics tool is to drive spend to the Amazon App Store. If you can't measure the ROI of their app store, you can't devote more resources to it.
This applies to just about all the big tech companies and their respective distribution platforms: Google with AdWords, Facebook with mobile ads, and Apple with the iOS app store. Lots of dollars flow through these platforms, and Amazon/Facebook/Apple don't want their developers measuring those dollars with a hostile competitor's analytics offering. (Often, the hostile competitor they have in mind is Google.)
You'll notice this in the screenshots for Amazon's mobile analytics. On the Overview page, note the breakdown of "Lifetime Value Per User". There are separate figures for iOS users, Android users, and...Fire OS users. A line item for "Fire iOS users" would never be so prominent in Google or Apple's analytics (or even present).
Thus, Amazon et al. focus on making their own analytics tools good at measuring acquisition (prioritizing their own channels) and some high-level metrics. Digging into the data is much less of a priority. Even basic questions - "what's the conversion rate for my signup flow?", "what are the email addresses of my active users?", "what percent of my revenue comes from repeat visits?" - require you to use a different tool.
Bigger companies are aware of this feature gap and happy to pay the price premium. But startups are (appropriately) more price-sensitive, even though a solid investment in growth/analytics is arguably more important for startups.
I'd love to hear HN's feedback on how Heap (and other analytics companies) can structure their pricing to better accommodate small companies.
Heap is taking a new approach to web and iOS analytics: just capture everything. Whereas other analytics tools require you to define events upfront, Heap lets you run instant, retroactive analytics without writing code.
=== The Role ===
Your creativity and intelligence are much more important to us than your experience with our stack. We're eager to meet all types of engineers, regardless of where you live or what tools you use day-to-day.
We’d like to get to know you if:
* You enjoy teaching yourself whatever is necessary to build something.
* You plow through obstacles.
* You’ve written 10,000 lines of code that look really embarrassing in retrospect.
* You’ve written 10,000 lines of good code since then.
* You communicate ideas with clarity and precision.
* You make decisions with a preference for empiricism and measurement.
* You like fruit, sunshine, and bad jokes.
Our stack is Node + Redis + Postgres + Backbone + D3. Some things we're working on:
* Data capture. We’re integrating with more clients and frameworks, including Android, AngularJS, and Backbone.js, all with virtually no performance overhead or integration cost.
* Real-time infrastructure. We support an expressive set of queries that allow our users to slice and dice the data in arbitrary ways. The results need to come back with sub-second latencies and reflect up-to-the-minute data.
* Data visualization. Simple pre-generated graphs just don't cut it. There's an enormous number of ways to organize the data. Existing tools only scratch the surface.
Heap was in Y Combinator’s W13 batch. Soon after, we raised a $2M seed round from Ron Conway, Ram Shriram, Sam Altman, Garry Tan, Alexis Ohanian, Harj Taggar, and others.
We work in SF but are absolutely open to remote engineers. Email us at jobs@heapanalytics.com with reasons as to why you'd make a great fit.
Heap's list view was built for this exact use case: https://heapanalytics.com/features/users. We use it all the time for developing a better intuition for our product.
Which is fine if you're adding automatic event-tracking directly to your own app. But for a third-party library (like our own), it exacerbates the integration process. Method swizzling allows for a purely drop-in solution.
Consider that you spent over 400 words describing what swizzling is, and you likely lost a lot of audience in those vast plains of text.
For example, you lost me. Having stumbled on it, I couldn't bring myself to finish the piece. I actually do need an analytics solution for our iOS app, but this blog post just fell into "I will read it later" category, out of "I will read it now".
This is an excellent point. Two things:
1. Empirically, we've found that our customers rarely fall back on custom attributes. The vast majority of queries run in Heap (>75%) operate on automatically-captured events. To me, this suggests we've either: 1) cut out a significant portion of implementation work, or 2) enabled analysis that was previously blocked by implementation work. If either (or both) are true, it's a win, and suggests that automatic event-tracking produces salient data out-of-the-box.
2. That said, some metrics are important and do require manual instrumentation. Coincidentally enough, we're about to launch a feature that solves the problem you mention and requires no extra implementation work. We're excited about it. Want to try it out on newrelic.com?