We’re very excited to announce our $11M Series A! The fundraising round was led by NEA and includes Menlo Ventures, SVAngel, Initialized Capital, and Pear Ventures.
Analytics software is uniquely leveraged. Most software can optimize existing processes, but analytics (done right) should generate insights that bring to life whole new initiatives. It should change what you do, not just how you do it.
But then why does traditional analytics look more like janitorial work than data science? Let’s say you need to decide whether it’s worth investing more engineers into your app’s new “Invite a Friend” feature. You might ask yourself “does inviting a friend lead to longer-term retention?”
To get the answer, you’ll often have to:
- Bother some engineer and spec out a tracking implementation.
- Wait for the engineer to get around to instrumenting your app with logging code.
- Wait for the updated code to get approved by Apple and pushed live.
- Wait a few weeks for data to trickle in.
- Bother the data team to run the analysis for you and produce results.
That’s a lot of bottlenecks and wasted time. For many, this process hasn’t changed since the first analytics tools came to market. In fact, today’s most prevalent analytics tools still originate from products designed in 1996! Given the massive technological shifts of the past two decades—the rise of mobile, on-demand compute, ~8000x cheaper storage, large-scale AI—this seems very wrong.
In 2013, we built Heap from the ground up with a different approach in mind: automatically capture all the data. This saves our customers the headache of defining events upfront, maintaining brittle tracking code, and waiting for data to accumulate. Today, in 2016, we’re happy to serve as core analytics infrastructure for thousands of growing businesses across many industries.
But we’re still in the early days of analytics. There’s still much more friction we can remove. As we build out Heap further, we’ll aim
Our goal is to automate as much of this infrastructure as possible. Companies shouldn’t have to reinvent the wheel with messy data science/engineering work. They should be directly getting the insights they need to grow their business.
Though we’ve got a lot of work ahead of us, we’re excited to use this new round of funding to tackle even bigger problems for you and our customers!
If you’re interested in solving this problem with us, let us know. We’re hiring!