Analytics is something that’s easy to put off. When you’re actively building a company and trying to figure out your value proposition, collecting and splicing data can seem non-critical or premature. But then, all of a sudden, you hit a point where things get complex, you need to understand your customers much better, and you have lots of unusable data because you captured it the wrong way — or didn’t capture it at all.
As soon as your company has users, you need to set up a solid analytics framework. It’s not a waste of time or money.
“Many companies send data off to a service to store it, but once it’s stored, it’s no longer accessible in the same form; it would require engineering to get it back,” according to Ben Porterfield, a Co-founder and VP Engineering at Looker. “Too much of this is event data — metrics showing what happened with your site or product. This is super valuable stuff. When you combine event data with your operational transactions in a database, you learn which events triggered conversions.
The value of combining your operational data with your event data is that you get to understand your user’s journey through your product or service — there are few things more important.”
Your impulse might be to save your resources and have your existing engineers cobble together an in-house solution that will do the job, tracking and storing only a sparse set of the most essential metrics. Porterfield has seen a number of companies cave to this temptation and it doesn’t end well.
It’s well worth the time and money to find proven resources that have stability and support from the outset. Every time data is hard to access or understand, your business is falling further behind because people are making slower decisions.
If you would like a friendly and neutral needs analysis of where you can maximize your planning analytics and big data management ROI, just shout out and we can be your listening post.