June 26, 2014
PagerDuty’s Favorite Dev Ops Blogs
PagerDuty’s Ops Engineering team lead Arup Chakrabarti knows how to scale complex architectures. During his time at PagerDuty, the company...
On December 14th, 2016 Heavybit member CircleCI held their monthly Office Hours meetup at our San Francisco Clubhouse. The evening’s presentation was given by Justin Cowperthwaite, a developer at CircleCI, on the journey his team took to implement reliable event analytics across their apps and services. This post includes a video of his talk, and an excerpt from his blog post on the same subject.
When I joined CircleCI as a Growth Engineer, I came on board with one mission: improve conversion rates. Having freshly transitioned from an ecommerce startup, I had spent the past six months designing and iterating on funnels which turned user acquisitions into conversions. During that time I had learned a pretty basic formula for improving conversion rates:
So when I joined CircleCI Rishi (our Growth Project Manager) and I went to work. First we enumerated our key funnels: non-user to user, user to paying customer, and then paying customer to higher paying customer. We used the knowledge and data we had at our disposal to identify what funnels we had and which were underperforming. And last, we launched test after test to try and improve acquisitions, conversions, and upgrades.
But as we started to try and measure the success of these tests, we kept running into the same problems. We either couldn’t trust the data, or we were missing the data we needed to tie the test to the larger picture: the health of the business. After careful consideration, we decided it was time to declare bankruptcy on a broken analytics implementation and build a new one from the ground up…
Read the rest of Justin’s post on the CircleCI blog.
If you’re interested in learning more about event analytics and using that information to build personalized experiences for your users, watch this video of Segment’s VP of Growth, Guillaume Cabane, on building 1:1 personalization at scale.