This content originally appeared on Jonnie Hallman (@destroytoday) and was authored by Jonnie Hallman (@destroytoday)
In the previous post, I mentioned user testing and how valuable it’s been to learn from Cushion’s users in their words. I feel like I’ve gotten pretty far on occasional user testing alone, and it helps that my wife and I run a studio space full of freelancers, but if the year leading up to my burnout taught me anything, it’s that I don’t truly know what hooks people or what causes them to leave. On top of that, I don’t have any way of measuring this or tracking it over time. As much as I’d love to blindly continue ~doing what I love~ and hope folks continue to use an app mostly built on my assumptions, I really need to learn more about how people use Cushion, which means adding analytics.
It probably shocks a lot of folks to know that I don’t have any analytics set up for Cushion—not even Google Analytics on the marketing site or anything. Back when the GDPR deadline was approaching, we stopped and realized that we didn’t even use our analytics. Like many others, we inserted the snippet, started collecting the firehose of data, and didn’t do much with it. Despite being really into stats and numbers, I’m actually not really into analytics. I’d much rather spend my time designing and building, but that’s naive because at the end of the day you need to know what to build and how it should be designed.
Instead of taking the firehose approach again, I’m going to be overly intentional this time around. Earlier this week, I added a new “client industries” feature to Cushion, which lets people specify the industry that their clients are in. This came out of my conversation with Jen because she wants to know which types of clients she should continue pursuing. If Cushion can instantly reveal that the clients who take the longest to pay her are also the ones who pay her the least, she can make an easy decision and focus on clients that she doesn’t need to chase down. I’m really interested in whether this feature will actually catch on, so once I set up analytics, I’ll add a single metric for whether folks discover the feature and if they use it. That’s all I’ll add for now before moving onto the next feature I want to measure.
Once I start thinking about measuring meaningful actions versus everything all at once, analytics become really interesting to me. I have so many assumptions about where Cushion should go, but none of them are based on anything—simply intuition. This is totally fine if I were starting right now with a simple idea and no users, but Cushion is far enough along that assumptions will actually lead me astray if I’m not careful—the past few years are a prime example of this. While it feels uncomfortable now, I think this is one of those times where I need to “eat the broccoli”. The best case scenario is that I discover a crystal clear path for Cushion to go from here. The worst case scenario is that I realize my assumptions are all wrong and Cushion can only succeed in a direction I don’t want to take it. I’m excited, but I’m also terrified.
This content originally appeared on Jonnie Hallman (@destroytoday) and was authored by Jonnie Hallman (@destroytoday)
Jonnie Hallman (@destroytoday) | Sciencx (2020-07-29T08:33:00+00:00) Intentional analytics. Retrieved from https://www.scien.cx/2020/07/29/intentional-analytics-2/
Please log in to upload a file.
There are no updates yet.
Click the Upload button above to add an update.