Avian

Almost every company collects data. There are also a billion "data" tools out there. Being a data platform is too broad. Kyle is the technical founder and started working on the technical challenges. My challenge was to talk to as many people as possible and narrow down on an area where our learnings are consistent.

We decided to go after the largest source of marketing data, which is Google Analytics, so I reached out to people working in the SEO space. (If you're reading this and you love SEO, work with website/search engine data, send me a message so we can chat!) And learned that reports are often created manually. So we built the easiest interface ever to easily extract this data from Google Analytics and build these reports with less overhead.

We are in August beta testing with users within this segment, we are learning a lot from how they interact with our product, bugs and missing features etc.

Kyle and I did not work together before we founded Avian. We did get along well from the first conversation, but that doesn't mean we can work together.

So we decided to time-box one problem and learn how we work together: to design the logo and landing page in one afternoon. We got some lunch and then booked a meeting room, at the end of the afternoon we had a logo we were proud of, and a really good design for the landing page. We then ended up designing a few more pages and the onboarding flow. Which was crazy productive for one afternoon!

We then realised we could work together productively. Our next challenge was to make sure we had similar goals and ambitions. We ended up aligning pretty much 100% on what the goals should be in the first year, after 3-ish years and where a company should go long term.

Based on these two things we believed we should working together a try. And that's how Avian became real.

Kyle and I met for a coffee and chatted about our goals. Kyle is a successful founder with 2 exits under his belt. I did not have that level of success but as a consulting designer, I managed to solve hard business problems without reaping the benefits many times.

At the end of our conversation, we decided to work on something difficult that could be big: work on a startup that manages and moves data from different sources into one managed source.

I was personally motivated by this space as someone close to me was forced to close their business and went bankrupt because this person had no real insight into the financial and marketing data. I really want to solve big hairy problems like this.

There are 'easier' spaces but one cool thing about being in the data space is that you don't have to rely on hype, fame or popularity. We just need to build the right solution for the right audience and go from there.