Before I cared about data or had much experience in marketing, I would be biased toward trying something new. I liked learning and always had the generalist’s confidence that I could figure something out so when selling work, instead of opting for what I was familiar with, whether SEO or funnels or a podcast or whatever, I would recommend a client to do whatever seemed like the best fit, with a little slant toward novelty for my scope.
At a certain point, that clearly wasn’t working for me, I had very little leverage and when we’d have a really successful outcome, it would feel like luck. And so learning analytics started as one of those “seems like a good novel fit” thing to do for clients and then it started feeling important to decision making.
Quickly though, analytics audits, tune ups, custom reports, goals/events tracking became things I resented doing, not because I didn’t like them, but because whether or not clients wanted to pay for it, I thought I needed it to orient projects, evaluate what was working, and improve outcomes.
Even writing about it now, I get a little amped up. I don’t know why.
Choosing what to track, what events to fire, what reports to build forces you to decide what is important. Like asturdy decision-making process being the first step in ensuring success.
Choosing what to do by paying attention to metrics you decide matter means that at the very least you have a shot of uncovering the bias in how you decide things. Bias toward instinct in a way that ignores data, toward traffic in a way that ignores conversions, towards doing what you feel like instead of what is uncomfortable.
We are so very bad at making decisions that solve these sorts of problems on our own. Even once you get to a point where you are tracking the right things, you will inevitably look at reports or session recordings or sales by channel and then think, “Okay. I see these numbers. What do they mean?” And then proceed to get your bias all over it.
You want to focus your energy on organic social because it is familiar, you see social doing poorly in your dashboard, and so you think “we have to try harder.” Instead of, “look at this organic search traffic doing so well over here. We weren’t even trying. I bet we could really improve this.”
If you prefer the adrenaline of a big sale, enjoy relationship-building, and are one of those weird people with a lot of confidence, you will prefer whale hunting and end up with whale client feasts and idle periods of famine.
Being a purely whale hunter means you get comfortable in bad power dynamics, are subject to volatility, and now everything you do is custom so you can be lazy about pattern recognition and systems building.
The opposite is also true. If you shy away from outbound sales, you are left trying to attract clients by creating gravity around your content and gravitas around your authority.
The returns on running a content factory are also markedly low for most of us, at least the first few years.
Neither preference is optimal. Either alone precludes diversification, multi-channel cooperation, exercising the muscle of trying new uncomfortable things.
When bias is running the show, you are on autopilot, acting predictably. Predictable action means our outcomes will also be predictable. This is what network science as a field is actually built upon. We know that nodes in a network are relatively stable, it is their relationships that then dictate their outcomes.
Driving decisions with data doesn’t mean picking the right answer, it just means giving yourself a fighting chance at reducing bias in a decision making process because it is our biases that get us into the most trouble. It also lets us look at the data in a multi-stakeholder situation and have a conversation about what it means instead of vying for personally biased interests.