These Results Not Typical

So this is a super fun topic, right? Well, okay, let’s reframe that, if you want to keep your job, you’ll act like this is a super fun topic, okay? Metrics and data analysis are few people’s favorite thing, at least if you’re in the creative world, but they’re the thing that keep your dinner table full, and understanding how it all works, just a little bit, can be the difference between make or break creative that can fuel real success. If technology hasn’t made it apparent yet, what happens in each stage of a creative project has impact on what happens in the next stage of that project, i.e. it’s all connected. The greatest creatives understand objectives, and aim for those objectives; you’ll hit zero of the targets you’re not aiming for…

This is a tough one, because it depends on what you’re aiming at. I always favor more general metrics, because they have a little flex in them. Raw impressions by itself tells you little, until you filter that number through your core audience and determine how well you hit your target in terms of actual response. You’re not just measuring revenue success; you’re measuring the actual audience your creative spoke to. That intelligence is as valuable as a successful campaign for your future if you think about how to capture it and how to use that to move up from a successful baseline.

This one is easy, go digital. Making technology a core part of your metric strategy isn’t rocket science, but the nuance of the way you do it is. Clunky jumps to mobile, heavy reliance on inbox presence, or other user opt-in features are a good way to get a high conversion rate, but they’ll teach you very little, you’ll shed many engaged people along the way. Finding ways to use inferential data meaningfully are critical to getting the How of your analytics right. The educational piece is too often overlooked in terms of takeaway. It can sometimes take a so-so campaign and follow it up with something electric. Making sure your analytics don’t get in the way of the face you’re presenting is

That’s right, when. Longitudinal measurements are great for some things, and useless for others. In my opinion, a lot of this has to do with whether you run long or short term campaigns, and whether your focus is on brand perception or revenue generation. Both at once is the golden egg, you can shoot for it, but you’re more likely to wander the land with no clear direction, and it’s hard to do that for too long. There’s also times when it’s appropriate not to measure.  Just like design, sometimes, in data analytics, less can be more. The hard frameworks required to capture granular data bend campaign creatives and user behavior into uncomfortable models, depending on your desired outcome, the pure experience might serve better, with a designed follow up feature at the appropriate time. Patience might cost you in terms of response rate and data capture, but it will leave the consumer with a much cleaner taste in their mouth for their next interaction with you.

To sum up, nothing is hard and fast, technology will change making all of this irrelevant in less than a year, and we’ll always struggle finding meaningful ways to learn from our successes and failures. It comes with the territory, but it doesn’t have to be a headache, and it offers valuable lessons even for the people who don’t have to do the measuring and analysis. Knowing how to elegantly design bits and bots to let you know what’s going on is an art form all its own.