Last week we had the opportunity to ask a couple of questions to Peter "Dr. Pete" Meyers, Marketing Scientist at SEOmoz. Pete shared with us what it really means to be data driven and what we can do to make sure data is actionable
Here's some really useful tips:
What does it really mean to be a data driven company?
If I really had to boil it down, I think being truly data-driven is all about listening, even when the numbers tell you things you don't want to hear. Many companies claim to be "data-driven", but that seems to mean that they create metrics that back up what they already believe or help justify the existence of some manager or department. Being data-driven isn't about collecting a mountain of data to hide your problems with - it's about asking honest questions and finding the right numbers to answer those questions.
In the context of marketing, what are the typical challenges in choosing the right metrics and what can we do to facilitate that process?
I think one of the biggest challenges is that not every metric suits every situation or audience. What the CEO needs to see and what content marketers, social media managers, etc need to see can be very different. Ultimately, it's a question of (1) how much do you simplify, and (2) how do you end up with something that's actionable (and not just looks nice on a PowerPoint slide). They're both balancing acts - if you don't summarize enough, you can't act. If you summarize too much, you might miss something useful. I think the key is to never treat any one metric as sacred. Any measurement or summary is just one point-of-view.
What would you suggest are the best mechanisms or processes that startups can adopt in order to make sure that data is actionable and acted upon?
Don't get hung up on perfection. You'll never find the ultimate metric, and you're going to have to evolve along the way. Pick something actionable, build a goal around it, and try something. Spending two years deciding which metric to use can be worse than no metrics at all. This means you have to accept a certain amount of flexibility and even forgiveness. Measure success in modern marketing channels is tough, and you shouldn't fire everyone after three months because they can't live up to your first attempt at measurement. Metrics should allow you not only to measure success, but to adjust to failure and improve. It's an ongoing process.
Could you tell us a little bit how do you go about making sense of data and making sure those insights are communicated?
Even when I'm wearing a data science hat, I always try to have a question to answer. I think it can be dangerous just to hand someone a pile of data and say "Here - find something!" Our obsession with "big data" is only making that worse, in my opinion. Data can hold answers, but you have to ask the right questions.
As you saw in our recent report, a lot of startups struggle when choosing their metrics and then acting upon them. Could you offer some advice on this?
I think step one is to pick something that sounds sane and accept that you're going to have a few missteps. If I had to generalize, from a marketing mindset, I'd say to start with at least one "traffic" metric and one "conversion" metric. Ultimately, sales depends on how many people you get through the door and what percentage of those people buy what you're selling. Pulling one lever or the other isn't enough. What exact metric you use to measure each of those can be very situational, but if you've covered both sides of that equation, you're off to a good start. Once you've got that down, you can start looking at things like lifetime value, but everyone has to start somewhere.