Analytics: Lies, Damned Lies, and Statistics
We ran a blog post a few weeks back about “Analytics and the Art of Decision-Making”, and the basic point was to look at how analytics actually affects decision making (duh). It’s something I think about a lot, because let’s face it: analytics data is not the end-all, fail-safe tool that it’s made out to be at times. If it were, people wouldn’t still be making ineffective marketing decisions, and everyone’s marketing ROI would be skyrocketing. This makes me think of the old Samuel Langhorne Clemens quote, “There are three kinds of lies: lies, damned lies, and statistics”. So where should data analytics fit in your marketing decision making process, and how can you get the most of the data you have? Follow the jump!
For starters, it’s important to look at data analytics as a part of your process, not the ENTIRE process. There are countless occasions where analytics data has led to revelations that have saved or made companies millions of dollars. There are almost as many occasions where data has been, for whatever reason, worthless. This is why it’s important for marketers or marketing teams to have a breadth of knowledge covering data and marketing. An analyst with no marketing background will struggle to uncover any useful insights from data, and a marketer with no data background won’t be able to make the data tell a story in the first place. The best way to look at data is as a key ingredient in your process, and as a way to check what you think you already know.
Secondly, and most importantly, you need to make sure that you’re measuring the right things (and measuring them correctly). Let’s use a sports example for this one. Say you’re comparing Tom Brady, the legendary future Hall of Fame quarterback of the New England Patriots, and Christian Ponder, the Vikings quarterback who gets benched by his coaches every other week. Ponder has completed 63% of his passes this year, while Brady has completed only 60%…Ponder is clearly the better player right? (Try to make that argument in a Boston sports bar). The point is, you can (either consciously or sub-consciously) cherry-pick data to tell any story you want to tell. To get value out of your data, you need to tell as much of the story as you can…to go back to the football example, you’d bring in other data: touchdowns thrown, interceptions thrown, quality of receivers, difficulty of throws attempted, etc.
The conclusion we can draw here is that it’s important to have a blend of marketing and data knowledge on your team. If you make all your decisions from data in a vacuum, you’re minimizing your success. Likewise if you ignore data and make all your decisions based on some marketing person’s “gut instinct”. If you maximize your data, but temper it with marketing insight and experience, then you are on the surest road to success.
Thoughts? Let us know in the comments!