Why You Should Work Towards Clean Marketing Data
My name’s Cade Jones, Digital Marketing Manager here at Element Three, and I’m here to talk to you today about one of the most vital but commonly overlooked portions of your marketing operations, data integrity. But before I do so, let me just set some ground rules.
This content is most helpful to marketers, not engineers, not data scientists, marketers who have a baseline understanding of data accuracy, completeness and consistency. At the end of this, my goal is for you to walk away feeling like you’re armed in charge to essentially help better understand your department and how marketing and data can be aligned and working in the same direction for your team.
All right, so let’s dive in. What is dirty data?
Dirty data is inconsistent, incomplete or often just data with errors throughout it. It can come from human error, so somebody’s inputting into an open text field or it can come from your systems being set up in an unstructured manner. Essentially, and most commonly, it’s because people who are setting up forms on their website or whatever it is don’t have the end output of what they want that data to do for them in mind at the outset.
I like to think about it as a little bit of like a messy room. So when you walk into a messy room, you have clothes scattered throughout, everywhere. You know what you want to wear, but you don’t know where it is. And so it essentially slows down your time to put on those clothes.
Data works in the same way. It’s typically all there, but in an unstructured manner, you don’t know where to go to find that insight that you might be looking for.
The harms here are obvious. The messier the data, the slower it is to draw insights. The slower it is to draw insights, the slower you are to deploy your activities and the slower you are to deploy your activities, the slower it is to see the ROI from your marketing efforts.
So why does this matter?
Well, let’s say you’re looking to optimize your marketing funnel, specifically the average days between lifecycle stages in a user journey. When that data is clean, those insights are readily at your fingertips, and you can deploy a strategy quickly to decrease the amount of time between stages.
When it’s not clean, you’re left doing the manual effort of figuring out where that leaky gap is in the funnel to essentially deploy that same tactic. So if you can move at twice the speed, you can deploy the tactic twice as fast and see the impact twice as fast as well.
So if I were you, I’d be asking, what can I do to improve the data integrity across my marketing operations? Well, first, I would make sure that there’s a clear owner on your team, somebody who owns the data, it’s cleanliness, how it’s collected.
The second thing is making sure that you have set audits, checks and reviews of your data on a weekly, monthly basis depending on how much you’re getting into your systems at any given time.
The third thing is making sure that your data strategy is in place. So when you’re setting up forms or the collection of the data, making sure you think through where down the road are you going to need this data and how it’s going to be used?
And then lastly is just having data analytics tools that helps a lot of this process — what is typically manual — become automated so that you can again draw those insights quicker, faster and more strongly.
Doing these things will essentially enable you as a marketer to be more informed on what’s happening with your data, how to use it, and how to deploy tactics and strategies to help impact the ultimate ROI of your marketing efforts.
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