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Keep It Clean, People: Why Data Cleanliness Is Important

Alert: the next sentence is kinda gross. A few months ago, I cut into a green bell pepper and discovered a big, gross patch of mold inside of it. After I finished running circles around the kitchen while shouting “ewwww” at the top of my lungs, I started thinking about data. Because that’s what I do, even at the most random times.

“Your data” is a big, somewhat amorphous thing that you likely mostly think about as a whole. But much like that horrible pepper, sometimes you don’t know if something’s rotten about it until you slice into it and see what you’ve got. (I bet you were wondering how in the world I was going to connect moldy peppers with data. Well, there you have it.)

Marketers don’t really do that enough. It becomes one of those, “Yeah, I know I should scrub my data, I just haven’t done it yet” things. And they run campaign after campaign and collect more info and data and the problem gets worse and soon you have these terrible things lurking in your data, screwing up your marketing results. You wouldn’t use mushy, spore-infected veggies while cooking (I hope)—so why would you use bad data to market with?

I’m going to stop talking about the pepper because it still gives me the heebie-jeebies just thinking about it, and move on to what you want to know—why you should give your data the loofa treatment. Bad data permeates like a bad odor and affects everything it comes in contact with: campaign performance, sales team effectiveness and ultimately revenue.

The sucky thing is, there’s no easy way to clean up your data. No simple answer, or single tool. Instead, you have to use a layered approach.

Standardization—If your data collection is a free-for-all where everyone formats fields however they’d like, you’re doing it wrong. Draw up some rules and standards around data collection and make sure your whole team follows them. It’s the only way to ensure scalability so you don’t have a big fat mess years later.

De-Duplication—Dupes suck. They take up space in your database and artificially plump your numbers. Depending on your CRM, there are ways you can set rules to identify and merge duplicate records. You may have to do a little hands-on work in batches to address some that don’t quite fit the specifications, but driving them out of your system is definitely worth it.

Data Capture—If you’re using cookies to collect additional info about your site visitors, make sure this data is making it into the correct records. Again, you want to avoid duplications of information. Plus, if your data is scattered, it makes it that much harder for you to engage in targeted marketing and for your sales people to ultimately close them. After appending, make sure you run through standardization and de-duplication to keep it all squeaky clean and purty.

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