4 Sure Signs Your Data Needs A Cleanse


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Ever feel like you need to put down the fatty foods and booze and go on a “cleanse”? You know, water with a wedge of lemon, vegetable broth. Maybe you need to flush the body of toxins to get back in working order.

Your data sometimes goes through the same thing. In order to get the most out of your data sometimes you need to put it through a cleanse, or at least a scrubbing. Putting your data through the wash can help ensure you’re reaching the right targets with your marketing campaigns. Below we provide 4 signs that your data might be due for a cleanse.

A VP By Any Other Name…
So Jon B. Pasty has identified himself as Vice President of Marketing Strategy on one form and Director of Strategic Initiatives on another. Oh, and when you collected his info at an event two months back his title was Senior Vice President of Product Positioning.

Just who the hell is Mr. Pasty?

If your database has multiple titles for the same person, it can make figuring out whom you want to talk to onerous, hindering your lead nurturing efforts. Throwing your data into the wash can help normalize the situation. And that will lead to better targeting and segmentation.

Haven’t I Met You Before?
Similar to receiving multiple titles, you might have more than one email address in your database. Perhaps Mr. Pasty provided his work email at that event, but used his personal email to download a white paper.

Who cares? Multiple email addresses can lead to some embarrassing oversights when sending out campaigns. For instance, maybe you’re offering a 30% discount to a certain segment in your database and 10% to another. Mr. Pasty gets both offers and, of course, opts for the higher discount. You may have just surrendered 20% of revenue on that opportunity. Either way, multiple emails to the same person suggest you don’t know the person behind the email, which looks unprofessional.

Global Pains
Big, global brands often carry slightly different monikers. Widgets Inc. may have divisions such as Widgets Ltd., plc or SA, for example. If 10% of your data has duplicates like IBM Canada and IBM CA, then it can mean multiple members of your sales team are selling to the same company.

Similarly, most forms in use are not standardized, which can result in a wide variety of country codes coming in. (Think: US vs. USA vs. United States.) If you have a wide variety of country codes coming in, you’ll have to remember all the variations in order to properly segment that data.

Finally, large companies may span across industries. Multiple employees from the same business might identify across various sectors. If you are targeting by industry, this can have a real impact on the success or failure of your marketing campaigns. With a good data cleaning you can set all these situations straight, improving your campaign analytics and campaign measurement. (For more on global database marketing check out this informative post.)

The 10 and 70 Guideline
There are no hard and fast rules in terms of how much duplicate or incomplete information is tolerable in your database. It depends on the size of your company, the organizations you are trying to reach, etc. But there are some general guidelines. If your database contains more than 10% of duplicates, it might be time to put your data on a cleanse.

Also, many people might not take the time to fill out all the required fields you request. You might ask for a company name and get “AAA”. Broadly speaking, if less than 70 percent of your data is incomplete, it might also be time for a cleanse.

Bottom line: A good run through the wash will help cut down on duplicate, incomplete or inaccurate data, and make your life much easier.

Republished with author's permission from original post.

Jesse Noyes
Jesse came to Eloqua from the newsroom trenches. As Managing Editor, it's his job to find the hot topics and compelling stories throughout the marketing world. He started his career at the Boston Herald and the Boston Business Journal before moving west of his native New England. When he's not sifting through data or conducting interviews, you can find him cycling around sunny Austin, TX.


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