Dirty data can make your conversion rate look lower than it is. It can also cause you to send information to people who don’t want your information, especially if you purchase leads. The best way to handle this is to ensure that you start with good data, and that you collect good data in an organized way the first time.
Do It Right the First Time
The fact is, the reason people have dirty data is that they didn’t plan so that they could collect the right data in the right format, for the right purpose. So before you bother collecting the data, ensure that it fits into the categories you’ve designed and that it will be collected properly so that you’ll have less to clean.
For example, don’t import all the email addresses in your Google account to LinkedIn or other business platforms, because not all of them are your audience.
Use the Right Tools
Each type of data needs a specific tool to help you use that data to your advantage. In some cases, you’ll need your data to be able to be downloaded in a single Excel sheet to organize it; in other cases the data needs to be on many sheets. Yet other times it’s all online in a database that the software tool you’re using has created. The right tool will make data cleaning much easier.
Define What Constitutes Dirty Data
Each business will have its own definition of dirty data. This could be incorrect email addresses, fake names, old information, incorrectly formulated results and so forth. Once you have determined what is dirty and why, you’ll know what to do with that data to clean it up.
Understand How the Dirty Data Is Being Created
For example, let’s say you have a lot of inactive subscribers. How did they get on your email list? Let’s say you notice that 100 people who downloaded a freebie from you never opened your emails. If you’re still offering that freebie, check it out to ensure it really is the right freebie for your audience. It may need to be tweaked or replaced entirely, and the people on the list that never opened your emails can be deleted.
Delete Fake Names
One way that you end up with dirty data even if you’re using the right tools has to do with the software you are using. For example, if you’re using an autoresponder form to collect email addresses in exchange for giving them a lead magnet, nothing is keeping them from entering a fake name. Go through the names. If something stands out, search their email address to find out if it matches their name. If it doesn’t, it’s a fake name and they’re likely just freebie seekers and you can delete them.
Never Opens Emails
If you’ve collected a lot of email addresses over the years and they’re on your email list, remember that even if they don’t open the emails, you’re paying for them to be on your email list. You can be relatively sure that if someone hasn’t opened an email from you in a year or more, they’re never going to. Delete them out of your mailing lists to clean up your data and improve your open rates immediately.
This depends on your system. If you’re using a system like AWeber.com for your email lists, you may have duplicate names legitimately because they’re signed up for more than one of your freebies or have purchased more than one of your products. But if you’re using a system like ConvertKit.com, then you should not have duplicate names on your list. You should be able to improve tagging to avoid that problem.
Having said that, nothing is preventing someone from signing up again with a different email address. You can sometimes eliminate this by asking for more information so that for anything that’s the same, such as Twitter handles, you can combine their account into one.
Work on keeping your data clean to start with, as it’s so much harder to clean it later. If you think about why you’re collecting the data and set it up correctly the first time, you are less likely to have dirty data.