What Is “Bad Data” and How to Spot It

what-is-bad-data-and-how-to-spot-it

We spend so much time and money collecting data for our marketing efforts that many of us want to believe that’s all we have to do. Sadly even if the data you collected is accurate, data is like milk – it goes bad eventually. Data decay refers to the gradual loss of quality; resulting in outdated and oftentimes invalid data. About 25% of your email database will become outdated each year. Since data is the fuel of your email marketing efforts, this “bad data” hurts your results as we explain here.

Types of bad data

Not all data is bad for the same reasons. Let’s take a look at some examples:

Inaccurate data
Misspelled names & email address, incorrect phone numbers, you name it. These small errors are not only hard to spot in any database, but they can easily lead to offended prospects and bounced emails. Take some extra time to comb through your database from time to time and give it some love. 

Incomplete data
Data-driven marketing means that the more data you have on a prospect, the more you can personalize your campaigns. Incomplete data becomes a nuisance when targeting & segmenting your prospects. You want your email to land into the inbox of your ideal customer, which is very tricky if you are missing data such as their job title or the industry they work in. Suddenly you’re wasting precious resources while your emails aren’t landing in the hands of the right person. Likewise, you might realize you can’t personalize your email message properly if you’re missing crucial information like their name.

Outdated Data
People change jobs, companies merge. What was accurate today might not be tomorrow. Data expires at an alarming rate. You’ll want to regularly verify your data to make sure your database stays up-to-date.

Non-compliant data
Over the last few years, privacy has become a more complex topic. Anti-spam laws and regulations such as CAN-SPAM, CASL and GDPR help protect citizens from spam and fishy business practices. Make sure you do everything by the book to avoid hefty penalties.

Duplicate Data
You wouldn’t want to contact the same person twice. Avoid duplicates in your database by deleting duplicate contacts when you notice them.

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