Why You Should Care if Your Data is Dirty

When was the last time you updated your marketing database? If you can’t remember, chances are you are using dirty data. Dirty data is outdated, is typically riddled with mistakes and is incomplete. Using it can negatively impact your entire organization. At worst, it will ruin not only your marketing campaigns, but your online reputation as well. Yet, many companies ignore data hygiene—according to Sirius Decisions 25% of the average B2B database is inaccurate and 60% of companies surveyed had an overall data health scale of “unreliable.”

Using dirty data is a sure fire way to become blacklisted by your internet service provider—that means you can not send messages to your customers and prospects, missing out on opportunities to move prospects through the pipeline and reach customer segments with important offers.

But it goes beyond email to impact all of your marketing efforts, and therefore your revenue generation.
To keep your data fresh, you need to perform regular data hygiene checks. This is more than removing duplicate names from a CSV file. It includes removing unresponsive contacts and appending your data file. At a minimum, this should be done yearly. Here are three steps to take now:

Check your database today to see how healthy it is.
How many bounces are you getting? How many of your contacts have not opened an email in six months or more? How many mail returns? How many duplicate records? A good health check should identify spam traps and determine record completeness at a minimum.

Establish you data management strategy.
To keep you data fresh, you need to know what your standards are. What constitutes a complete record? What are your minimum standards for deliverability? What do you need from data providers? Then regularly perform maintenance and updates to ensure you are in compliance with your strategy.

Append and update records.
As you delete names from your database, you want to add, append and update your records. Appends and updates ensure proper taxonomy, addresses, phone numbers, email addresses, and syntax are correct. Make sure you use a reputable data partner for this. If you’re only paying pennies per name, you are not going to get quality data.

Clean data is critical for your long term success. If you’re starting from scratch, learn how to build a good mailing list for your small business here.

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