Automation platforms, social media, paid advertising, the cloud and countless other new technologies have driven marketers to rely heavily on large amounts of data. Finding quality data to purchase and keeping your own records up to date is a significant challenge. Employees change jobs, companies go under or rebrand. These are just a few reasons it’s important research those you’re purchasing lists from, audit the data and keep close track of your return on investment.

Higher Quality Leads

A recent Forbes Magazine article noted, “Better data enables more accurate targeting and communications, especially in the omnichannel environments many organizations are striving toward.”

The merging of inbound and outbound marketing techniques has amplified the need for high quality data as most companies now engage their audience through a multitude of channels. If you receive inaccurate data, it’s possible you’ll email, call and direct mail someone multiple times before realizing the data is incorrect. This can cost you time, money and potential new business. Even leads that come through inbound marketing sources are best served being qualified with teleprospecting efforts before passing them along to sales.

Efficient Email Campaigns

According to Ascend2, “51% of marketers say enriching contact data quality is their most significant barrier to achieving email marketing success.”

Data quality in an email marketing campaign impacts your bounce rates, which can have a far-reaching affect on future emailing efforts and your web reputation. With more than half of email marketers identifying contact data quality as a top priority, it is clear many organizations have an issue with finding quality lists and qualifying leads.

Measuring Data Quality

DiscoverOrg uses six parameters to measure data quality:

• Completeness: Is the company, contact, or prospect record as complete as possible?
• Uniqueness: Are there duplicate records? Can records be combined?
• Timeliness: Is the data fresh? Has it been recently confirmed?
• Validity: Does the data conform to a common syntax? (e.g. “ave.” vs. “avenue”)
• Accuracy: Is the information correct?
• Consistency: Is the data presented in a way that is the same as similar records?

Developing a clear list of parameters to audit the data you are receiving will help you compare potential list dealers in a more complete form than simply measuring leads and sales. It is also important to remember that list data degrades over time and continuous attention to your database is needed to ensure efficient and successful campaigns.