Readers of my blog know that one of my core messages to B2B email marketers is a dedication to data quality. By making quality a cornerstone of your email campaigns, you’ll not only focus on serving your exact targeted prospects and delivering them real value, but also avoid the many pitfalls poor data quality can bring.
Indeed, poor data quality remains a challenge for B2B marketers. A recent survey that analyzed over 775,000 B2B tech contacts found that 25% of the average B2B marketer’s database can be determined “inaccurate,” while a full 60% of companies continue to struggle with “unreliable” data.
The study found that the most common data quality issues B2B marketers face, ranked by the percentages of data that include these errors, are:
- Duplicate data (15%): While this data error can be defined as having the same contact repeated in your database twice (or more), the problem can be even more complicated – and harder to detect – than that. This is because duplication can often be attributed to poor data formatting. For example, the same person might be included multiple times on a list if their names are repeated but different (e.g. “Robert” and “Bob”) or, as is more common, company names are repeated (e.g. “Proctor & Gamble” and “P&G” or “Bank of America” and “BofA”) Discovering these duplicates might be compounded further if the contact record contains other missing fields (e.g. titles or addresses), making comparisons and cleansing both difficult and time-consuming.
- Invalid values or ranges (10%): Contacts can be erroneous if the data is contained but is inaccurate. For example, corporate headquarters addresses are often defaulted or assumed by marketers, but these days, employees are more dispersed than ever. For example, while you may be targeting the Boston region, the product manager you want to reach may actually be located in Denver. In addition, if your campaign is targeting small and mid-sized businesses (SMB), you might identify a specific contact as working in a small (50-100 employee) office, when in reality, he or she works for a large, dispersed organization.
- Missing fields (8%): Incomplete data will make sorting and targeting difficult, relegating many contacts into the dreaded “other” or “miscellaneous” list, where successful email targeting will be difficult at best. For example, if you’re creating a campaign targeted at specific levels or titles within an organization, and many of the titles are missing in your database, your message and value proposition will likely miss the mark within the target company. Or, it will fall flat or be ignored by the recipient. The Same theory applies to missing regional data, company size, products in use, etc. You get the idea.
So while the error rates within contact data are significant, the cost of cleaning it can be equally discouraging. The report finds that manual processes to review and correct the information can introduce additional human error, and would require companies, on average, to review and repair over 300,000 contact fields.
While this laborious amount can be reduced with automated data governance software, the real, most efficient solution to addressing the data quality dilemma remains acquiring, capturing or entering it into your database the correct way to begin with. It all points to the need for B2B marketers to consider the resources they have, both internally and externally, and then consider the best way to achieve the data quality that email marketing success demands. It’s that simple.
Find and win new customers with targeted, high-quality email marketing data from OMI. Click here for more information and download our new e-book, “The Executive’s 15-Minute Guide to Building a Successful Email Marketing Database,” today.