Good data quality processes can have an incredibly positive impact on the overall quality of an organization’s data. There’s perhaps no better representation of the importance of a data quality process than in a company’s marketing department. With digital marketing quickly becoming the main source of brand awareness, leads, and sales revenue, being an effectively data-driven department is crucial for success. So, how can your marketing department take action to collect and utilize clean, actionable data? Let’s take a look.
Data Capture Standardization
Capturing consumer data via digital contact forms is an excellent way to execute re-marketing opportunities. Whether it’s lead capture or just signing up for a newsletter, this engagement allows marketers to have an ongoing relationship with consumers. However, this marketing tactic can take a turn for the worse if data capture is haphazard. To ensure your data is consistent, make sure all data capture fields (Name, Email Address, etc.) are the same across every campaign, all the the time. This will ensure your database will have identical fields filled in, across every marketing effort, keeping the data you collect actionable for every continued campaign moving forward.
Data Verification Automation
Another extremely useful tactic is to have an automated verification process incorporated into your data capture process. When the lead or consumer enters their email address and additional information, an email is then sent to the email address that the user registered in the form. The user is then asked to verify they received the email, ensuring they entered the correct email to receive the newsletter, promotion offer, or any other call to action. Ensuring that you’re capturing the correct email means fewer bounced emails and less lost re-marketing opportunities due to typos during the data capture process. This automation is, more often than not, easily utilized in any email marketing client, social media platform, or other data capture solutions. Using this widely-available feature can go a long ways to making sure your data is clean and actionable now, as well as for the foreseeable future.
This is just one example of the potential effectiveness for incorporating a data quality-conscious approach to your company’s data. If you have any tips you’d like to share, let us know on Facebook or on Twitter.