Big data is the buzz word of the year. I keep seeing numerous posts about how the more information your business collects and how it is going to improve your ROI. It seems that every data company is trying to capture the most information to piece things together about their users to have unique interactions and create engagement.
Ok, so all of this sounds great but what happens when information in the database has wrong information? Perhaps your database was comprised of shared information with partners and a partner has sent over some bad information by mistake, it happens! Maybe you collected information about Phil that he is an athlete and recently completed a marathon, so now you are ready to send him an offer on the next best pair of running shoes. The most crucial piece of information is having the right contact credentials.
Phil originally made a mistake when he registered for his run and entered his email address as email@example.com and without taking a second look you decided to email your campaign to him. This particular email account would have resulted in a hard bounce. After having a human look at this email address you can instantly see that gmall is likely supposed to be gmail, but when you collect hundreds of thousands of records per day you cannot possibly have an employee sift through all that data.
This is why it is highly important to have a data validation solution in place. XVerify specializes in email verification to detect these errors and make the correction on the fly. With common miss spellings of popular domains Xverify can resolve the situation. If your customer fat-fingers an extra letter or digit in the email address then we catch that too. We want to help you build lasting relationships with your clients or prospects and the first step to have the ability to communicate with them directly.
Even when your growing database gets verified upon the collection of the email address, you can still run into a snag later. Good email accounts can go dormant or get closed by the end user it is recommended that you clean up your entire database on a quarterly basis. As a rule of thumb don’t let your data age past 90 days without sending it for an updated cleaning.
“You can have data without information, but you cannot have information without data.” – Daniel Keys Moran