The only thing better than putting on a warm shirt right out of the dryer is putting on a CLEAN warm shirt right out of the dryer.
Similarly, the only thing better than a data set is a CLEAN data set. If you don't have clear data on your target, you'll get a loose campaign that never hits home the way that it would if the information in your database was correct.
That's why list hygiene is such an important part of data management. Like an unwashed shirt that's just out of the dryer, your data's going to stink after a while. Ask the following questions before a data purge:
1. What information do we need?
2. How much of that data is already in our system
3. Which data should we get rid of?
Which information do we need?
Square one is always a great place to start. Make a list of the type of information you need in the data set. After you've created a list of possible types of information, discuss each to whittle your list down to the essential facts. This is especially important for companies with limited data storage capacity.
How much of that data is already in our system?
Assuming that you already have data, you need to look through it. Of the information you decided to use, how much of it already exists in your system? You'll probably find a lot of useful tidbits, like current addresses and names. More than likely, the correct behavioral data will be harder to find.
Which data should we get rid of?
This is, of course, the essential question when performing a purge. Is the whole list headed for the trash bin, or are there grains of truth that should be sifted out? If this is the first time you're scrubbing your data, this will take longer, but will be extra beneficial.
Just remember to include the info from question #1 and make sure not to add purged fields back into the mix. Happy cleaning!