With Halloween right around the corner, it’s time to talk about the skeleton in every business closet: wasting valuable time and resources reaching out to customers who are no longer with us. Of course we don’t mean to send to deceased customers, but how would you or your clients know any better? The answer is using data hygiene. It’s time to stop sending out offers to the dead.
The Value of Data Hygiene
Data decays at a rate of about 2 percent per month, and by the end of the year you can expect that about 30 percent of your database information is no longer accurate. This is not exactly ideal for planning your next marketing campaign. However, this is where a suppression list can help you. By identifying the customers in a database who are no longer with us, you can simply remove these names from your mailing and start your campaign with no worries.
Suppression is useful for much more than removing deceased customers. You can use suppression to identify a variety of qualities, including:
- Customers who are in prison
- Recipients below the age of eighteen
- Individuals who have filed for bankruptcy
- Customers who are on the Do Not Call registry
Keeping Your Data Up-to-Date
Regularly cleaning up and maintaining your data can also help your marketing efforts. With the high rate of decay for most databases, it pays to know that your information is as fresh as possible. Beyond suppressing the records on your list that don’t match with your target audience, data cleansing is another beneficial way to make sure you are reaching individuals at their best point of contact.
By using consumer information updated every month, such as that found in AccuLeads, you can feel secure that your database information is as accurate as possible.
Related: Four Data-Driven Marketing Must Haves
The data you provide and what you can do to help your clients are valuable tools in your ability to keep your current business and attract new customers. Additionally, what you are able to do with the data you own and collect about customers is equally important.
What are your biggest challenges with data? Tell us below!