How to Clean up Your CRM Database for Marketing Automation - dummies

How to Clean up Your CRM Database for Marketing Automation

By Mathew Sweezey

Cleaning up your database in preparation for marketing automation is a must to protect your sender score and sending reputation. Your sender score is a numeric grade that spam filters put on your IP address. The higher your score, the better your chances of getting your emails delivered to a person’s email inbox.

One of the reasons people obtain a lower score is that they send emails to bad email addresses or spam traps. If you have been building your database for years, you likely have a large number of both in your database.

While you’re preparing your customer relationship management (CRM) system for marketing automation, it’s a good exercise to clean your database so that your CRM integration starts out with a clean bill of health. You have two good ways to clean a database. One is by using tools to do it yourself; the other is by hiring someone to do it for you.

How to use tools to clean up your database

You can easily access many tools for cleaning up your database through online services. The cost of your database cleanup will be a direct reflection of how large your database is and what, specifically, you need cleaned. For the purpose of protecting your sender score, you need to be concerned only with the validity of the email address, not all the information in a record.

Data brokers are another way to clean up your database. Companies such as, Dun & Bradstreet, and Equifax can help you to clean up your database in one fell swoop and help you augment your data at the same time.


Part of cleaning up your data involves verifying whether data is accurate. Two different types of data are used for verification:

  • Crowd-sourced data is collected when people enter their own information into a public database. For example, people on the social media site LinkedIn create a profile and enter data about themselves.

  • Verified data is collected by companies who are in the business of data collection. For example, Dun & Bradstreet is a company that collects data from a variety of sources, including credit reports, public documents, and questionnaires.

List-cleaning tools such as NetProspex, RingLead, and FreshAddress are also great tools for cleaning up your data set in real time moving forward. Verified data sources such as NetProspex routinely call each data point to verify that the information is correct. This type of tool can be a more expensive option than using a data broker, but it tends to have a higher reliability.

Data cleaning tools can also be integrated into a marketing automation solution to clean and augment each new prospect record that comes into your database in real time.

Tools such as RingLead help you to better de-duplicate data coming into your database to ensure that you are connecting the right information to the correct record. It solves the problem of having the same lead in your database five times because that prospect used five different email addresses. This is very important if you have very complex data sets or have multiple email addresses on a single person.

Hire someone to clean up your database

If you can’t use an automated tool because of the size of your data or the specific nature of the data needed, you can find consultants or outsourced call centers who can clean your data for you as well as offer data augment services without the need for automated tools.

Hire a consultant with specific industry knowledge to help expedite the process of data collection, cleansing, and augmentation. Hiring a consultant who knows how to use your chosen marketing automation solution would be prudent. Choosing a consultant who is not familiar with your industry is okay if you have to compromise, but do your best to avoid consultants who lack a working knowledge of your marketing automation solution.

An outsourced call center is a more expensive option than a consultant, and it tends to take the most time. This option is generally the best option for companies that need to constantly augment and cleanse data as it comes in.

A call center can be tied into the lead qualification stage and manually verify data before that data is passed on to the next stage. The call center can also obtain data via a phone call that cannot be obtained via online interactions.