Over time, duplicate profiles, erroneous data points, and inconsistent information will accumulate in your CRM or marketing automation tool, leading to financial inefficiencies, inaccurate analysis, and compromised marketing campaigns.
Data cleanup is a crucial task for any business that aims to maintain the integrity and reliability of its CRM. Over time, duplicate profiles, erroneous data points, and inconsistent information will accumulate in your CRM or marketing automation tool, leading to financial inefficiencies, inaccurate analysis, and compromised marketing campaigns.
In this article, I will explore why cleaning up your customer data is essential and provide a step-by-step approach to help you tackle this task effectively.
One compelling reason to clean up your customer data is the potential for cost savings. Many platforms charge based on the number of profiles, number of active profiles, or engagement metrics. If you have duplicate profiles or duplicate data points within your CRM, there's a high chance that you're overpaying. By identifying and removing duplicates, you can optimize your costs and maximize the value of your CRM investment.
Accurate and reliable data instills confidence in marketers. When assumptions are based on clean and trustworthy data, analysis becomes more accurate, and the results of marketing campaigns are more reliable. Marketers can make informed decisions, target the right audience, and achieve better campaign outcomes.
Having reliable data makes identifying any issues with customer profiles easier. Clean data makes it evident if a profile is duplicated or contains errors. It enables timely resolution of issues and ensures that your data remains accurate and up to date.
Cleaning up your customer data may seem overwhelming, especially if you're dealing with the issue for the first time. Here's a step-by-step approach to help you get started:
Begin by downloading a CSV file containing the data present in your marketing automation tool or CRM. This file should include user profiles and profile data points. By examining this file, you'll better understand the data you're working with. Don't overthink it at this step. Instead, focus on finding inconsistencies.
Start the cleanup process by identifying and marking the data points that you can trust. This includes reliable, accurate data that is aligned with your business requirements. Highlighting trustworthy data will provide a solid foundation and enable you to proceed confidently.
Next, identify and highlight the data points that are unreliable, questionable, or don't meet your quality standards. It may include data that appears sketchy, was manually imported, or doesn't follow naming conventions. By flagging these data points, you can focus on resolving them later in the cleanup process.
Tip: "2021_webinarattendance_Q1_email_opened" is defined as a sketchy data point.
Now, you have a set of data points that require further attention. Prioritize your efforts by focusing on essential data for day-to-day operations, automation, or immediate use. Filter the data based on how many users have existing values for each data point to understand its significance. Take your time to validate each data point and determine its importance and whether it can be safely removed.
Once you have validated the data, filter out the trustworthy data points and remove any unreliable or unnecessary items. Take advantage of any available records in your CRM or marketing automation tools to identify the source or creator of a data point and consult with them regarding its purpose and potential removal.
“If the statistics are boring, you’ve got the wrong numbers.” - Edward Tufte
Cleaning up your customer data is a crucial undertaking that helps you save costs, instills confidence in marketers, and enables you to spot and resolve data issues effectively. By following a structured approach and prioritizing data points, you can streamline the cleanup process and ensure the reliability and accuracy of your CRM or marketing automation tool.
Remember, data cleanup is an ongoing job, so make it a part of your regular data management practices to maintain data integrity and drive better business outcomes.
Pro tip: If your CRM or marketing automation tool allows it, create a dashboard highlighting that the data is not on par with your needs. This will help you to spot issues on the go.
