As marketers, data is our lifeblood. It provides us with the insights and intelligence we need to make data-driven decisions, drive campaigns, and improve engagement with customers. But to get the most out of your data, it’s essential to maintain good data hygiene.
Clean data hygiene means the records in a dataset are accurate, complete, and up to date. Maintaining clean data helps you avoid costly mistakes, such as mistargeting or missing out on valuable insights due to outdated information.
By following a few simple best practices, you can ensure your data is squeaky clean.
What Is Data Cleansing and Why Is It Important?
Data cleansing is the process of systematically going through your data to identify and fix issues that could be affecting your data’s accuracy.
FYI – The terms “data cleansing,” “data cleaning,” and “data scrubbing” all refer to the same activity. However, in some cases, “data scrubbing” may be more specific and refer to the process of removing duplicate, outdated, or irrelevant data from a set.
The data cleansing process can involve a variety of tasks, such as:
- Finding and correcting errors or typos
- Removing duplicate data entries
- Filling in missing information
- Standardizing formats to ensure consistency
- Identifying and removing outdated data
Inaccurate or outdated data is often unusable because it will lead to incomplete insights. Keeping data clean is crucial for maintaining the accuracy of your reports and analytics.
In the context of digital marketing, good data hygiene can improve conversion rates and personalization capabilities for your marketing campaigns. Clean data will help you better understand customer behavior, create segmentations for more effective and personalized campaigns, and ultimately, drive more revenue.
Data cleansing also saves time. Clean data is free of clutter, which makes it easier to locate and analyze. (No more spending hours sifting through disorganized records!)
What Is a Data Hygiene Process?
A data hygiene process is an organized effort to maintain and validate the accuracy of your data on an ongoing basis. This process should include regular reviews of existing data and proactive checks for any new information that needs to be added or updated.
Here’s how to begin your data hygiene process:
- Establish Data Standards and Benchmarks for Accuracy – Set a threshold for data accuracy and determine what types of criteria need to be met in order for data to meet these standards. (We’ll talk more about this in a sec!)
- Create a Clean-Up Schedule – Conduct regular reviews of your data on an established schedule (e.g., monthly or quarterly). Each review should include proactive checks for new information and retroactive reviews of existing data.
- Utilize Automation Whenever Possible – Automation can help streamline processes and reduce the time needed to maintain data accuracy. For example, you can use automation software to check for duplicate records, fill in missing information, or complete other tasks that would be tedious for human resources.
- Fix Problems Quickly – If you do find errors or issues with your data, it’s essential to address them quickly, so they don’t compound over time.
- Monitor Your Progress and Results – Be sure to track your progress against your standards and benchmarks–did you meet them? Are there areas where you need to focus more effort? Your assessment will keep you on track and ensure that you stay up-to-date with changes in your data.
Your process for data hygiene may look slightly different depending on your organization’s needs, but following these steps will help ensure your data is always accurate and ready for analysis.
What Is Good Data Hygiene?
As we mentioned, you’ll define what “good data hygiene” is for your organization. Every company’s data is unique, so your criteria for accuracy will depend on what’s important to you and your customers.
Here are a few criteria to consider:
- Accuracy – Does the data accurately reflect what’s happening?
- Completeness – Is there any missing information that needs to be included?
- Timeliness – Is the data up-to-date and reflective of current trends or conditions?
- Consistency – Is the same format used throughout the data?
- Accessibility – Is it easy to locate and access the data?
By setting standards for data accuracy, you can ensure that your data hygiene process is effective and tailored to fit your organization’s needs.
Common Data Cleansing Challenges
The data cleansing process becomes more complex with larger datasets, as there will be more information to review and errors to fix. With thousands or even millions of rows of data, it can become difficult to manually review and correct errors.
Here are a few common challenges you might encounter when you scrub your data:
Different sources of data may use different formats or terms to describe the same thing (e.g., the way a phone number is formatted “437-703-2699” vs. “(437) 703-2699”). Consistency issues can be time-consuming and challenging to fix, so finding a way to standardize data formats is crucial.
Duplicate records can lead to inaccurate insights and analysis. To avoid this issue, create processes for identifying and removing duplicates from your dataset.
Make sure you regularly review and update your data. As we mentioned, outdated records can lead to incorrect conclusions and decisions.
You can overcome these challenges by utilizing automation tools, such as data cleansing software, to help you quickly and accurately identify and fix errors. This can save time, and effort spent manually scrubbing your data.
If you don’t want to manage the data cleansing process yourself, you can hire an experienced professional to do it for you. They’ll do all the heavy lifting plus provide expert guidance on how to manage your data properly.
Work With a Data Cleansing Professional From Marketing Automation Canada
We recommend completing a data audit each quarter to maintain clean records. Managing data can be a daunting task, but with the right team, it doesn’t have to be. At Marketing Automation Canada, our experts are here to help review your data for accuracy and to optimize it so you can leverage it to make data-driven decisions.
Contact us today to learn more about how we can help your team clean and maintain your data!