Many businesses are losing revenue and wasting marketing efforts due to poor data hygiene.
Inaccurate, incomplete, and outdated data can hurt customer trust and lead to lost marketing spend.
Whether you’re looking to boost marketing ROI or deliver better customer experiences, clean data is a must.
In this article, we’ll dive into what data hygiene is, why it matters, and most importantly – actionable steps you can take to clean up your database.
Data hygiene refers to the process of ensuring that a database’s data is clean, correct, and relevant.
It’s about looking at your data to find and fix problems like:
Data hygiene can help you:
Data hygiene typically involves several steps:
These steps transform raw, messy data into a clean, reliable resource.
While data hygiene and data management are related concepts, they are distinct.
Data management is a broader discipline that surrounds how data is collected, organized, stored, maintained, and used throughout its lifecycle.
Data hygiene, on the other hand, specifically focuses on the processes involved in keeping data clean and accurate.
It is an important element of overall data management but has a narrower scope.
Effective data management requires good hygiene practices and other considerations beyond cleanliness, such as data security, access control, integration, and analysis.
These elements ensure your data is clean, secure, and easily accessible.
Data hygiene can help ensure the accuracy and reliability of your organization’s data assets.
Data decay is a process that gradually erodes data’s value over time.
It can occur through outright data loss (such as accidental deletion) or when data entries become outdated and irrelevant.
Research suggests that the average business sees around 30% of its data decay yearly.
Investing in data hygiene allows you to:
Accurate and clean data allows firms to fine-tune their targeting plans and personalize offers.
Mistargeted messages due to poor data quality can push away potential customers and lead to wasted marketing spend.
Data hygiene practices ensure that customer info is always current and relevant.
Bad data is costly.
Duplicate records and wrong information not only consume time but also increase operational costs.
By investing in data hygiene, you can tackle duplicate records and incorrect info head-on.
Data hygiene makes operations smoother and cheaper, cutting down on the extra costs tied to sorting out inaccurate data.
Start with a thorough audit.
Before you can create a plan to maintain clean data on an ongoing basis, you need to gauge the current state of your database.
Ask yourself: Which data fields are essential? Which ones are redundant or irrelevant? Which sections of your database are most problematic? The audit process uncovers inaccuracies, outdated entries, and other data quality issues.
Create a step-by-step action list. This might include:
Inconsistent data entry practices create dirty, unreliable data.
Establishing clear standards is a necessary step for maintaining data integrity.
You’ll need to identify which data fields require standardization of formats and values.
Numerical data like quantities, prices, and other quantifiable values should be mandated in a consistent format across systems. Allowing different styles (e.g., 1,000 vs. 1000 vs. 1,000.00) introduces unnecessary variance.
Standardization also benefits text fields containing proper names, titles, and addresses.
Determine whether titles like Ms./Mrs. should be used consistently or omitted entirely. Spellings should conform to a single regional standard, such as American or British English. Abbreviations for street names (St./Ave./Blvd.) should always use the short or long form, not a mix.
These protocols must extend beyond internal systems to any customer-facing platforms where data is collected, such as web forms or checkout flows.
Consistency across all data entry touchpoints is key. In addition to format standards, validation rules should be set to prevent the entry of invalid data values.
Certain fields can be marked as required to avoid blank entries.
Numeric fields can specify allowable ranges to block unrealistic values. Data types (e.g., text vs. numeric) can be enforced to maintain data integrity.
Use smart tools to keep data clean and on track. Companies like IMDataCenter can clean your data, auto-fix and merge duplicate entries, and keep it fresh.
Human mistakes are the leading cause of dirty data. Even a small typo can lead to missed opportunities and lost revenue.
Automated cleansing systems use algorithms to quickly identify anomalies and outliers caused by human error across large datasets.
These tools can also eliminate duplicate records, a common issue when companies rely on a single data point like email to identify contacts.
Multiple records may be created if a customer provides different emails on separate forms, preventing a complete customer view.
Cleansing tools use predefined rules to merge duplicates and maintain proper data hygiene.
However, studies show that under 50% of sales teams use automated tools to clean and deduplicate data before it enters their databases.
Maintaining a clean database involves removing information that is useless to your business objectives or could expose you to legal risks and reputational damage.
Ultimately, you collect data to leverage it for marketing and customer engagement. Any data points that fail to serve these goals or could negatively impact your brand should be suppressed.
This includes:
While more data is often seen as better, unnecessary information only clutters your database and complicates hygiene efforts.
It minimizes wasted marketing spend, legal risks, and any activities that could tarnish your brand’s reputation.
By being informed about what data you retain, you ensure a lean, high-quality database that delivers value rather than creating noise.
By this stage, you likely have a partial profile for each contact in your database, such as their name, email, and company address.
More powerful databases may include job titles, phone numbers, company revenue, tech stack, and location.
However, if these data points are incomplete or inaccurate, you risk inadvertently violating GDPR or CASL regulations.
Data appending can fill in those gaps.
This allows you to confidently engage with your audience while staying within the bounds of these laws.
Rather than avoiding communication due to fear of non-compliance, data appending allows you to connect with your contacts in a legal, personalized way.
It’s a proactive step toward better data hygiene and more effective, compliant marketing.
Data hygiene can be challenging, especially for large or intricate databases.
Consulting with a data team brings specialized expertise to your database, ensuring that your efforts are both effective and compliant.
These pros can provide tailored solutions and strategies to meet your unique data needs.
For example, platforms like IMDataCenter offer secure, automated data append and enhancement solutions that deliver high match rates and complete consumer identities from minimal inputs.
The right data partner will have deep experience helping businesses across industries clean, validate, and enrich their data assets using proven best practices and proprietary technologies.
This lets you focus on your core business while ensuring this critical data maintenance is done right.
The end result is a clean, reliable data foundation for confident decision-making and improved marketing outcomes.
While data hygiene has a high payoff, the process takes time and effort. Many organizations find it beneficial to outsource data hygiene to a trusted partner like IMDataCenter.
Their secure platform does all the heavy lifting for you, providing access to enterprise-grade append solutions for a fraction of the price.
With IMDataCenter, you can:
Getting started is easy – simply create your free account to test IMDataCenter’s solutions for yourself.
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