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Data hygiene: best practices for a better database

Last updated: October 8, 2024

45% of marketers don’t validate their data for quality and accuracy, and 62% use incomplete or invalid prospect data, according to research from Mercury, a creative digital marketing agency. That’s bad news, because inaccurate audience data will undermine your engagement and ad campaigns before they even begin. 

There’s the obvious consequence — not being able to reach your prospects at the right email address. But if you never check your contact lists for accuracy, you might also assume that your campaign’s failure is due to poor strategy rather than an outdated contact list. This can lead you to make unnecessary changes to your strategy and set you even further back.  

So how can you make sure your data always reflects what’s actually going on with your audience? Here, we’ll explain what it means to have “clean” data, then present our best practices for data hygiene and standardization across your whole organization.  

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What is data hygiene?

Data hygiene is the ongoing process of cleaning the data you collect to maintain its integrity and accuracy (e.g., removing duplicate entries, standardizing naming conventions, etc.).

Data is “clean” when: 

• You can establish a single view of each customer (i.e., you don’t have any duplicates) 
• Each customer’s record is accurate and up to date  
• Each data label is standard across every software you’re using (i.e., you use DD/MM/YYYY across all platforms rather than mixing it up between tools)
• It’s error-free, without any typos, structuring or formatting issues
• If you’re using third-party integrations to send data between systems, imported data is being stored under the right label (i.e., your data mapping is accurate)
• Read more on data cleaning best practices here.

5 benefits of proper data hygiene 

Data hygiene gives you accurate insights. That gives you a complete, current view of how your customers are interacting with you across every channel. That helps you give each person the content and offers they need to convert — all with less time and effort. Some other benefits of data hygiene include:  

Get more income from each customer by offering the offers, promotions and premium memberships/subscriptions most likely to resonate with them.  

Accurate audience information allows you to target offers based on someone’s previous engagement and purchase history, so you can make upsell offers or cross-promote related publications at the right time, in the right place. 

Improve customer retention by creating a more cohesive customer experience:  

When someone submits a support ticket, your support team can pull the user’s profile to see what product or service they’re using, what self-service resources they’ve already tried. They can address the problem more quickly instead of spending excess time on background questions.  

You can guide each customer down a personalized journey across multiple channels, from email and display ads to your website. At each touchpoint, they’re getting the same consistent message — and it’s tailored to their exact needs, demographic, past purchase behaviors, etc. 

Drive repeat purchases and renewals by making competitive insights more accurate and complete

A single customer view gives you a 360-degree picture of how each of your customers — and your broader audience segments — feels about your product. Use this to figure out what they need before they need it.  

Facilitate personalization, customer loyalty and advocacy  

The more you know about your audience, the easier it is to personalize your communications and offers for their needs. That alone can drive repeat engagement, brand loyalty and even additional word of mouth traffic over time, setting off a virtuous cycle of strong customer lifetime value and loyalty.  

Research backs this up: According to McKinsey’s Next in Personalization Report, three-quarters of consumers (76 percent) said that receiving personalized communications was a key factor in prompting their consideration of a brand, and 78 percent said such content made them more likely to repurchase. 

And 78 percent of consumers said they were more likely to recommend friends and family to companies that personalize.  

Streamline workflows and reduces cost to serve

Data hygiene prevents your team from making bad bets, whether it’s targeting an ad campaign at the wrong audience or triggering an upsell at the wrong time. It also keeps your editorial team from wasting time writing content that’s not proven to drive engagement or traffic. 

And ultimately, clean data frees up time for higher-priority creative tasks that can help you resonate with customers and drive revenue.

That creates a nice flywheel effect where your team has more resources for creative and strategic work, they can drive more impact and more revenue, and that gives them even more to invest in good content over time. 

Best practices for data hygiene 

Regularly audit your data 

One of the biggest barriers to data hygiene is the sheer scope of data to manage. The average company takes in customer data from multiple marketing channels, like email, social media, website forms and tracking, third-party cookies, etc. And your data consumers/stakeholders are siloed on different teams, it’s possible that nobody in your company knows exactly where all of the data comes from, much less how to wrangle it and make it actionable.  

Performing a regular data audit can help you keep track of your data — and diagnose potential quality issues. Locate all of your existing data, list your input and output data sources, and identify any recurring issues that might impact your data quality. 

Standardize contact data 

Data is only actionable when every stakeholder knows what each datapoint is measuring. This is only possible when every data point is standardized from the first point of entry. 

Establish a set of “brand guidelines” for data labeling so every data point is uniform and can be easily used across teams. For example, you might use a prospect’s local timezone to measure when they took a particular  action, rather than GMT, etc. Or you might agree on a certain set of criteria to move each candidate’s record from your CRM to your customer data platform, etc. 

You should also create a standard operating procedure for data entry, especially if some points are still entered manually. Also implement regular process checks into the process so that errors can be resolved before they impact campaign success or the health of your database. 

Verify data accuracy and integrity

Obviously, you can’t manually check whether each of your customers have changed job titles or email addresses in the next 6 months. But you can periodically review your database to confirm that your customer records are legitimate and free of irregularities. 

Customer data platforms like Omeda can perform many of these processes automatically. To flag fake accounts, Omeda checks the incoming name fields of each profile and rejects any name that has no vowels, 6+ consecutive consonants, repeating letters or is on a list of specific names that have been marked as junk.

Omeda has built-in procedures to remove junk characters (* or !, etc.) from customer profiles and match incoming information to established customer profiles. 

Omeda and other customer data platforms also require that specific data fields be mapped (like email, one part of a postal address, etc.,), all of which keeps customer data as accurate and relevant as possible. 

Identify and merge duplicates 

When customer data is spread across multiple softwares, it’s more likely that you’ll accidentally create more than one customer record for the same person. This could happen if someone books a demo, which is tracked by your CRM, but also regularly browses your website (which your 

Besides complicating your reporting and increasing the cost of campaigns, duplicate records also prevent you from getting a single view of your customer and reaching them effectively. Given the marketing and reputational cost of dupes, you should look to merge duped records whenever possible.  

But what if you don’t want to risk losing data from one of the records? Or you can’t be sure that two similar records belong to the same person?

Customer data platforms can help you identify and merge identical customer profiles without losing any profile data, For instance, Omeda’s Identity Resolution solution uses a combination of exact and fuzzy matching to develop a confidence score for determining unique and common records. If the records are determined to belong to the same person, the data from both profiles is merged into one, with any outdated information archived in our database for record-keeping. 

Unify your data 

Many data quality issues stem from overcomplicated tech stacks. Data stored in one place never makes it to the other, or it arrives with inconsistent naming conventions or incomplete records. This makes it a lot more difficult to use that data for its intended purpose, whether that’s creating segments, personalizing messaging, etc. 

Multiply that over thousands of customers and this can have huge revenue and opportunity costs for your business

Solve that problem by consolidating your tech stack. This makes it easier to manage, activate and benefit from the customer data you work so hard to collect. For instance, Omeda’s form builder connects to our customer data platform. This way, every form response is automatically recorded in our customer database, instead of needing to be cleaned, manipulated and sent across teams. 

Instead, sales and marketing can find it right away, capitalizing on audience interest more quickly, and ultimately get more conversions.. So as you evaluate your data strategy, look for opportunities to streamline. If you’re doing your email marketing in one platform and marketing automation in another, consider managing both processes — and collecting the resulting data — from the same place.

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