How To Build a Data Hygiene Process 

In your research and development process, have you implemented proper data hygiene measures? If the answer is no, it’s time to start. 

Data hygiene is the process of cleaning and clearing out any irrelevant or inaccurate data from lists you have collected. This helps keep your marketing efforts and predictions as accurate as possible, improving your ROI and ensuring that you invest your time and energy into worthwhile strategies. 

Why is data hygiene important?

Having accurate data is one of the most important assets any company can possess. Data helps companies make informed decisions to strengthen their strategies and review how current marketing efforts are performing. 

Data hygiene can be a complex process, but the outcomes are well worth it. Data hygiene is crucial for understanding the patterns and behaviors of your users, the performance of current marketing campaigns, and spotting any inconsistencies that might indicate a potential problem.

What is a data hygiene process?

A data hygiene process is the methodology companies use to update and refine data sets to make the most accurate predictions from their analyses. This process can look different from business to business, depending on the data collection method. When first starting to implement a data hygiene process, there are a few quick tests you can perform to cleanse your lists off the bat. Keep reading to explore how. 

Start by implementing a cleanout policy

First and foremost, it’s crucial for you to implement a clear and consistent cleanout policy. It is best to conduct a formal cleanout quarterly, but the maximum you can wait is up to a year. Be careful, as the longer you go between cleanouts, the more your work will pile up. For example, if you conduct a cleanout every quarter, the process will likely only take a day. If you conduct your cleanout annually, you may have to set aside up to a week to perform all of the necessary tasks. 

The timing of your data cleanout heavily depends on your area of business and the quantity of contacts/leads generated (and how frequently!) If your database is less than 50,000 contacts, you can likely conduct an annual cleanout. If you are working with over 100,000 leads, it’s best to complete the process quarterly.  

Say goodbye to the bounce 

The next step is to remove all contacts/leads that have bounced when contacted with marketing and campaign material. The only exception to this rule is if an active user has bounced, but they are a paying customer or active user in a SaaS. If you do identify a paying customer that has bounced emails, reach out to your customer success team to confirm the email is correct. This will help refine your lead lists and ensure your marketing efforts are effective and worthwhile. You don’t want to be constantly contacting leads who are not receiving your emails! 

Review data fields 

Next, evaluate basic data fields to ensure customers have completed and formatted the information submitted properly. Often, customers are completing data fields on their phones, tablets, or in a rush, which can lead to incorrect data such as email addresses, residency, or other crucial information. Data hygiene will be much easier to manage in 6-12 month chunks rather than years of bad data all at once, so keep this in mind when beginning your process. 

Check-in on inactive users 

Inactive users can be another source of dirty data and must be addressed to ensure accuracy. Send a check-in email to all contacts that have not engaged in marketing or campaign efforts in the past 12 months. If they do not engage in any way within two weeks of the check-in, it is best to delete their information from your system. Or, if the email bounces when you go to reach out, delete the contact altogether immediately. 

Send reminder emails to users

Everyone needs a reminder from time to time! Even your customers. If your business has a product that requires user log-in, send a quick reminder to all users who have not entered their account in the past year. This will help you ensure that the data you are collecting is up to date. It is also good to schedule a reminder like this bi-annually to make the data hygiene process more efficient. Setting automated reminders in HubSpot puts this process on autopilot.

Look for patterns and trends 

Another critical pattern to look for is customers who have not engaged with your marketing communication within the past year. Again, this means that they are likely not contributing quality data to your lists and can even skew some of your results. Try to see if you can identify trends in customers that are not engaging with your communication efforts. For example, if they have similar user profiles, account types, or industries. 

Once you have identified these patterns build a few re-engagement campaigns to see if you can get them back on board with your brand. If they use your product functionally but are not building an ongoing relationship with your brand, it will be easy for them to leave your platform and go to a competitor. Brand buy-in is crucial for retention, so re-engagement is key! You can re-engage by customizing emails, creating targeted ad campaigns, or using other creative efforts to target inactive users specifically. 

We hope this article helps you implement a strong data hygiene process to ensure the accuracy of your data pulling and predictions. Happy cleansing!