What is 'clean' data?

In short, ‘clean’ data means accurate data, and for data to be truly accurate, it needs to be complete. In a customer database, for example, complete data means full names, correct addresses/locations, and dates of birth. Of course, this depends on the data that customers have provided, but all data that is required by your business should be 100% accurate.

‘Clean’ data also means data that is free of duplicates; having the same customer’s details replicated in your database can adversely affect marketing and reporting. It can also serve to annoy the person whose data is duplicated, as they could receive multiple identical marketing emails, damaging the relationship at an early stage.

What causes inaccurate data?

Lots of factors can negatively impact the quality of data. Some of the key causes include:

Human error - As the acquisition of data is fundamentally reliant on people inputting their data themselves and this then being processed by employees, human error is one of the main causes of poor quality data. Whether this involves an individual misspelling their email address or an employee incorrectly inputting a last name, this can easily lead to inaccurate data.

Data duplication - With the importance of data apparent to the brands of today, it's likely that you’ll acquire data from a variety of touch points like website forms, social media lead generation ads and in-person sign-ups. This can lead to one person’s data being duplicated in the database.

The consequences of inaccurate data

Using incorrect, inaccurate, or incomplete data can cost your business in a number of ways.

• Wasted ad spend

If you’re targeting incorrect or outdated audiences, then your carefully planned ad spend budget will be going to waste. Even the smartest and most innovative strategies will be leading you down the wrong path if the data you’re using is incomplete or inaccurate, which means you’ll need to spend more time and money correcting your inaccurate data and targeting the right people further down the line.

• Loss of revenue

If you haven’t segmented or personalised your audiences properly, you’re going to see a reduced ROI on your marketing campaigns. Taking a bit of extra time and care to ensure everything is 100% accurate can make a world of difference to your marketing performance.

• Reduced productivity

Once you’ve discovered that your audiences are improperly segmented, or there’s duplicate information in your database, or customer details aren’t complete, then someone is going to have to fix it. This'll use up valuable time that could have been spent planning the next campaign, acting on findings, or working on other projects. It can also hinder any automation workflows that you have in place, as the inaccurate data will cause them to malfunction.

• Damage to brand reputation

Inaccurate information can lead to incorrect or unwanted messaging to customers, which can be very frustrating. Sending emails your customers aren’t interested in is a surefire way to drive unsubscribes, unfollows, and even complaints and customer churn. Your brand should be synonymous with impactful, effective, and engaging messaging, showing that you truly understand your customers, and demonstrating the value you have to offer them - to do that, you need clean data.

• Compliance fines

Huge regulatory importance is placed on data integrity and compliance. Falling foul of regulations like General Data Protection Regulation (GDPR), even accidentally, can lead to considerable fines. Plus, customers rightly take their data privacy very seriously, and using non-compliant data can lead to some angry questions from your recipients.

Best practice for ensuring clean data

So, there are plenty of less-than-ideal consequences for using inaccurate data, but luckily there are steps you can take to keep your data clean and complete, and we’re going to go through them here.

• Conduct regular audits
  Regular audits are a very effective way of keeping on top of the state of your data. Scheduling these audits ensures time for checking duplicates, errors, and inaccuracies within your data, so you can rectify any issues before they cause problems.
• Standardise your data
  If all your data follows the same format, it’s easier to prevent errors when recording said data. Establish a standard practice or a template for data entry that includes fields for all required info, and that’ll help people avoid mistakes. Make sure the standard of data entry is known by everyone who needs to know it - that way, they’ll also be adept at spotting any errors.
• De-duplication tools
  As well as internal procedures, there are several helpful tools that can automatically detect and merge duplicate information. Investing in one of these tools can save you a lot of time and effort that would otherwise be used trawling through your data to find and remove duplicates.
• Real-time verification and validation
  With some clever methods, you can ensure your data is accurate when it is entered. Things like email verification processes during sign-up - confirmation links, for example - can ensure that you’re storing the right email address when a customer signs up. You can also use automated messaging to follow up with customers when they haven’t responded or opened an email in a certain amount of time: Something like “We noticed you haven’t opened an email in a while - would you still like to receive our marketing emails? If you don’t respond to this by [date], we’ll remove you from our database.” This will help you keep your database clean.
• Segment maintenance
  Are your segmentation criteria up to date? Have there been any changes in your database or your business that would require some adjustments to your segmentation? Be sure to regularly check the way you are segmenting your audiences to keep everything as it needs to be.
• Integrate data sources
  If all your data sources and systems are synced up, the likelihood of inconsistencies is significantly reduced. Check all the tools and platforms you use to see if it’s possible to connect them, and if it is, make sure they’re connected!
• Staff training
  We’ve already mentioned the importance of standardised, established protocols for data and maintenance, but it’s crucial that staff are fully knowledgeable of those processes and their importance. Regular training and refreshers can help staff uphold your protocols, whether that’s by maintaining their own standards or spotting errors made by others.

Summing up

So, as you can see, there are plenty of reasons to keep on top of the accuracy of your data. From costly compliance fines to wasted money running campaigns powered by outdated information, inaccurate data can harm your business’ bottom line. Not only that, it can lead to lost productivity, hours spent rectifying easily avoidable mistakes, and crucially, a loss of trust amongst your customer base.

By following the tips we’ve supplied above, and refining them into actionable steps for everyone in your business to adhere to, you can minimise the chances of data errors and ensure your business is always reaching the right people in the right places.