4 Simple Steps to Include in your Data Cleaning Process

4 minute read

Upland Admin

With legislation surrounding data protection becoming stricter (see CAN-SPAM, CASL and the impending new EU regulations), companies need to have clear data processes in place in order to stay on the right side of the law. But while many focus on making sure data collection goes smoothly, data cleaning is just as important.

Why spend the time to clean your data?

Many are reluctant to clean their data because they have difficulty in letting go of an email address they have worked so hard in obtaining. But what they don’t realise is that un-engaged or invalid email addresses are actually costing the company money. They can also negatively impact deliverability, as old, unused email addresses are often turned into spam traps.

But cleaning your data doesn’t mean deleting bad data. Clean data is also having the appropriate permissions in place to send emails to consumers, and making sure unsubscribed addresses are suppressed.

A well-orchestrated data cleaning process is likely to increase deliverability rates, save you money and give you a more accurate view of your email marketing performance.

Simple steps to include in your data cleaning process

1. Re-engage your current list

A good place to start is separating un-engaged contacts from your current list. Look into your campaign reports and pull-out the contacts who haven’t opened your emails in a specific time-period (for example, a year). Then send these contacts an email asking them to confirm whether they still want to receive emails from you, and to update their details.

And if you’re worried about potential negative effects on your deliverability from emailing inactive addresses, see how staggering your launches could help.

2. Evaluate your bounces

Go into your campaign reports and look at the group of addresses that bounce. There will invariably be some, sometimes because the email address does not exist, the domain name is invalid, the inbox of the recipient is full, and many other reasons.

Invalid data can sneak in by accident, like someone typing @goggle.com rather than @google.com when they signed up. Other times, you might be dealing with soft bounces, which are temporary.

What you need to keep an eye on are permanent (or hard) bounces – they should be separated as part of the data cleaning process. You can read more about the different types of bounces here.

3. Have suppression lists in place

Now that you have identified the addresses that you don’t want to email anymore, you should add them to a suppression list instead of deleting them. If you delete them and they somehow end back in your system, you will waste money emailing them again and the data cleaning would have been in vain.

Suppression lists also helps you ensure you don’t email contacts who have previously unsubscribed from your emails.

4. Prepare for the future with a double opt-in

A double opt-in process is when you sending new signups an email asking them to confirm their subscription to your communications. Consumers can sometimes agree to receive your emails without realising (often the case with pre-checked boxes during registration). By confirming the opt-in you prove that the action was voluntary. If not, the next time they get an email from you, they could mark it as spam and negatively impact your deliverability.

By doing more than the minimum required by law, you have confirmation that subscribers really want you in their inbox. This can protect you in the case someone tries to argue otherwise, so you don’t end up in court like John Lewis. It also gives you the opportunity to offer something like a discount code or free download as a thank you for subscribing. Or you can set expectations for the future with regards to content and frequency.

Case study: Sheerluxe achieve 98.8% deliverability

Sheerluxe was looking to improve the results of their newsletter, and reviewing their data played an important part in this. Their challenge was two-fold: improved inbox deliverability and engagement rates. The solution? A re-evaluated data collection process, a new approach to email design and a rougher implementation data best practice.

Read the full-case study >>

Key takeaways:

  • Give un-engaged email addresses one last chance to show they’re still active
  • Don’t be afraid to let go of inactive addresses because they are not even exposed to your messages, so you’re wasting money
  • Don’t delete, add to suppression lists
  • Adopt a double opt-in process

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