A recent study by DDV (The German equivalent of the DMA) reveals that on average an email database will contain at least five spam traps. Five in a list of 100,000 doesn’t sound that bad, right? After all that’s only 0.005 per cent. But you’d be very, very wrong. Those five ESPs (email service providers) don’t know how many emails you’ve sent, they only know that you’ve sent an email to their spam trap and if you continue to do so will blacklist you.
The reason for spam traps
The battle against spam is raging. GDPR has gone someway in the EU to reduce unwanted email, but it is still the number one consumer complaint levied to ESPs. Hence spam traps – email addresses that are used to lure spammers. These email addresses do not subscribe to any organisations’ mailing lists and therefore should not receive any emails. Any mail that turns up in the account must therefore by its nature be spam.
Types of spam trap
There are two types of spam traps. The first is known as a pristine trap. This is a new email address set up by an ESP. The second form is a recycled trap. A recycled trap is an email address that was legitimately set up by a consumer in the past but is now dormant and has been deactivated by the ESP. After a period of time it is reactivated and used to monitor for incoming mail.
How do spam traps end up in your data?
Of course no legitimate marketers wants to be accused of sending spam – not least because of the damage to your IP address reputation which can lead to restricted or even refused email delivery, but also because it impacts campaign ROI and deliverability. So, if you carry out email marketing, spam trap screening is absolutely fundamental for the success of your future campaigns. Many organisations fail to do this because they believe in the quality of the data. However, even the most pristine email list can contain spam traps because of poor data sources, list contamination or the age of the data.
5 ways to avoid spam traps
Data quality: only use email data that comes with provenance and opt-in
Data cleansing: screen against lists of known spam traps
Data longevity: this is particularly important for recycled traps. Consider the age of the email address and whether or not there has been any interaction with long held email addresses. This is important for addresses over one year of age.
Data accuracy: ensure the accuracy of each email to avoid sending messages inadvertently to spam traps as a result of misspelt email addresses e.g. [email protected] instead of [email protected] Unfortunately spam traps tend not to be the obvious e.g. [email protected] Any malformed addresses should also be identified and then removed or corrected.
Data hygiene regime: prevention is better than a cure so a regular hygiene regime will keep data fresh and spam trap free
Email marketing is an incredibly powerful tool, and one that returns a strong ROI. However, just a few unchecked addresses can serve to undermine the entire channel.