While list growth is usually something to celebrate, a sudden spike in subscribers could be a sign of trouble.
A spambot is an abusive computer program that signs up a large number of real or fake email addresses to thousands of mailing lists. They can cause issues with your reporting, sender reputation, and deliverability.
Spambot attacks can significantly damage your sender reputation, and reduce your delivery rates. Typically, victims see an increase in spam complaints, bounces and unsubscribes, as well as decreased open rates.
Spam complaints increase when real email addresses are added by spambots without the owner's permission. Imagine your email landing in hundreds of inboxes of people who have never heard of you, or have no idea how you got their address. Some people may delete your email or unsubscribe instead of making a complaint, but this still negatively affects your sender reputation.
Even unopened emails are bad news. In email deliverability terms, low open rates are a clear signal that your recipients are not engaged with you, your brand, or your content. Lack of engagement is a factor in the delivery of future emails, and can even lead to your messages being blocked.
High bounce rates are another side effect of spambot signups. Sending to a list corrupted with hundreds of fake email addresses results in hundreds of "hard bounces". If bounce rates are high enough, then email servers may reject or block your emails entirely, and you could start to see bounces from legitimate recipients.
As explained above, there are many signs to alert you of a potential spambot attack. If you think a spambot may be attached to your subscriber list, you should identify the fraudulent addresses and remove them.
In some cases, it's easy to spot fake signups because the addresses look very spammy. Or, you might see a batch of signups that share a common characteristic, such as a consecutive number string, a random alphanumeric string, or domains that contain the same word, for example:
Start by exporting your email list, including all subscriber fields so you can look for oddities. Here are some other things to look out for:
If you can determine a pattern, the next step is to create a segment using that pattern to isolate the fake signups. See the instructions below.
You can build segments to isolate fake signups, based on information like "Date subscribed", "Name", "Email address", "Location", custom fields, or a combination of these.
For example, if a name, phrase or set of numbers are repeated in the signup details, you can segment them by creating a rule based on name or email, then choose "contains" as the condition.
Instead of just deleting spambot email addresses from your list, it's a good idea to add them to your suppression list. After you've created a segment to isolate the fake signups, follow these instructions: