Email List Hygiene

BuzzFeed Article Uses Validity Spam Trap Data: What Does it REALLY Mean?

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Yesterday, BuzzFeed dropped one of their signature exposés, this time revealing unsavory marketing behavior from the people behind SafeMask, a disposable mask people rushed to for safety from the novel coronavirus. In their reporting, they used some data from our spam trap network to highlight the sheer magnitude of dodgy email practices employed by affiliate marketers shilling this mask to desperate and vulnerable Americans.

BuzzFeed reported, “…Sendlane was designed to help affiliate marketing campaigns, but only ones that send emails with permission. But over the past 45 days, 177,567 SafeMask emails sent by Sendlane were caught in spam traps operated by Validity.” What the BuzzFeed article didn’t include was the fact SafeMask started to be blacklisted by Spamhaus and Invaluement during the first week of March.

First, it’s important to make a clear distinction: A spam trap is NOT the spam folder. Spam traps can be addresses created to catch people emailing addresses without permission, addresses gone unused for months or years, or simply addresses with typos in them. If an email reaches a spam folder, it had a correct and legitimate address, but the message was deemed unworthy for the inbox. Anyway…

How do emails hit our spam trap network? We’re going to get into this more deeply on an upcoming video in May, but let’s unpack this a bit.

A few scenarios come to mind. Email marketers aren’t looking at their engagement signals and continue to email old, unengaged addresses, which over time could become recycled traps. Or, senders shoot emails to addresses without ever obtaining permission to do so. This indicates major red flags: poor data collection, trying list appends where a sender tries to best-guess email addresses for customers or prospects, or list buying.

List buying is a super risky and inadvisable email marketing practice that could get senders in a lot of trouble in major countries around the world. Unfortunately, the United States simply isn’t one of them. Here, you CAN-SPAM (get it?). So, when you look at trap network data, you can get a sense of the volume of unsolicited email sent by an IP or domain. Chances are those who are hitting loads of traps are also getting tons of spam complaints, hard bounces, and other easily trackable negative reputation signals all working together to destroy their sending reputation.

Our spam trap network is designed to be used by senders who want to be good senders, so it helps them identify where their practices may be lacking. Maybe they would be well-served by list verification, or perhaps they’re not using segmentation to weed out unengaged addresses who should stop receiving mail simply because they don’t seem to like it anymore, or maybe they’re playing it a little too fast and loose with their address collection practices. Email service providers (ESPs) can also use the network to see if any senders using their platform are behaving badly, and they can mitigate those issues before they cause issues for other customers.

Not only that, our spam trap network can identify when an IP or domain is blasting unauthorized email with phishing or malware scams inside, making it a tool really worth knowing.

That’s why we’re going to share a new experts-led video in just a few weeks, looking at the Validity spam trap network which now combines both Return Path and 250ok trap networks, its size and capabilities, and how it provides a key service to senders around the world. If you have questions about spam trap networks, bring them to our next State of Email Live webinar on April 29, where we’ll host an Ask-Me-Anything with several experts who can give you all the info you need. You can register now.

Articles like BuzzFeed’s show it’s a valuable tool not just for helping good senders get better, but also helping protect the email ecosystem by identifying and stopping bad senders from putting people at risk.

Because that’s what we’re about: making email better for everyone. See you then.