Retailer or Spammer? You Decide

Email deliverability is hard. It’s hard for retailers trying to get campaigns into customers’ inboxes. It’s hard for mailbox providers trying to keep users’ inboxes safe. It’s hard for consumers trying to manage their messages. Deliverability is hard.

So often, I hear marketers express their frustrations with mailbox providers when they find out campaigns are being filtered to the junk folder or blocked altogether. “Don’t they know my brand?” “Why would they mark me as spam!?!” “Can’t you just call someone and tell them my mail is OK?”

As marketers with a specific motive, I understand their perspective and the very real business impact of campaigns never making it to the inbox. I also understand the challenges mailbox providers face when sorting and filtering mail.

Each day, 225 billion emails are sent to nearly 5 billion email addresses. Mailbox providers have the difficult daily task of sorting through hundreds of billions of messages and determining which are legitimate, and which are malicious and spammy. In 2016, 65 percent of email volume was attributed to spam, the highest it’s been in the last five years. This huge volume of unwanted mail is just one reason for mailbox providers to be skeptical of incoming messages.

The landscape is constantly evolving, but there are common practices that complicate the process and make it nearly impossible to separate the spammer from the retailer. Can you determine which sender is legitimate in these three scenarios?

Scenario 1: The Quick Move

  • From: A well-known retail brand domain
  • Subject line: You’re invited
  • IP activity: No recent history, 1 million messages sent today, high number of unknown users
  • Message content: All images with an address in the footer
  • Problem: This is a new IP address with no sending history. The image-based content isn’t easily scanned to determine the risk level of this email. Is it a retailer or spammer?

Scenario 2: The John Doe

  • From: Another well-known retail brand domain
  • Subject line: BOGO 50% Off!
  • IP activity: Sender score of 80, regular weekly email volume of 500K-4M messages, high complaints
  • Message content: Some images and text
  • Problem: This sender’s history includes wide ranges of volume and a high number of complaints from subscribers. The content headers don’t include a DKIM signature, so the sender cannot be validated. Is it a retailer or spammer?

Scenario 3: The Random Send

  • From: A well-known retail brand domain
  • Subject line: Members Save an Extra 20%! TODAY ONLY
  • IP activity: Sender score of 85, last campaign of 200K sent two weeks ago, 1.5 million messages sent today
  • Message content: Some images and text, text contains pharma-related verbiage
  • Problem: This sender has inconsistent mailing history. The pharma-related content may or may not indicate a spam message. Is it a retailer or spammer?

Did you spot the spammer among the retailers? Probably not, because all of these examples describe recent campaigns sent by legitimate retailers. Surprised? Think about your own campaigns. How would your messages look if we anonymized your mail in this same way? To avoid looking like a spammer, review your sending patterns for risk factors, and consider these tips:

  1. Don’t change ESPs or IP addresses often. Sending permanence is an important factor in your reputation, as spammers often jump around to new IP addresses to avoid being detected. If you do move to a new vendor or IP address, slowly ramp up the volume to establish a solid reputation before moving the entire program over.
  2. Mail consistently. Review your sending patterns and adjust your mailing schedule to prevent gaps in sending (days/weeks with no campaigns) and large volume spikes. Steady, predictable volume lowers the risk of your campaigns being filtered or blocked.
  3. Authenticate your mail. Mailbox providers use DKIM, SPF, and DMARC as a way to validate a sender’s identity and inform the sorting process. Updating your message headers to include this information is a simple step to prevent message filtering.
  4. Manage your metrics. Watch your performance metrics for spikes in unknown users, complaints, and spam traps. Remove problem data immediately to keep issues from compounding.

This post originally appeared on Total Retail.

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