There’s something about bounces

I’ve shared a version of this image repeatedly. I think it was only my Facebook friends that got the stick figure screaming in frustration, though.

An overlapping circles diagram showing bounce classifications from 3 different ESPs and how they overlap (and don't) with each other and with my classifications of the underlying error.

The reality is bounce handling is one of the most frustrating pieces of email delivery. Not only that, many people in the email space treat it as a simple process. It’s really not as simple as we’d like it to be.

The above image was created based on docs from 3 different ESPs a client was using. They wanted to normalise their bounce handling across ESPs, and asked me for policy recommendations. I ended up digging through a bunch of docs from their 3 ESPs. I recorded the reasons as reported in the docs in a colored block corresponding to the ESP, then dropped them in the appropriate circle: soft, block or hard.

The shaded circles are based on my interpretations of why these bounces happen.

  • The big grey circle surrounds bounces due to reputation issues.
  • The green circle is primarily networking and technical issues.
  • The top purple circle is non existent or bad addresses

Note, nothing here indicates how we should react to the bounces, this is just a categorisation activity. This classification also has nothing to do with what the actual SMTP response is.

Just remember, next time someone says bounce handling is simple: they’re wrong.

Related Posts

Share your average bounce rates

The question came up on slack this morning about bounce rate benchmarks. What are the normal / average bounces that different ESPs see? Does region matter? What’s acceptable for bounce rates?

Read More

Thoughts on bounce handling

This week’s Wednesday question comes from D.

What are your thoughts on bounce handling

Read More

Bounces, complaints and metrics

In the email delivery space there are a lot of numbers we talk about including bounce rates, complaint rates, acceptance rates and inbox delivery rates. These are all good numbers to tell us about a particular campaign or mailing list. Usually these metrics all track together. Low bounce rates and low complaint rates correlate with high delivery rates and high inbox placement.

Read More