The perfect email

More and more I’m moving away from consulting on technical setup issues as the solution to delivery problems. Delivery is not about the technical perfection of a message. Spammers get the technical right all the time. No, instead, delivery is about sending messages the user wants. While looking for something on the blog I found an old post from 2011 that’s still relevant today. In fact, I’d say it’s even more relevant today than it was when I wrote it 5 years ago.
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Email is a fluid and ever changing landscape of things to do and not do.
Over the years my clients have frequently asked me to look at their technical setup and make sure that how they send mail complies with best practices. Previously, this was a good way to improve delivery. Spamware was pretty sloppy and blocking for somewhat minor technical problems was a great way to block a lot of spam.
More recently filter maintainers have been able to look at more than simple technical issues. They can identify how a recipient interacts with the mail. They can look at broad patterns, including scanning the webpages an email links to.
In short, email filters are very sophisticated and really do measure “wanted” versus “unwanted” down to the individual subscriber levels.
I will happily do technology audits for clients. But getting the technology right isn’t sufficient to get good delivery. What you really need to consider is: am I sending email that the recipient wants? You can absolutely get away with sloppy technology and have great inbox delivery as long as you are actually sending mail your recipients want to receive.
The perfect email is no longer measured in how perfectly correct the technology is. The perfect email is now measured by how perfect it is for the recipient.

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Setting expectations at the point of sale

In my consulting, I emphasize that senders must set recipient expectations correctly. Receiver sites spend a lot of time listening to their users and design filters to let wanted and expected mail through. Senders that treat recipients as partners in their success usually have much better email delivery than those senders that treat recipients as targets or marks.
Over the years I’ve heard just about every excuse as to why a particular client can’t set expectations well. One of the most common is that no one does it. My experience this weekend at a PetSmart indicates otherwise.
As I was checking out I showed my loyalty card to the cashier. He ran it through the machine and then started talking about the program.
Cashier: Did you give us your email address when you signed up for the program?
Me: I’m not sure, probably not. I get a lot of email already.
Cashier: Well, if you do give us an email address associated with the card every purchase will trigger coupons sent to your email address. These aren’t random, they’re based on your purchase. So if you purchase cat stuff we won’t send you coupons for horse supplies.
I have to admit, I was impressed. PetSmart has email address processes that I recommend to clients on a regular basis. No, they’re not a client so I can’t directly take credit. But whoever runs their email program knows recipients are an important part of email delivery. They’re investing time and training into making sure their floor staff communicate what the email address will be used for, what the emails will offer and how often they’ll arrive.
It’s certainly possible PetSmart has the occasional email delivery problem despite this, but I expect they’re as close to 100% inbox delivery as anyone else out there.

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About that Junk Folder

I use a pretty standard mail filtering setup – a fairly vanilla SpamAssassin setup on the front end, combined with naive bayesian content filters in my mail client. So I don’t reject any mail, it just ends up in one of my inboxes or a junk folder. And I have a mix of normal consumer mail – facebook, twitter, lots of commercial newsletters, mail from friends and colleagues and spam. (As well as that I have a lot of high traffic industry mailing lists, but overall it’s a fairly normal mix.)
My bayesian filter gets trained mostly by me hitting “this is spam” when spam makes it to my inbox. If I’m expecting an email “immediately” – something like a mailing list COI confirmation or email as part of buying something online – I’ll check my spam filter and move the mail to my inbox in the rare case it ended up there. Other than that I let it and spamassassin chug along with no tweaking.
I’m starting a data analysis project, based on my own inboxes, and as part of that I’m using some tools to look for false positives in my junk folders, and manually fixing anything that’s misclassified. I’ve been doing this for a couple of hours now, and I’ve found some interesting things.

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