How Spamfilters Work

AllSpammedUp has a post describing the primary techniques anti-spam filters use to identify mail as spam or not spam. While is this not sender or delivery focused knowledge, it is important for people sending mail to have a basic understanding of filtering mechanisms. Without that base knowledge, it’s difficult to troubleshoot problems and resolve issues.

Any anti-spam system that is worth using will contain a range of preventative measures and features that are used to determine whether an email is likely to be spam or not.  As a complete solution they can be very effective, but taken individually and their weaknesses become more apparent. […] when you combine a number of different techniques into a single system, with each technique applying a “likelihood” score to each email that is checked, the system can be quite effective.
For example, if an email is from an IP address that is not considered a likely spam source (no score increase), but contains spam-like content (score increased according to severity), and fails sender verification (increases score again) , the combined “likelihood” score may reach the configured threshold for the system and cause the email to be treated as spam.

This is the concept I try to convey by using my bucket metaphor.

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We want your mail to succeed

One thing I hear from a lot of delivery folks, both consultants and those who work at the ESPs, is that their customers and clients fight back whenever they say no. A client or a customer proposes this great idea that involves sending irrelevant email to uninterested people. Then, with bated breath, they ask their delivery consultant to agree it is a brilliant idea. Most of the time, their great idea is actually a bad idea. Those of us who have been around a while can even and provide examples and experiences that back up that it is a bad idea.
The result is similar, when told their idea will hurt their delivery they fight tooth and nail. On good days they will argue and decide to listen. On bad days they go off and do what they were warned not to do.
It can be horribly frustrating for all of us in the delivery field. We actually want customers’ mail to succeed. We tell customers no, not because we want to ruin their day or their business or their ideas, but because we want to help their business. Our job is to make their email work, and sometimes that means saying no.
Next time your delivery consultant, or your ESP delivery expert, tells you that an idea may cause delivery problems, give them some credit for their experience and expertise. We really do have your best interests at heart and really do want your email to succeed.

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Delivery lore

Number of people believing outrageous statements on the Internet
(Image from Bad Astronomy)
Almost every delivery consultant, delivery expert or deliverability blog offers their secrets to understanding spam filters. As a reader, though, how do you know if the author knows what they’re talking about? For instance, on one of the major delivery blogs had an article today saying that emails with a specific subject line will not get past spam filters.
This type of statement is nothing new. The lore around spam filters and what they do and do not do permeates our industry. Most of the has achieved the status of urban legend, and yet is still repeated as gospel. Proof? I sent an email with the subject line quoted in the above blog post to my aol, yahoo, gmail and hotmail accounts. Within 3 minutes of sending the email it was in the inbox of all 4 accounts
I can come up with any number of reasons why the email ended up in my inbox, rather than being caught by spam filters as the delivery expert originally claimed. But none of those reasons really matter. The expert in question is spreading delivery lore that is demonstrably false. Emails with that subject line will get through spam filters. I even added an extra 4 exclamation points in the subject line.
Not all delivery lore is true. In fact, most lore involving “always” “all” “never” or “none” is not going to be true. Just because you read it on the internet, and because it came from someone claiming to know what they’re talking about does not absolve individual senders from critically thinking about the information.

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Who is Julia and why won't she leave me alone?

There seems to be some new spam software in use. Julia <random last name> keeps telling me about her new webcam, how much she wants to date me and wants to know when I want to visit. These spams started February 1. I’ve had 179 caught by my MUA filters, and 152 caught by spamassassin (SA score >7 are filtered to a special account).
This is exactly the type of pattern that causes people to write filters that years later people look at and ask why someone thought this was a reasonable marker for spam.
The good folks over at MailChimp have examined some of the scoring rules that their clients trigger. They found some “Julia” type markers. Some oddities they reported on:

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