How to Get Your Web Marketing E-Mails Past Content Filters - dummies

How to Get Your Web Marketing E-Mails Past Content Filters

By John Arnold, Michael Becker, Marty Dickinson, Ian Lurie, Elizabeth Marsten

Web marketers need to be aware of content filters when preparing their e-mails for distribution. The majority of e-mail filters are included within e-mail programs and written with broad consumer preferences in mind to filter e-mail content that has spam-like characteristics. E-mail filters within e-mail programs almost always allow the user to access the default filter settings and alter them according to user preferences.

Filters often look for spam-like content, so avoid simulating spammer techniques. Recent examples include

  • Generic Subject lines and anonymous From lines

  • PDF attachments containing advertisements

  • Images of entire advertisements without any plain text

  • Excessive promotional phrases and words

Most consumers don’t alter their default e-mail filter settings manually, so avoiding false positive filtering by the most common e-mail filters is partly a matter of building your e-mails to exclude the most commonly filtered content. Below is shown a sample of the headers in a junk e-mail folder.


Read some of the e-mails in your own junk folder to see examples of what to avoid: namely, the most common types of content that spammers include in their e-mails.

You can prevent your e-mails from looking like spam if you do the following:

  • Don’t include your subscriber’s first name in the Subject line of your e-mails. The practice is common among spammers because most consumers can’t understand how a complete stranger could know their first name. (Spammers use web crawler programs to pull the information out of your e-mail headers.) After being tricked a few times, most consumers associate this technique with spam.

  • Always include a From line in your e-mail header. Excluding the From line is an attempt by spammers to trick people into opening e-mails in the hope that the consumers are curious to find out who the e-mail is from. Most filters automatically identify e-mails with no From line as untrustworthy.

  • Avoid excessive punctuation (such as strings of exclamation points!!!!!) and “crafty” symbols (such as ¢ents or dollar $ign$). Spammers often use strings of punctuation to make their offers more eye-catching, and the practice is just as attention-catching to e-mail filters.

  • Don’t send marketing e-mails with attachments. Consumers are understandably nervous about e-mail with unfamiliar attachments, and e-mails sent to more than a few people with attachments are usually filtered.

  • DON’T WRITE SENTENCES IN ALL CAPITAL LETTERS. Writing in all capital letters draws attention to e-mail headlines, and this tack is as annoying to consumers as it is noticeable to e-mail filters.

Building your e-mail content with the most common filter settings gets more of your e-mail delivered to the inbox, but several types of user-controlled filters aren’t so simple to sidestep.

Individual filters

A small percentage of consumers do access their filter settings to make changes. Here we show some of the individual filter settings available in Yahoo! Mail.


If someone on your e-mail list accesses his personal filter settings to set up a filter, your e-mail content is obviously subject to being filtered based on the personal settings for that user. Because you can’t know every personal setting in an individual filter, you can do little to get your e-mail through. Accessing filter settings allows the user to personally filter one or more of the following e-mails:

  • From specific senders

  • Containing specific words or phrases

  • With links or images (usually converted to plain text only)

  • From senders not in the user’s address book

  • With certain domain extensions, such as .biz or .info

  • With certain types of encoding, such as international languages

  • With attachments

Trained content filters

Some filters begin with broad default settings and are automatically updated based on whether the user identifies certain e-mails as unwanted. The most common example is the Spam button, which is a clickable link in an e-mail program that reports the e-mail as spam to the e-mail system administrator.

Clicking a Spam button not only reports an e-mail as unwanted but also scans the content to identify content that recurs frequently in the reported e-mails.

When a user clicks a Spam button, a filter scans the e-mail to look for words, phrases, and other types of content to determine whether there is a pattern to the types of content being reported as spam by the user.

For example, if a user continues to click the Spam button on multiple e-mails containing the phrase discount meds, the filter begins to learn that phrase and automatically filters any e-mails containing that phrase to a junk folder.

Trained content filters work fairly well, but a filter can’t distinguish between wanted words and unwanted words in an e-mail that is marked as spam. Because spam e-mails share many common characteristics with legitimate e-mails — such as the phrase Click Here — some legitimate e-mails are identified as false positives.