BULK EMAIL SYSTEM
Testing: The ability to test variables is one of the greatest benefits of email marketing. It is also an activity that is rarely deployed. If you can muster the energy, we recommend testing at least one variable in each email campaign or newsletter issue (assuming one or two distributions per month). Test variables can be design/format changes, subject line elements, time of day/day of week, use and style of graphics, copy style, amount of copy, offers and more. Of course, don't just test for testing sake. Testing should form a key foundation of your overall improvement program and help move you forward toward your end goal. The simplest approach to testing is to split your list into two random but equal groups ("A/B splits") and test one new variable against an existing constant.
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Domain/AOL Segmentation: If a sizable percentage (say 5%+) of your recipients are AOL users, you should clearly develop separate versions of your email for these increasingly challenging subscribers. At minimum we recommend subject lines that include your company or newsletter name, one that is shorter in length (see Subject and From Line Tool) and often more conservative in nature. Secondly, you should definitely develop and test both plain text and Rich Text Format (RTF) versions of your newsletter - and monitor which versions (HTML, Text, RTF) pull best with your recipients. Better yet, offer these AOL subscribers a choice of which version they would prefer. Also see Dealing With Domains: Quick Tips on Improving Your Email Performance.
Profile/Demographic Segmentation: If you have more information than name and email address on your customers and email subscribers, why not use it? If you haven't collected information, perhaps this is the key ingredient currently missing from your program. For example, if you are an online retailer of bicycle apparel, parts and accessories, capturing demographic information such as sex, age and biking preference (road, mountain or both) would enable you to conduct fairly targeted campaigns. Using this data you could develop customer profile segments (i.e., males over 40 who ride mountain bikes) who then receive emails with specific products, offers and messaging that appeals to this demographic profile group.