The Most Important E-Mail Marketing Tactic of All

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Column by Bill Nussey

The Most Important E-Mail Marketing Tactic of All

E-mail is well-regarded in the marketing world for its low cost, ease of use and exceptional measurability. But e-mail marketing also possesses another, often-overlooked strength. If you know how, e-mail makes it easier to ensure your campaigns are successful and well received nearly every time.

What's the secret? Testing.

Although marketers who test clearly achieve better results than their counterparts who don't, only about 40% undertake this surprisingly easy and simple tactic, according to a JupiterResearch survey of more than 600 e-mail marketers. In its January 2005 report, "Effective E-mail Marketing," JupiterResearch found that marketers using testing were almost twice as likely to attain conversion rates of 3% or better. They also achieved a 68% improvement in return over non-testers.

So why aren't more marketers doing it? Lack of awareness and lack of resources are most often cited. But if I told you that experimenting with your e-mail landing page -- the page recipients go to when they click a link in your e-mail -- could boost your return by 40%, wouldn't that be worth looking into? According to MarketingSherpa's "Landing Page Handbook," marketers who test and tweak their landing pages consistently achieve such marked improvements.

What can you test?

The types of testing e-mail marketers find most worthwhile, according to MarketingSherpa's 2003 "E-mail Metrics Survey" of more than 2,000 e-mail marketers include:

Landing pages, 74 %
Subject lines, 74 %
HTML vs. text, 70 %
Personalization with name, 63 %
Long vs. short copy, 31 %

You can also test your offer, design, time of day, message layout, day of week and duration before follow-up. Do recipients prefer a 30% discount, or a $20 discount? Do some recipients who don't open HTML e-mails open their text versions? Do they respond to a catchy subject line, or a straightforward promotion? No other medium makes it as easy to test and act on those tests as e-mail marketing.

So, if this testing thing sounds interesting, how do you do it?

Split your list. Divide your list into two or more groups (sometimes called an A/B split) and change one characteristic (e.g., subject line) for each group. Assuming that you divide your groups randomly so that each represents an accurate cross-section of your overall recipient base, and everything else about your message remains the same, your results should clearly reveal the best-performing characteristic.

Or, you can test to a subset of your list. Think of it as an e-mail dress rehearsal. Using a technique called nth-testing, you pull every nth record from your list to create a near-random set of subgroups. For example, if you have 1,000 names, and you nth on every 10, each of those 1,000 names is assigned a value of 0, 1, 2, 3, 4, 5, 6, 7, 8 or 9. If you wanted to create two random "test" segments, you would send one offer to segment 0 and another to segment 1. You would then send the best-performing offer to segments 2 through 9.

Conduct tests at the same time. Time is a variable, and sending test e-mail A in the morning and test e-mail B in the afternoon can yield very different responses. So send tests out as near to the same time, same day as possible.

Make sure the results are statistically relevant. One or two responses are not enough to tell you whether one test succeeded over another. While purists may argue the exact number, you should try to get at least 50 to 100 responses for each test before you can make broad judgments about which performed best. So, if you are nthing, be sure to segment off a large enough chunk of your overall list. You can arrive at number of recipients you'll need by using your average click-through rate. If you have a list of 10,000 recipients, and your average click-through rate is 5%, then you could expect to receive 500 responses. So to get 50 responses, one-tenth of that total, you'll need to test one-tenth of your list, or 1,000 recipients. To get 100 responses, you'll need to test one-fifth of your list, or 2,000 recipients.

To figure out how well your test performed, compare the click-through rate of your test group to your average click-through rate, and to the other version to see which did best, or which you will send to the rest of your list. A rule of thumb recommended by some (ClickZExperts "A/B Testing for the Mathematically Disinclined") is that you should have at least a three times larger result in order to be able to declare a clear winner.

Maintain a control group. A control group is a random sample of your list that is excluded from the change you are testing. This enables you to compare the behavior of the test group vs. the control group to determine the precise effect of your change. This might be the group that gets your usual subject line A, against which you are testing subject line B. Or, a great example is frequency testing. If you want to find out whether sending more frequently would be more profitable over the long-term, or whether it would wear down recipients with too many messages, you can compare the response of your test vs. control group over a period of months to get your answer.

The options I've outlined barely scratch the surface of all the e-mail testing possibilities available. Understanding campaign responses and their implications for future customer behavior can get into incredibly complex statistics, analytics and modeling. Fortunately, those of us without a Ph.D. can still use the basic testing methods to significantly enrich our ongoing customer relationships. The real power of e-mail isn't how easily and quickly you can send it, but how easily and quickly you can figure out what appeals to your recipients, tailor your offers accordingly and keep them coming back for more.

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