{"id":2282,"date":"2016-11-14T18:18:39","date_gmt":"2016-11-14T18:18:39","guid":{"rendered":"https:\/\/mailinglistservices.com\/?p=2282"},"modified":"2023-04-18T20:25:48","modified_gmt":"2023-04-19T00:25:48","slug":"did-your-customer-pass-the-a-b-test","status":"publish","type":"post","link":"https:\/\/dundee.net\/index.php\/did-your-customer-pass-the-a-b-test\/","title":{"rendered":"Did Your Customer Pass The A B test?"},"content":{"rendered":"\t\t
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Did Your Customer Pass The A B test?<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Whether you run a business, organization or nonprofit, you all flourish with repeat customers. \u00a0We all know email campaigns<\/a> are the best cost-effective way to cultivate your list members into repeat customers while attracting new ones.\u00a0 Do you believe you are getting the most out of your mailings? \u00a0Are you satisfied with the outcome of your campaigns? Do you always have an increase in ROI, conversions or a higher subscriber rate, because you test your emails, or are you one of the many senders that don\u2019t test, and just hope that the results will be better every time you mail?<\/p>

AB Test<\/p>

For those who take a back seat to testing, it\u2019s been shown, list owners who employ email A\/B testing hit their goals more times than those who don\u2019t.<\/p>

A\/B \u00a0testing is easy<\/a>, the hardest part may be deciding what to test; \u00a0So how do you decide what to test? \u00a0How do you measure the results and how much trial and error should you expect: because you cannot test everything at once if you expect to obtain accurate test results.<\/p>

To start, A\/B testing is a method of comparing different versions of the parts of an email against each other to determine which one performs better.\u00a0 A hypothesis can be generated based on how you could improve your campaigns, set up your test and send it out.\u00a0 In theory, this testing method gives the user solid evidence of what performs well and what does not.\u00a0 Through testing, you can get a clear idea of your customer\u2019s preferences, which will help you create the type of email they will read and act on.<\/p>

Decide what to test:<\/h3>
  1. Subject Line<\/li>
  2. Hyperlinks<\/li>
  3. Images<\/li>
  4. Type of Personalization<\/li>
  5. Colors<\/li>
  6. Content<\/li>
  7. Call-to-Action<\/li>
  8. Downloads<\/li>
  9. Length of email<\/li>
  10. Landing page<\/li>
  11. Fonts<\/li>
  12. The time you send out your email<\/li><\/ol>

    Each and every item on this sample list is likely to have a different consequence on your conversion process.\u00a0 Change your \u00a0Subject Line to test different open rates, \u00a0\u2013 If you\u2019re testing for advertiser click-throughs you might change the position of advertiser links within your email and so on.<\/p>

    When you decide if you are testing for advertiser clicks\u00a0or opens, test what you consider important first. If more opens are a concern to you, testing the Subject Line might be number one on your list.<\/p>

    Decide who to test<\/h3>

    Should you test your entire list by splitting it in half or segment<\/a> your list into smaller groups. If you segment into smaller members, select random email addresses unless you\u2019re testing something in the demographics area, like people in a particular zip code or women only. You never want to individually select an email address to place in a segment when you are doing\u00a0A\/B testing as using hand-picked selected email will distort the results.<\/p>

    Segments work well when you are testing for conversions based on a time limit, such as a sale. You can test what you need to with a few hundred recipients, use the best response to your tested email and then send to your entire list.<\/p>

    Success?<\/h3>

    After you decide what to test for and who to test, the results may not be what you expect. Statistics from previous campaigns using the same format, where you made subtle changes when testing, will be most helpful when you measure success. Success, however, depends on what your testing goal is: more opens, call to actions, increased conversions\u2026.etc.<\/p>

    Don\u2019t Make it Hard On Yourself<\/h3>

    Dundee hosted ListManager has built-in tools for A\/B testing<\/a>. There are\u00a0no limits to the tests you can run concurrently and\u00a0the test(s) are free.\u00a0 Most ESPs offer some type of built-in A\/B test. Having a built-in A\/B test sections as part of your hosting platform is easier to deal with than setting up a manual A\/B test, but it can be\u00a0done.<\/p>

    Analyze the Results<\/h3>

    What the numbers tell you depends, again, on what you decided to test. For example, if your goal is to increase visitors to your website and conversions, you may find that while 10% of your segment B clicked on the link that got them to your landing page, \u00a0only 15% went deeper and purchased.\u00a0 Your second test resulted in a 25% increase in clicks, \u00a0but\u00a0once the subscriber reached the website, they left; logically the second test should have resulted in more conversions, but in this case, it doesn\u2019t.<\/p>

    Why didn\u2019t the numbers work, because email and landing pages go hand-n-hand.\u00a0 Those \u00a025% clicks in the second segment test, to be successful should have taken the visitor to the Call- To -Action your test email prompted. \u00a0The subscribers, expected, for example, the clickable link to take them to a Lawnmowers Close Out Sales as described in your email, not take them to your home page where they had to search for the sale.<\/p>

    Best Practices<\/h3>

    Here are a few best practices to keep in mind when running an email A\/B test:<\/p>