Hitmetrix - User behavior analytics & recording

Earn higher conversions using an A/B split

Consider this situation: You run the marketing department for an e-commerce outdoor outfitter, and your team has decided on a subject line and special offer for your next campaign. The variable you’re trying to settle is whether the main graphic should be a product photo or one of the company president announcing the offer. This is the perfect time to employ an A/B split to find out which works better.

Creating campaign A
First create the e-mail using product shots — in this case, one that includes an array of men’s and women’s shoes. Then, create a landing page that reiterates the president’s sale coupon offer, in addition to using the same product imagery.

This will be your ‘A’ campaign.

Creating campaign B
In order to isolate how much impact the imagery has on the recipient’s actions, campaign ‘B’ will be an exact replica of ‘A,’ but in place of the shoes photo, use a photo of your president. The landing page includes the coupon offer and that same picture.

Randomize, send and analyze

Now it’s time to send out the e-mail. If your e-mail service provider offers you the option to randomly select half of your list, use it. If not, simply cut your list in half alphabetically or by order of the opt-in date, bearing in mind that the results will be slightly skewed because of these variables.

After you’ve sent the mail, look at your metrics. First, check your e-mail stats to determine if your click-through rates are better for either campaign. Then, use your Web analytics application to see how visitors from campaign A behaved differently from visitors from campaign B. And although you’ll want to concentrate on conversion rates, you can glean knowledge from other metrics, as well. How did the visitors’ average time on site differ? Did visitors from one campaign view a vastly different number of pages than visitors from the other? Contrasting and comparing how each campaign’s visitors behaved lets you draw conclusions about what worked and what didn’t.

Drawing conclusions
In our imaginary scenario, let’s assume that you found that campaign B (featuring the picture of the president) yielded 1.5 times better purchase conversion than campaign A, which featured product shots. Your customers showed you that seeing your company president made them feel more compelled to purchase.

A/B testing may be a bit more work on the front end of an e-mail campaign, but the information and insights you gain from it can make a huge difference in your click-through rates, as well as your conversion rates. So the next time your team can’t decide between two good ideas, split the difference and let your customers show you.

Michael Stebbin is CEO of MarketMotive. He can be reached at [email protected].

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