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Retargeting Emails - Do E-commerce customers like or loathe them? March 10th, 2011Leave a commentGo to comments By Charles Nicolls, SeeWhy At SeeWhy, when we first launched our remarketing service in 2009, Randy Stross wrote a piece about email remarketing in The New York Times suggesting that while remarketing might be a great idea for ecommerce websites, it's not a great idea for consumers. He likened emails following up on abandoned shopping carts to a salesman chasing you down the street if you didn't buy from his store. There are major differences, of course. We've long argued that remarketing emails, when done well, not only drive conversions but also build brand trust. They can deliver great service and provide customers with the confidence to return to buy-either online, by phone or in store. If Randy was right and customers universally resented the intrusion, then these emails wouldn't work. In aiming to answer the question more substantively, I turned to data, and specifically email marketing benchmarks. The key metrics to look at to determine whether customers like or loathe remarketing emails are: the recovery rate the open rate the clickthrough rate the unsubscribe rate Frankly, the evidence is overwhelming: Remarketing, when done well, is appreciated by customers. Here's the evidence: (1) The recovery rate The recovery rate is the percentage of visitors that abandon shopping carts, and remarketed visitors thatthen return and purchase following remarketing. At SeeWhy, we measure recovery rates across all our customers, and currently the average is 20 percent. So, one in five shopping cart abandoners come back and buy, having being remarketed. In some cases, the recovery rate is as high as 50 percent. Moreover, when remarketed customers buy, they spend on average 55 percent more than customers who didn't abandon their shopping carts. (2) The open rate The average email open rate for remarketing emails is currently 46 percent, m

What Seth calls a "Use Case" we call Personas in the world of conversion. Otherwise the benefits are the same: understanding your most important visitors, ending bad relationships with poor customers, and getting everyone on the same page.

Great case study on using Facebook to test ads and landing pages.

Peep Laja @peeplaja has put together a great list of ways to increase conversion rate. The remarkable thing about this list is that he provides a case study for each of his recommendations, proof that these ideas have works somewhere. This lets you understand the circumstances that drove the improvements in conversion and help you choose the tactics you will use on your site. Thanks, Peep.

 @unbounce Here is some data that we are seeing elsewhere, in which video increases conversion rates. The universal appeal of video is quite surprising -- and powerful.

So, should you use a carousel, those rotating hero images now found at the top of most B2B and B2C websites?

The answer is "carefully."

This clever little site illustrates the reasons rotating banners are so frustrating. The timing, the amount of text and the order all come into play.

We have been able to tune a rotating hero on an ecommerce site so that it outperformed a static image. But it took several test cycles and didn't work in every case.

Have a little chuckle at yourself and enjoy the content on this site -- if you can read fast.

@yaost offers some good advice in this article. In particular, there are some testing "elephants in the room" that he points out. These include the fact that the Z score used by testing tools assumes a normal distribution -- a bell curve -- in the data. That is often not the case.

He also recommends ending tests on week boundaries. If you start a test on Friday and end it on a Tuesday, you may be exaggerating your results as Tuesdays are often bigger conversion days for ecommerce sites.

This article is just nerdy enough for most marketers, and you're going to have to add some nerdy to your repertoire if you're not already there.

Great case is made for using email to increase conversions of those who leave your site.

The steps we take as conversion optimizers look suspiciously like designers. Each of theses steps can use more data, though:User PersonasJob StoriesUsability TestingAffinity Mapping2x2 AnalysisProblem DefinitionIdeate & CreateMockupsPrototypeValidateOur task is to execute on this with high frequency and make small changes as we go to learn what moves the needle.