Creating a relevant e-mail experience from click to conversion

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Carolyn Gardner
Carolyn Gardner

As e-mail marketers, you assume subscribers will only spend a few seconds reading your e-mails — at which point they decide to keep reading, move on to the next e-mail or delete. In order to make sure as many subscribers as possible opt to keep reading, you work at making your e-mails more meaningful, more personal and ultimately, more relevant. The most effective e-mail programs usually include subscriber preference centers, segmentation strategies and dynamic content — all great tactics to improve the effectiveness of e-mail, but is it helping with conversion?

A conversion point rarely lives in an e-mail. It's off on a landing page, or a few clicks into your site. So while your e-mail messages may be relevant, the time from click to conversion can be a critical danger zone. Web personalization — the act of dynamically customizing a Web page based on user attributes such as geo-location, depth of visit, time on site, or language — can make the after-click experience more relevant. It's the perfect partner for e-mail marketing.

Web personalization has been around for years, but is only starting to get traction. Although, according to an August 2007 Aberdeen Group study, only 17% of companies are using personalization, the Web Analytics Association declared personalization on the Web as one of the hottest areas of growth for the analytics industry in 2007.

Already, marketers have started to look past e-mail marketing metrics and are aligning those metrics with their Web analytics. Personalization is going a step further and taking action on those analytics. Based on what's happening from the click through, a marketer can identify underperforming segments and build a personalization strategy to increase conversion rates within these segments. By combining anonymous analytical information with data from your preference center and past purchasing behavior, you're equipped with everything needed for a truly relevant experience.

Take, for example, a retailer who sends out weekly promotionally based messages to its subscriber base. It targets based on past purchase behaviors, and sends out a promotion about product A, which complements product B, which this segment all purchased within the last month. Some recipients click through the e-mail, but don't buy product B, instead clicking around several times. Based on analysis of analytics, the retailer knows people following this click path ultimately purchase product B or C. Since we know they already have product B, they see messaging about special savings for e-mail subscribers on product C. Based solely on the e-mail data, the retailer never would have drawn this conclusion.

Now the e-mail leads subscribers to your Web site and dynamic personalization drives them to the conversion point. You're happy because you're converting more, meaning more money in your pocket. Your subscribers are happy because you are giving them exactly what they want and making the journey to conversion easy and accessible. It's a win-win.

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