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A marketer's cheat sheet for web optimization

A marketer's cheat sheet for web optimization Kim Ann King

You think you have a great website, but do you? If you are not optimizing your site via A/B and multivariate testing and behavioral targeting, you are likely not making the most of your online presence. So where to start? This checklist will help you make sure you're not only optimizing the effectiveness of your site, but also better engaging your audience, which will help you achieve your online marketing goals.

Are you testing?

Common methods for running controlled experiments on websites range from simple A/B testing to sophisticated multivariate testing. In A/B testing, one or more new versions of a page or single site element compete against the original (control) version. For example, two new versions of a headline might compete against the original headline. Multivariate testing, on the other hand, is like running many A/B tests concurrently, where there are multiple elements being tested at the same time. It's important to understand that multivariate testing not only shows you which combination of elements generates more sales or pulls more leads, but also reveals which individual elements influence visitor behavior versus those that do not.

Are you targeting?

It has often been said that when you optimize for everyone, you optimize for no one. That's why it's important to target. While some segmentation is better than none at all, demographics tend to be weaker predictors of future behavior than more dynamic behavioral characteristics -- the real actions someone takes during a visit to your site. So when optimizing for a behavioral objective, such as "proceeded to checkout," you'll see more reliable results faster by focusing your testing on those visitors who are in the appropriate behavioral segments.

Are you optimizing for speed?

When it comes to website performance, there are many variables and one guaranteed constant -- visitors strongly dislike slow sites. Leading research shows that visitor behavior is directly related to the speed of the browsing experience, and that conversion rates and overall customer satisfaction are hindered by site sluggishness. Front-end optimization leverages multivariate testing and analysis, enabling companies to determine causal relationships between individual performance-enhancement techniques and end-user experience.

Are you optimizing for mobile?

Mobile optimization using A/B and multivariate testing has been proven to be one of the most effective and immediate methods to increase visitor engagement, mobile application adoption, and content consumption. Since many organizations have not yet allocated specific budget for their mobile initiatives, testing a subset of existing, highly-trafficked content on a targeted mobile audience can provide a low-cost and low-risk stepping stone towards building a case for making a deliberate investment in mobile optimization. Tests have proven that showing mobile users' content that is specifically tailored for mobile devices improves the user experience, makes the site stickier, and ultimately, increases conversion rates. With mobile targeting, web marketers and analysts are able to test, measure, and deliver the content, layout, and promotional offers that are most effective for each mobile device category.

The bottom line is this: By implementing an optimization program on your web and mobile sites, you will deliver a better experience to users, which in turn will help you meet and exceed your marketing goals in 2013.

Kim Ann King is chief marketing officer at SiteSpect.

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"Business man designed on a checklist box" image via Shutterstock.

Kim Ann King is an award-winning marketing executive and has been a B2B software marketer for more than nearly three decades. She currently serves as the Chief Marketing Officer of web and mobile optimization firm SiteSpect. Her first book,...

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to leave comments.

Commenter: Miglena Nedelcheva

2012, December 12

Re-considering the web optimization plan I had, due to this article, I found a mistake in it. "Optimize for everyone, you optimize for no one" is a good meaningful description of an useless optimization. Really find it difficult to make segmentation of $earch customers but at least now I have the idea about dynamic behavioral characteristics to think about. I haven't read about this idea before and I'm glad I found it.