Trips, falls, and head-on collisions. These days, a quick stroll down the street is an accident waiting to happen. It’s easy to point fingers at uneven pavement, crazed skateboarders, or fanny-packed tourists, but the truth of the matter is clear: smartphones are the culprit. Young, old, commuter, tourist, sometimes even bikers (yikes!) – everyone is face down, glued to their mobile device. While the act of walking-and-browsing can be aggravating, it speaks to a very important truth: mobile web is pervasive. Improving your mobile website will not only help prevent sidewalk catastrophes, it will also help create an optimized experience that generates more clickthroughs, revenue, and conversions.
Here’s where mobile testing comes in.
Mobile versions of target.com, reddit.com and taskrabbit.com.
Not all types of visitors respond to web content in the same way. For example, visitors coming from an email campaign may react to a landing page differently than visitors coming from a paid search ad; mobile visitors may react to a homepage differently than non-mobile visitors. Understanding the difference between these behaviors is the first step towards delivering an optimal experience specifically tailored to each visitor type.
We’re excited to announce a powerful new feature called visitor segmentation that enables Optimizely customers to view test results for specific visitor segments to understand how those types of visitors reacted to each variation.
Welcome back to Conversion Rate Optimism, Jeff Blettner, a web designer and conversion optimization specialist at Formstack. Having just completed a complete redesign of formstack.com, Jeff spoke with me about the role AB testing tools played in the process.
Optimizely: How big of a role did A/B testing – actually doing it, or knowing you were going to do it – play in this redesign for Formstack?
Jeff: Very large role. Everyone has an opinion on what a website should say or include, and sometimes those strong opinions lead to disagreements in planning or design. When we reached those spots, resolution was a lot easier when we knew that post-launch, we could A/B test our different hypotheses to see what is the better approach.