Using Optimizely

How to Wisely A/B Test WordPress Headlines With Optimizely

Wordpress Headline A/B Testing

Love it or hate it, headline testing has proven to be a necessary tool for media sites to use in order to stay competitive in the quest for clicks. Testing every headline is a great way to increase clicks, engagements, and social shares and create a culture of testing and experimentation needed to survive in this fast-paced digital world.

In this post, we walk through how publishers running their sites on WordPress can experiment with headlines using the Optimizely A/B Testing Plugin for WordPress.

Targeting Your Test to Specific URLs — In 1 Minute


one minute mondays

One of the most important parts of setting up an experiment is deciding where you want it to run, as in which pages specifically are you deciding to target. You can be as narrow as a single URL or as broad as your entire site. It all depends on which of the four URL match types you use. In this One Minute Monday, we’ll cover what these match types mean and why they’re important for you.

Stats with Cats: 21 Terms Experimenters Need to Know


Stats cat

Statistics are the underpinning of our experiment results—they help us make an educated decision on a test result with incomplete data. In order to run statistically sound A/B tests, it’s essential to invest in an understanding of these key concepts.

Use this index of terms as a primer for future reading on statistics, and keep this glossary handy for your next deep dive into experiment results with your team. No prior knowledge of statistics needed.

Statistics for the Internet Age: The Story Behind Optimizely’s New Stats Engine


Optimizely Stats Engine

Classical statistical techniques, like the t-test, are the bedrock of the optimization industry, helping companies make data-driven decisions. As online experimentation has exploded, it’s now clear that these traditional statistical methods are not the right fit for digital data: Applying classical statistics to A/B testing can lead to error rates that are much higher than most experimenters expect. We’ve concluded that it’s time statistics, not customers, change.

Working with a team of Stanford statisticians, we developed Stats Engine, a new statistical framework for A/B testing. We’re excited to announce that starting January 21st, 2015, it powers results for all Optimizely customers.

This blog post is a long one, because we want to be fully transparent about why we’re making these changes, what the changes actually are, and what this means for A/B testing at large.

Introducing Audiences: A New Way to Deliver Personalized Experiences

audiences-feature

75% of US customers appreciate when companies customize messaging and offers to them, but most companies struggle to achieve this in the digital space.

In a world where your customers interact with you every day at multiple touch points across multiple channels, Audiences make it even easier for you to optimize and deliver them personalized experiences.

Introducing a Faster, More Powerful Optimizely Results Page

cdn-balancing

Today we’re excited to announce that Optimizely’s new results page is available to all customers.

The results page is Optimizely’s #1 most viewed page, so rebuilding it was no small task. We ran multiple rounds of user research and conducted an extended opt-in beta with more than 6,000 users.

In this post, we walk through the features of the brand new experiment results page.