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Hypothesis Generation

One of the first steps in A/B testing is coming up with hypothesis for items to test on your site or mobile app. Learn about hypothesis generation best practices from the Optimizely teams and top companies from around the world.

Conversion Rate Optimization Best Practice: Ignore Best Practices

Conversion Rate Optimization Best Practice: Ignore Best Practices

Why do marketers insist on looking for “best practices” and “conversion optimization tips” that simply don’t work? Conversion rate optimization (CRO) is context-specific which is why not adhering to specific conversion rate optimization best practices is a best practice.

A structured process is your best chance at getting valid results you can use to build your internal team and take your marketing efforts to the next level.

How to Run More Effective A/B Tests: An Optichat Recap

How to Run More Effective A/B Tests: An Optichat Recap

Good ideas are the foundation of our work as optimizers. The source doesn’t matter — whether it comes from our heads, a user testing session or our website analytics — as much as the quality. Instead of one-off ideas, we need to equip ourselves with scalable strategies for brainstorming effective A/B tests. Hiten Shah, founder CrazyEgg, co-founder of KISSMetrics joined #optichat to discuss tactics for running effective A/B tests.

Here’s a recap of the questions, answers from Hiten and the #optichat community.

Apply Emotions and Learn More from Your A/B Tests

Apply Emotions and Learn More from Your A/B Tests

A large opportunity for improvement exists in the realm of optimization. Most marketers optimize their websites and campaigns on pure intuition alone.

A/B testing can be so much more. It can help us tap into our customer’s emotional needs, goals and help us build a better customer journey. To do this you have to test differently. Instead of testing elements, you need to start testing concepts using behavioural and emotional methodologies.

Creating Excellent Hypotheses with Website Analytics and User Research

Creating Excellent Hypotheses with Website Analytics and User Research

For an optimization team to be successful in reaching an aggressive revenue goal, both quantity and quality of experiments must be high. To support a focus on testing velocity, a strong backlog of experiment ideas is essential.

In this third installment of our spotlight on the optimization team at Move. Inc (the operator of realtor.com), we look at a couple of the thoroughly vetted experiment ideas that the team has tested.

How to Write a Solid A/B Test Hypothesis

How to Write a Solid A/B Test Hypothesis

Imagine you set out on a road trip. You packed the car, made a playlist, and set out to drive 600 miles—but you don’t actually know where you’re headed. When you arrive at a destination, and it’s not at all what you imagined it would be.

Running an experiment without a hypothesis is like starting a road trip just for the sake of driving, without thinking about where you’re headed and why. You’ll inevitably end up somewhere, but there’s a chance you might not have gained anything from the experience.

In this post, we’ll show you how to craft great hypotheses, how they fit into your experiment planning, and what differentiates a strong hypothesis from a weak one.

How to Use Data to Choose Your Next A/B Test

How to Use Data to Choose Your Next A/B Test

Your optimization strategy is an exercise in rigorous prioritization. When your most valuable resource is time, it is essential that your experiments run on high-priority pages and generate a measurable effect. Learn how to estimate test impact, leverage your website analytics, and develop a robust testing strategy with data that will let you you make the most of your limited time.

Qualitative Questions That Lead to Great A/B Tests

Qualitative Questions That Lead to Great A/B Tests

You’ve asked everyone in your company. You’ve looked to your competitors. You talk about it with your friends at happy hour. You’re trying to come up with ideas for your next big A/B testing win. Pulling qualitative feedback is the next best place to look. If you’re not getting qualitative with your data to understand your visitors better, then you’re missing out on one of the biggest pieces of learning.