How can you optimize mobile devices for CRO experiments?

2 Segment your mobile audience

Not all mobile users are the same, and they may have different preferences, behaviors, and needs. Therefore, you need to segment your mobile audience based on relevant criteria, such as device type, operating system, browser, location, demographics, psychographics, or previous actions. Segmenting your mobile audience will help you target your experiments to the most relevant and profitable groups, as well as avoid potential conflicts or biases.

3 Choose your mobile tools

To run effective and reliable CRO experiments on mobile devices, you need to choose the right tools that can handle the technical and analytical aspects of your testing. For example, you need a mobile-friendly testing platform that can create and deploy variations, track and measure performance, and report and analyze data. You also need a mobile-responsive website or app that can adapt to different screen sizes, orientations, and resolutions. Additionally, you may need other tools, such as heatmaps, surveys, or user testing, to gain more insights into your mobile users' behavior and feedback.

4 Create your mobile hypotheses

Based on your mobile goals, audience segments, and tools, you can create your mobile hypotheses, which are the core of your CRO experiments. A hypothesis is a statement that predicts how a change in your website or app will affect a specific metric or outcome. For example, a hypothesis could be: "Adding a sticky call-to-action button on the product page will increase the mobile conversion rate by 10%." To create a valid and testable hypothesis, you need to base it on data, research, and best practices, as well as make it specific, measurable, achievable, realistic, and time-bound.

5 Run your mobile experiments

Once you have your mobile hypotheses, you can run your mobile experiments, which are the methods of testing your hypotheses against a control version of your website or app. Experiments can include A/B testing, multivariate testing, or split testing, depending on the number and complexity of variables. To ensure successful experiments, it’s important to follow best practices such as testing one variable at a time, testing both qualitative and quantitative metrics, and testing for a sufficient sample size and duration. Additionally, be sure to test for statistical significance and confidence, as well as external factors and sources of error.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?