Imagine this scenario: you just ran your first few A/B tests and taken action based on the results. The primary call-to-action button on your homepage is now orange instead of gray. Extra steps in your checkout funnel have been removed to reduce friction. You are wondering: where does the next great idea come from? Maybe you have several ideas; which do you choose?
There is a good chance these questions sound familiar to you, even if you are part of a mature experimentation program. Many teams, no matter the size, face a shared set of challenges when it comes to building an impactful, data-driven practice. These challenges include how to research, ideate, plan, develop and interpret the results of tests and campaigns to maximize impact.
Optimizely Experimentation enables you to experiment with and personalize your website. Below, we offer a series of articles to guide you through the strategy and practice of running an experimentation program.
There are five major stages in the Optimization Methodology:
Your team works through each of these stages, from ideation to production, with every experiment you run. This iterative cycle helps your testing organization continually learn from and improve your site experience, to drive business goals.
The articles below help you plan more effectively through each stage. So, when you analyze results in production (stage 5), you can monitor how improvement in one test affects other valuable revenue sources on your site—because you set up monitoring goals in design (stage 3). Or, you can turn interesting data in your results into the next great idea you will test (stage 2).
In this series, you will find:
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Strategic recommendations for building a powerful, sustainable program
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Actionable templates to help you jump right into prioritizing, designing, and sharing your experiment and campaigns
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Resources to help new teams and more mature testing organizations build a strong, data-driven culture
Optimizely's Program Management feature helps your team scale an experimentation program across an enterprise and gain program-level reporting. It is available on select plans.
Learn the experimentation strategy, like deciding what to test and how to prioritize, in our free, interactive training sessions.
Implement Optimizely Experimentation and establish your experimentation program
First, establish an optimization framework that prepares your team for long-term success. You will complete this phase once and revise only based on significant program or company-level changes. But you will consult the resources often to orient your efforts. Tackle these steps early.
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Improve metrics that matter with your experimentation program
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Boost your program with an Optimizely Experimentation Solutions Partner
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Implementation checklists for Optimizely Web Experimentation: Basic | Advanced
Decide what to test
Once you set the direction for your program, it is time to research and brainstorm ideas for testing and personalization.
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Use a business intelligence report to ask the right questions
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Generate ideas for experimentation based on data: Direct data | Indirect data
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Generate ideas based on analytics reporting: Basic | Advanced
Organize your experiments
Next, you will prioritize, plan, and design individual tests.
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Prioritize your experiment ideas: Basic prioritizing | Advanced roadmap
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Use minimum detectable effect to decide what type of test to run
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Create an experiment plan: Basic template | Advanced template and QA checklist
Build and run your experiment
Create your experiment in Optimizely Web Experimentation. Before you publish it live to the world, QA to ensure it is set up the way you want. Then, launch it!
Analyze and take action on your results
Analyze your results and take action based on what you find. Use the insights you generated from winning, losing, and inconclusive tests to design the next round of tests and campaigns.
Every optimization team is different. As your program grows, the iterative cycle from ideation to production will help you adapt your process to meet the changing needs of your testing organization.
Subscribe to the Optimizely Experimentation Blog for more tips from experts in the field. Happy testing!