The Optimization Methodology

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  • Optimizely Web Experimentation
  • Optimizely Web Personalization
  • Optimizely Performance Edge
  • Optimizely Feature Experimentation
  • Optimizely Full Stack (Legacy)
This is the introductory article on The Optimization Methodology. See the links in this article to view the rest of the Optimization Methodology.

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 and applications. 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:

Implementation, ideation, planning, development, analysis

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:

  • Strategic recommendations for building a powerful, sustainable program.

  • Actionable templates to help you jump right into prioritizing, designing, and sharing your experiment and campaigns.

  • 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.

Stage 1 – 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.

Stage 2 – Decide what to test

Once you set the direction for your program, it is time to research and brainstorm ideas for testing and personalization.

Stage 4 – Build and run your experiment

Create your experiment in Optimizely Web Experimentation, Optimizely Performance Edge, or Optimizely Feature Experimentation. Before you publish it live to the world, QA to ensure it is set up the way you want. Then, launch it!

Stage 5 – 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!