Combining Multiple Testing Strategies

The best conversion rate optimizers use multiple testing strategies to maximize the conversions and learnings with their split tests. In this video, I will show you a few of the strategies we employed to optimize our home page.

A/B Testing is a dynamic process and the strategic approaches used should be dynamic as well. Knowing what strategies to use at what time is essential to maximizing impact.

In this video, you will learn several things to improve your testing efforts including:

  • The baseline strategy
  • The existence testing strategy
  • Multivariate testing as a strategy
  • Isolation as a strategy
  • Iteration as a strategy

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Case Study: Order Confirmation Page A/B Test

After a visitor has completed the main action you want them to take, what should you do with them at that point?

Once an order is complete you aren’t done with your visitors. They have a relationship with you and you have a relationship with them. Just because they have completed an order or signed up, that relationship still needs to be nurtured to encourage future opportunities.

This is a quick a/b testing case study of a test on the confirmation page. Our business question was about how much content we should show the visitor and what type of content would be most compelling to get a visitor to further engage.

In this video, you will learn several things to improve your testing efforts including:

  • How we created variations to offer different content
  • How we reduced some content to learn about the ideal amount of content
  • The things the test helped us learn and the gaps in our learning that needed follow up testing
  • A common principle that is applicable to most sites and businesses.

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Get more information at  https://www.testingtheory.com

Hypothesis Handicapped A/B Testing

Trying to optimize a digital experience while you are hypothesis handicapped is like trying to live with handcuffs on. This video talks about 4 symptoms of being hypothesis handicapped and 4 ways to be free of it.

Optimizers that handicap their hypothesis don’t get the gains they otherwise would with their testing because they limit the possibilities of things they try.

In this video, we will discuss the makeup of a hypothesis and you will learn what it means to be hypothesis handicapped. We will talk about the symptoms which include:
• Testing only what you think will work
• Testing a small set of alternatives that all “safely” revolved around your main concept
• Test results show exactly what you had hoped would win so you stop testing more options
• Not forming any follow-up questions or testing actions

At the end, I will also give you four self-evaluation questions to free yourself from being hypothesis handicapped.

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

5 Cultural Quagmires Stopping Your A/B Testing

In order to do successful experience optimization, you have to have the right culture of optimization. There are many things that influence a culture of successful A/B Testing and there are even more elements of your culture that hurt your split tests.

In this video, I will cover 5 things that company cultures tend to develop that can hurt your conversion rate optimization efforts.

In this video, you will learn about some of the cultural challenges companies face including:

  • Fear of change
  • Overuse of other research methods
  • Guessing without data
  • Relying on correlative data
  • The IT Beast

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Micro vs. Macro Conversions with A/B Testing

Which metric should you use to call a successful test winner, your macro conversion or the micro conversions? This is one of the most common questions I see. A/B testers need to understand which metrics they should use for evaluating test results.

This video will help you learn about choosing the best split testing metrics.

In this video, you will learn several things to improve your testing efforts including:

  • What a macro conversion is
  • What a micro conversion is
  • How to choose the best metrics for your testing programs
  • When to prioritize micro conversions first

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Monetizing A/B Test Results

Split test results that don’t show an annualized impact aren’t as good for a number of reasons. Get more buy-in for testing by annualizing your A/B testing results.

This video will help you learn a ton about foundational tests to jumpstart your split testing.

In this video, you will learn several things to improve your testing efforts including:

  • 4 benefits of monetizing your test results
  • 4 inputs into the annualizing formula
  • The exact annualized monetization formula I use on my test results

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Perfect Amount of Traffic Per Test Variation

How much traffic should you have per test? What about the ability to choose the percent of the audience per experience? How should you split the traffic among your different variations?

There is a perfect amount of traffic to include with each test and each tested variation.

In this video, you will learn about 4 strategic reasons for including more traffic in each test:

  • Segmentation implications
  • Statistical confidence implications
  • Population representation implications
  • Speed and timing of results implications

Testing Theory is where professional conversion rate optimizers turn to do better A/B testing and get more conversions.

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Multiple A/B Tests at Once

Have you wondered if you can run multiple A/B Tests at once? If you run more than one split test at once and do it correctly, running multiple tests can maximize your gains. If however, it is done incorrectly your testing program is put at risk.

This video will review the important considerations in making the decision to run multiple tests at once.

  • The strategy of running multiple tests at once
  • How location impacts the decision
  • How traffic levels impact the decision

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Get more information at  https://www.testingtheory.com

Creating Buy-In to Test – 7 Strategies

Do you feel like the organization you work with isn’t doing as much testing as you could? Are you looking for strategies on how to create buy-in for your testing program? I will share with you 7 ways to get the buy-in you need to do more split testing.

These are strategies that I have employed to take businesses doing no testing to making testing essential to the roadmap and planning of the business.

In this video, you will learn several things to improve your testing efforts including:

  1. Partner
  2. Teaching and training about A/B Testing
  3. Proactive split testing plans
  4. Evangelizing data and results
  5. Identifying multiple angles, departments, and people
  6. Using all your resources and finding allies
  7. Having patience

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

Data Science and A/B Testing

What is data science? What makes a good data scientist? What does A/B Testing have to do with data science? What is the hierarchy of needs for data science? Learn the answers to all these questions and more as we take a look at how optimization and learning with data is best accomplished with experimentation.

In this video, you will learn several things to improve your testing efforts including:

  • What data science is
  • How A/B Testing fits into the data science hierarchy of needs
  • The relationship between machine learning & AI and A/B Testing
  • What makes a good data scientist

Testing Theory is where professional testers turn to do better A/B testing and get more conversions.

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