SEO and AB Testing
Does A/B testing negatively affect SEO? Will your SEO suffer if you do A/B testing? What if you are making major changes, will that hurt your SEO? In this video, I will cover the 3 major things to consider regarding SEO and A/B Testing. We will also review the 4 things Google says to do to make sure your testing doesn’t affect your SEO.
In this video, you will learn several things to improve your testing efforts including:
• What Google says about ab testing impact on SEO
• The motivations of the search engines
• Tangible benefits vs intangible benefits
• 4 Practical implementation tips from Google
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Counterweight Measurement
It is possible to over-optimize to a metric. The counterweight measurement strategy is your safeguard to keep you from optimizing to short term gains at the expense of long term loss.
This strategy is designed to give you a gut check on your results to ensure that you are aren’t robbing your future success and helps you appropriately balance your metrics and results.
In this video, you will learn several things to improve your testing efforts including:
- What the counterweight measure strategy is
- How to decide your counterweight metrics
- Examples of what it looks like in practice
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Living Roadmaps
At the first of the year, most companies plan what they will do for the year and the quarters ahead. Rather than just making a plan, the best optimization organizations make a Living Roadmap. This video is all about what a living roadmap is, how to use, and how it can help you do better testing and get more conversions.
A living roadmap allows you to be flexible in your conversion rate optimization plan. By prioritizing and re-prioritizing ideas and work into a living roadmap you give a strategic boost to a/b testing efforts.
In this video, you will learn several things to improve your testing efforts including:
- Why a living roadmap is essential
- What a living roadmap is
- What fields you should have on your roadmap
- When you should change your roadmap and when you shouldn’t
- How you should prioritize your living roadmap
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Tack On A/B Testing Strategy Blunder
This video is about a common strategy error that if avoided will give you better testing and improved results. The Tack On Blunder is a subtle mistake that creeps into split testing strategies. This error is when you add additional variations to a test that focuses on a different business question than the original question was seeking to answer.
In this video, you will learn three side effects of this A/B testing blunder:
- Limits ideas that are tried
- Makes tests and analysis more complex
- Creates the illusion of learning more
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Beware the Best Practices
Most best practices aren’t actually best practices. In this video, we will discuss what a best practice is and I will show you examples of “best practices” that actually aren’t.
A best practices applies universally to different websites and different industries. Too many experts proclaim best practices that are actually test ideas. In this video I will help you learn how to identify split testing best practices.
In this video, you will learn several things to improve your testing efforts including:
- What a best practice is
- The three steps to identify best practices
- Examples from multiple websites of bad best practices
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Speed vs. Control – Doing More or Isolating Changes
Every A/B test has a trade-off of doing something else. There are some testing scenarios where you should control fewer variables in order to gain more speed and go faster. The faster you go, the more you learn, and the more you impact your conversions.
In this video, you will learn several things to improve your testing efforts including:
- The trade-offs of speed vs control
- The two scenarios when you should sacrifice control for speed
- The principles you need to know to help you guide your decision of using more speed
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Evaluating A/B Tests with the Efficiency Equation
If you want to run good split tests and get more wins with every test, the Efficiency Equation can guide your efforts. This simple equation can help you know which tests are efficient to run and which ones you should avoid. It can also help you know where you should focus your future efforts by doing post-test comparisons.
If you want more wins with your conversion rate optimization efforts, then this video is for you.
In this video, you will learn several things to improve your A/B testing including:
- What the Efficiency Equation is
- How to use the Efficiency Equation
- The value of pre-test analysis with the equation
- Doing post-test comparisons with the equation
- A real-life example of the Efficiency Equation
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Guess Who A/B Testing Strategy
The strategy to win at the game of Guess Who is the same strategy that can help you win at A/B Testing. By employing the Guess Who Testing strategy you will be able to get more wins more often.
The strategy says that you should eliminate things that aren’t good, not by trying everything out, but by asking bigger broader questions first. If you get too specific too soon, you will fail at testing just like you will lose at the game.
In this video, you will learn several things to improve your testing efforts including:
- What the Guess Who testing strategy is
- How the Guess Who testing strategy works
- The benefits of using the Guess Who testing strategy
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Actionable Rates of Action
A rate of action by itself doesn’t tell you if it is good or bad. Most rates of action are used in correlative data sets and lead to poor recommendations.
In this video, I will show you a common example of how rates of action are used improperly. We will also discuss the two things needed to make your rates of action actionable.
- Comparable data sets
- Causal data
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.
Experience Optimization not CRO
True optimization experts understand this very important principle. We don’t optimize conversion rates and we aren’t A/B testing teams. We aren’t split testers who also run multivariate tests. We are experience optimizers.
Our true success as optimizers in the digital marketing industry is to realize that we are optimizing the visitor experience. We aren’t optimizing rates or running tests. If we aren’t improving the visitor experience we are potentially getting short term gains at the cost of long term profits.
In this video, you will learn several things to improve your testing efforts including:
- The difference between experience optimization and conversion rate optimization
- How you can have one without the other and one that does both
- The key metrics you need to consider as you become experience optimizers
Testing Theory is where professional testers turn to do better A/B testing and get more conversions.