Mistakes to Avoid While A/B Testing
- Invalid Hypothesis: In A/B testing all the steps depend upon the hypothesis developed before beginning the test. A hypothesis involves what should be changed, why it should be changed, and the expected outcome. If a test starts with a wrong hypothesis, the probability of a successful test is very low.
- Testing Wrong Page: Split testing wrong pages can waste time and valuable resources. It is important to determine what to test and identify the best pages to test that will increase the conversion.
- Testing Too Many Elements Together: Testing too many elements together makes it difficult to pinpoint which element influenced the test’s failure or success. Prioritizing tests is important for successful A/B testing.
- Working with Wrong Traffic: The site must have a healthy amount of traffic to its pages. If the site has heavy traffic then the split tests will be completed relatively faster in comparison to when there is low traffic then tests need to be executed for a longer period.
- Running Split Test at Wrong Time: To split test a website, it is important to determine the correct timing. If a page gets most of its traffic on Friday then it does not make sense to compare the test results of Friday with low-traffic days.
- Running Tests for Not Long Enough: To achieve statistically significant test results it is important to run tests for a certain amount of time.
- Using Wrong Tools: There are multiple low-cost tools available in the market for A/B testing. Not all the tools are equally capable and not all tools provide all the necessary features. Some of the tools can slow down the site leading to data deterioration. Using faulty tools can affect the test’s success.
- Measuring Results Inaccurately: Measuring tests accurately is equally important as conducting tests accurately. If the results are not measured correctly then one cannot rely on the data.
- Running Tests on Wrong Site: Sometimes the split tests are being conducted on development sites instead of the live sites. It is important to switch the tests from development sites to live sites as development sites are used by developers, not customers.
- Not Documenting: Documenting every detail is important. Some companies skip this step or the documentation is not in one place, it is scattered across multiple emails. When there is a need to determine why the change was done, it becomes difficult to trace back the details of the change.
A/B Testing Framework
A/B testing is a proven way to improve your online strategy by comparing two versions of a webpage or app and seeing which one performs better based on user behavior. This article focuses on discussing the A/B testing framework.
Table of Content
- What is A/B Testing?
- Why Should You Consider A/B Testing?
- What Can You A/B Test?
- Types of A/B Testing
- Statistical Approach to use to Run A/B Test
- Steps to Conduct an A/B Test
- A/B Testing Process
- What are Variant A and Variant B?
- What is the Conversion Rate?
- What do you mean by Statistical Significance?
- Mistakes to Avoid While A/B Testing
- Challenges in A/B Testing
- A/B Testing and SEO
- Conclusion
- FAQs
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