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Improve your content: The What, Why, Where and How about A/B Testing

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Improve your content: The What, Why, Where and How about A/B Testing

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A/B testing, also known as split testing, is a user experience research methodology where users are randomly split into two or more groups to see different versions of the same element. This presentation explains what is A/B testing, why you need it, where you can apply it and how to conduct an A/B test.

A/B testing, also known as split testing, is a user experience research methodology where users are randomly split into two or more groups to see different versions of the same element. This presentation explains what is A/B testing, why you need it, where you can apply it and how to conduct an A/B test.

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Improve your content: The What, Why, Where and How about A/B Testing

  1. 1. Improve Your Content: the What, Why, Where and How about A/B Testing By Zhiqi He UCSD Extension Content Marketing FA21
  2. 2. What is A/B Testing? •A/B testing, also known as split testing, is a user experience research methodology where users are randomly split into two or more groups to see different versions of the same element. •Metrics such as click-through rate and conversion rate are tracked to determine which version performs better.
  3. 3. Example Half of the users would see the blue button on the left while the other half see the green button right. Click rate is measured.
  4. 4. Why do you need A/B Testing? Improve Reduce Content Bounce Rate Engagement Cart Abandonment Conversion Risk Sales Traffic It is impossible to come up with the perfect UI & content that lasts forever in one attempt, which means there’s always room for improvement. A/B testing enables users to evaluate if what is thought to be “an improvement” is actually better.
  5. 5. Where can you apply A/B testing? • Typography: Type face Color Font size
  6. 6. Where can you apply A/B testing? • Call to Action: Positions Color Text In 2007, Obama raised an extra $60 million just by changing his CTA button text from “Sign Up” to “Learn More”
  7. 7. Where can you apply A/B testing? Price Schemes: Freemium v. Free Trial v. Money Back Free trial length Pricing Copywriting: Headlines Length Writing Style Formatting Design: # of columns Background # of clicks required
  8. 8. How to Conduct A/B Testing? Research Pick the Variable Formulate Hypothesis Determine Confidence Level and Sample Size • Current performance • Tools • One “independent variable” in A/B testing • Take desktop and mobile version differently • Check out multivariate testing and URL testing for changing multiple variables • Determine the metrics • Identify the main “dependent variable” • Make prediction to formulate the hypothesis • Large enough to perform statistical test and draw meaningful conclusion • But not too big to waste resources • Common confidence level is 95%
  9. 9. How to Conduct A/B Testing? Create Variations Run the Test Interpret the Result and Deploy Changes • Use current version as control • Create new variations as the treatment • Run the test and wait until desired sample size and duration is reached • Different variations should be tested simultaneously EXCEPT testing on “timing” • Users should be directed to different versions randomly • Perform statistical tests to draw conclusion • If one variation is statistically better, make the improvement • If there is no significant test result, stay with the original version and design new A/B test.
  10. 10. Exercise

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