When A/B Testing Fails: How Data-Driven Decision Making Can Go Wrong
Done right, A/B testing can be an extremely powerful tool for making data-driven decisions. But as these tests have become more popular, so too have false results, leading teams to invest time and money into decisions not borne out by data.
After this session, you will be able to:
- Understand the basics of using data to make decisions and testing out what matters to your users
- Avoid common mistakes in setting up A/B tests
- Determine if the results of your experiment are actually meaningful