A tale of two growth experiments

A deepdive into the lifecycle of a winning and losing experiment and the process, team, and tools behind them. In this webinar, Sam from Mindbloom and Karim from Pearmill discussed how to structure growth experiments, shared examples and reflected on learnings.

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Why run experiments? – A/B experiments can assist you in making data-driven decisions about how to optimize your funnel. They can help you identify where users are dropping off in the funnel and what changes you can make to enhance their experience. By continuously running experiments and analyzing the results, you can make incremental improvements to your funnel and ultimately increase conversions.

In this webinar, you will learn – How to structure your tests, build hypothesis, and carry on learnings to help you improve conversion with examples of experiments from Mindbloom.

See the recording of our webinar, “A tale of two growth experiments” to learn more about best practices for designing and executing experiments that deliver impactful results.

Experiments process and tools – Maintaining a process for running experiments is crucial. After you have generated ideas and tasks, you should decide which ideas to prioritize and validate. Each experiment idea needs to be clearly defined, including its boundaries and potential impact. Next, you should assign ranking factors to every experiment. The most common ranking system used by growth teams is ICE: impact, confidence, effort. Lastly, prioritize experiments based on the ranking factors.

If you want Pearmill's experiment prioritization template, sign up below!