How would you A/B test first trade rate?
Experiment Design: Increasing New User First Trade Rate
Coinbase aims to enhance the first trade rate among its newly signed-up users. Your task is to design a robust A/B test to evaluate a proposed product change specifically intended to increase the probability that a new user successfully places their initial trade.
Your design should comprehensively address the following aspects:
- Hypothesis Formulation: Clearly state your hypothesis and describe the specific user behavior you anticipate changing as a result of the product modification.
- Metric Definition: Define a precise primary metric (e.g., "first trade within 7 days of signup"). Additionally, identify at least two secondary or guardrail metrics to monitor potential risks, compliance issues, user harm, or impacts on revenue quality.
- Experiment Unit & Randomization: Specify the chosen experiment unit (e.g., user, account, device) and detail the randomization strategy. Outline the eligibility rules for users to enter the experiment and define when a user is considered "exposed" to the treatment.
- Threats to Validity: Discuss key threats that could compromise the experiment's validity, such as selection bias, learning or novelty effects, interference between groups, instrumentation issues, and sample ratio mismatch (SRM).
- Power Analysis & MDE: Describe your approach to sizing the test, including how you would perform a power analysis and determine the Minimum Detectable Effect (MDE). Identify the necessary baseline inputs for these calculations.
- Result Interpretation & Action: Explain your course of action if the experiment yields results that are not statistically significant but show a directional trend. Furthermore, detail your response if any critical guardrail metrics regress significantly.
AI interview prep
Core dilemma
Balancing the need for rapid, iterative product experimentation with the stringent requirements for statistical rigor, financial compliance, and user safety in a high-stakes financial trading environment.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
How would you A/B test first trade rate?
Experiment Design: Increasing New User First Trade Rate
Coinbase aims to enhance the first trade rate among its newly signed-up users. Your task is to design a robust A/B test to evaluate a proposed product change specifically intended to increase the probability that a new user successfully places their initial trade.
Your design should comprehensively address the following aspects:
- Hypothesis Formulation: Clearly state your hypothesis and describe the specific user behavior you anticipate changing as a result of the product modification.
- Metric Definition: Define a precise primary metric (e.g., "first trade within 7 days of signup"). Additionally, identify at least two secondary or guardrail metrics to monitor potential risks, compliance issues, user harm, or impacts on revenue quality.
- Experiment Unit & Randomization: Specify the chosen experiment unit (e.g., user, account, device) and detail the randomization strategy. Outline the eligibility rules for users to enter the experiment and define when a user is considered "exposed" to the treatment.
- Threats to Validity: Discuss key threats that could compromise the experiment's validity, such as selection bias, learning or novelty effects, interference between groups, instrumentation issues, and sample ratio mismatch (SRM).
- Power Analysis & MDE: Describe your approach to sizing the test, including how you would perform a power analysis and determine the Minimum Detectable Effect (MDE). Identify the necessary baseline inputs for these calculations.
- Result Interpretation & Action: Explain your course of action if the experiment yields results that are not statistically significant but show a directional trend. Furthermore, detail your response if any critical guardrail metrics regress significantly.