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Mention a control group and two test groups in the A/B test for Instagram Stories duration.
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Control Group: 24-hour stories; Test Groups: 48-hour stories, Option of 24 or 48-hour stories.
What are the three components of the first step in Diana's trade-off framework?
Mission, Goal, and Hypothesis
What is hypothesized to be the impact of increasing Instagram Stories' duration from 24 hours to 48 hours?
Increased engagement, more time spent on stories, and a rise in the number of weekly active users.
Why is it essential to have a sufficient user sample size in A/B testing?
To ensure the results are statistically significant and representative of the entire user base.
Why is it important to connect the product goal to the company's mission in a trade-off analysis?
It ensures that the decision aligns with the broader objectives of the company.
List three engagement metrics used to measure success in Instagram Stories duration testing.
Number of stories with at least one engagement per week, average time spent on stories per weekly active user, and number of story impressions.
Why might offering users both a 24-hour and 48-hour story duration be beneficial?
It caters to different user preferences, particularly power users who prefer fresh content.
What three types of metrics should be analyzed in the A/B test for Instagram Stories duration?
Engagement Metrics, Creator Metrics, and Consumer Metrics
What role do data scientists play in the design of an A/B test according to Diana's framework?
They help with power calculations, ensuring proper sample size and test duration, and monitoring the results for statistical significance.
What does unbiased results mean in the context of A/B testing?
It means ensuring that the test groups are randomly assigned and results are free from any systematic error or bias.
Why is ensuring tests are unbiased crucial in A/B test design?
To validate that the changes being tested are genuinely responsible for any observed differences in outcomes.
What is the main focus when prioritizing metrics for decision-making in trade-off questions?
Focusing on the key metrics that have the most significant impact on the decision.
What are the three main criteria for the 'Ship' decision in Diana's framework?
Highest incremental impact, no major metric regressions, and positive overall results.
How does Diana's framework suggest dealing with the lack of statistical significance in test results?
If results are not statistically significant but show positive directional trends, a retest may be conducted.
Describe the three possible decisions that can be made after analyzing an A/B test.
Ship (highest incremental impact, no major regressions), No Ship (negative impact, significant regressions), Retest (lack of statistical significance, positive directional results)
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