Tactic 5: AI-Assisted Results Analysis & Insights
What it is:
Example Prompt:
After or during an experiment, use GenAI to analyze the
“Our test results: Variant A – 5% conversion,
performance and translate results into plain-language insights.
Variant B – 6% conversion (20% lift, p=0.03).
This includes summarizing which variant won and by how
Bounce rate dropped 5% on B. Analyze these
much, explaining statistical significance, uncovering patterns in
results and suggest what we should do next.”
subgroups, and even suggesting follow-up actions – all in an
easily digestible format for stakeholders.
How to use it:
Provide the AI with the key results of your experiment. This could be absolute numbers or a summary: for example, “Variant A
conversion rate 12.5%, Variant B 13.7%, p-value 0.04, B is 10% higher on conversions.” You can paste in more detailed metrics or
observation notes if available (e.g. “mobile users responded better than desktop”). Then ask the AI to interpret the results and
draw conclusions. A prompt could be: “Here are the A/B test results... Summarize the outcome and highlight any insights, as if
reporting to a product manager. Include whether the result is statistically significant and actionable.” The AI will then generate a
narrative: e.g., “Variant B increased conversions by 10%, which is statistically significant, suggesting the new checkout flow is likely
better. Notably, the improvement was biggest for mobile users, indicating our changes resonated more on small screens. Next,
we should consider rolling this out or testing on other pages…”
The AI can also answer ad-hoc questions about the data: “Did any segment perform differently?” (if you provide segment data)
or “What might be reasons Variant B outperformed A based on the data?” Essentially, it can serve as a data analyst that speaks
human language.
GenAI Quick-Win Playbook for Experimentation
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