Tactic 3: Experiment Design & Setup Guidance
Tips:
•
Ask the AI to explain its reasoning.
For example,
if it suggests “run the test for 3 weeks,” have it
explain why. This helps you learn and also verify
When to use:
if the advice makes sense.
Use this tactic before launching an experiment, after you have a
•
Use AI to generate a pre-test checklist:
hypothesis and variants. It’s great for teams less familiar with
e.g., “List 5 things to verify before starting this
experimentation best practices, or whenever you’re unsure about
test (tracking, segmentation, etc.).” This
test parameters. It’s like having a statistician or seasoned A/B
ensures you cover all setup steps (like QAing
testing expert on call to sanity-check your plan.
that both A and B variants render correctly).
Why it works:
•
Combine with human expertise:
If you have a
GenAI has ingested vast knowledge on experimentation and
data scientist, have them review the AI’s
statistics. It can guide you through selecting the right metrics,
recommendations. The AI can do the heavy
audience size, and duration for confident results optimizely.com.
lifting on routine computations or recalling best
For instance, it might warn you (as a human expert would) if your
practices, freeing your experts to focus on
chosen metric is too rare to reach significance, or suggest a more
critical decisions.
sensitive metric. It brings up factors like metric relevance,
•
Remember AI’s limits:
For precise statistical
statistical power, and business alignment, which are key to good
needs (like exact sample size calculation),
experimental design. Essentially, AI can help prevent common
you’ll still use traditional formulas or tools. Use
mistakes such as testing too short, picking a misleading metric, or
AI for directional guidance and education
forgetting to isolate variables.
rather than final authority on stats.
GenAI Quick-Win Playbook for Experimentation
7
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