Tactic 1: Rapid Hypothesis Generation with AI
When to use:
Tips:
This tactic is ideal at the ideation stage – when your
•
Give the AI some constraints or focus areas
team needs fresh ideas or when you’re not sure what to
(e.g. “ideas for mobile users” or “low-cost
test next. Also useful when optimizing a specific metric
changes”) to get more relevant suggestions.
(e.g., add-to-cart rate) and want AI to propose
•
Use a refinement loop. After AI suggests ideas,
targeted, hypothesis-driven changes.
ask follow-up questions on the most promising
ones (e.g. “How would that improve UX?”) to
Why it works:
further develop the hypothesis.
AI can tap into a wide knowledge base of proven
•
Keep human insight in the mix. Use the AI’s
strategies, sparking ideas you might miss. In fact,
ideas as a springboard in team discussions,
modern AI systems can even suggest targeted
not a final decision. Human intuition plus AI
experiments based on your data and goals, essentially
breadth makes for better hypotheses.
automating the brainstorming process. You’ll still want to
vet the AI’s ideas for feasibility and impact, but this
approach ensures you start with a strong list of
hypotheses aligned to your objectives.
GenAI Quick-Win Playbook for Experimentation
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