Tips:
•
Include as much context as possible in the prompt. If Group 2 had a different experience or a known attribute
(e.g., “Group 2 is first-time visitors”), mention that. The AI’s analysis will be more insightful when it knows the circumstances.
•
Ask for segment-specific insights. If your personalization spans many segments or markets, have the AI analyze each:
“Tell me how European customers versus US customers responded to our personalized recommendations.”
•
Have the AI suggest hypotheses for why something happened. This can inspire your team to test those hypotheses.
For example, AI might say: “Segment B may have found the content not relevant to their age group,” which you can verify or
test by adjusting content for that segment.
•
If you have qualitative data (customer service chats, social media comments about your personalized features),
don’t neglect it – AI can summarize those too, adding color to the numbers. It’s like doing thematic analysis in seconds.
•
Share the AI’s summary with stakeholders to quickly update them on personalization performance. It’s often easier
to digest than raw data. Just be sure to verify key claims. You can even use the AI to generate a polished report:
“Present these findings in a concise report with three key takeaways and a recommended action for each.”
GenAI Quick-Win Playbook for Personalization
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