When to use:
Use AI-driven persona generation at the start of any personalization
initiative. It’s great for marketing and product teams during planning
Tips:
or brainstorming. If you’re unsure how to break down a diverse
•
Combine AI personas with real quotes or
audience – or need a refresh of your personas using up-to-date
anecdotes from customers (if available). Ask
data – this tactic is ideal. It ensures your personalization strategies
the AI to incorporate snippets from interviews
are rooted in a clear picture of who you’re targeting.
or reviews for authenticity.
Why it works:
•
Ask the AI to identify emotional drivers and
GenAI can synthesize disparate data points into a coherent story.
preferences for each persona (e.g., “values
It’s adept at pattern recognition and narrative, turning dry facts
convenience over price” or “seeks expert
(like “prefers X, has done Y”) into a living character description. This
advice”). These insights help craft more
saves time (no more spending weeks creating persona documents)
resonant messaging.
and captures nuances you might overlook. In fact,
about 90% of
•
Validate AI personas with stakeholders who
leaders believe GenAI opens up new ways to understand and reach
know your customers (e.g., sales reps,
audiences.
And because AI continuously learns from data, it can keep
customer support). Does the description feel
personas fresh as behaviors evolve – helping you target real, dynamic
accurate? Tweak as needed – AI gives you a
users, not outdated stereotypes.
solid first draft.
Example Prompt:
•
Keep personas fluid. Rerun this exercise
periodically (e.g., quarterly or when entering a
“Our user base data: Segment A – 20s, frequent small purchases,
new market) to see if the AI detects shifts. This
engages on social media; Segment B – 40s, high average order
kind of agility is something static, annual
value, responds to email. Describe these two customer personas
persona exercises can’t match.
and suggest what content or offers each would appreciate.”
GenAI Quick-Win Playbook for Personalization
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