When to use:
Example Prompt:
Use this tactic in real-time decisioning or campaign planning for individual
customers. It’s particularly valuable in CRM systems, sales outreach, or any
“Customer Jane Doe: 3 purchases
one-to-one marketing scenario.
this year (all running shoes), left
a 4-star review, hasn’t bought in
In B2B, an account executive could use it before a call to decide what to pitch.
4 months. What’s the next best
In B2C, it can inform what dynamic content to show when a user logs in, or what
action to re-engage her?”
offer to email them next. Essentially, whenever you have to decide “What do we
do for this specific customer now?”, AI-driven suggestions can help – at scale.
Why it works:
Traditional recommendation systems predict products or content, but they might not explain the logic or consider multi-step
interaction sequences. GenAI can incorporate various inputs and business rules, then recommend an action in plain language.
It’s flexible – not limited to just products. The “action” could be anything: invite to an event, a survey, or a loyalty offer. This helps
marketers or sales reps understand the recommendation and gives them a ready-to-use approach.
For example, the AI might reveal:
“This customer often responds to community-oriented messaging, so the next best action is to invite them to our user forum.”
That's a nuanced tactic a generic algorithm might not surface.
Over time, these AI suggestions can be tracked – if they prove effective (which you’ll know from Tactic 4’s analysis), you can
even start automating them. Essentially, you’re crowdsourcing strategy from the AI for each customer.
This leads to highly personalized, timely engagements that can significantly improve conversion, retention, and customer
satisfaction. GenAI enables personalization systems for individuals at a scale never seen before – treating each person uniquely,
as if you had a personal concierge for each one.
GenAI Quick-Win Playbook for Personalization
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