AI Agents · Lesson

Customer Context and History Management

Personalized responses using past purchases, tickets, and preferences.

Why Context Makes Agents Feel Human

The difference between a mediocre and an excellent customer service agent is context. When an agent says 'I see your subscription renews next week — would you like to pause it before then?', the customer feels known, not just processed.

This lesson covers building a rich customer context layer for your agents.

Customer Profile Schema

Define a standard customer profile that aggregates data from multiple sources. The agent receives this dict at the start of every conversation.

from dataclasses import dataclass, field
from datetime import date

@dataclass
class CustomerProfile:
    customer_id: str
    name: str
    email: str
    join_date: date
    subscription_tier: str          # 'free', 'pro', 'enterprise'
    account_age_days: int
    lifetime_value_usd: float
    previous_tickets: list[dict] = field(default_factory=list)
    recent_purchases: list[dict]  = field(default_factory=list)
    preferences: dict             = field(default_factory=dict)

    @property
    def is_long_term_customer(self) -> bool:
        return self.account_age_days > 365

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