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Generative AI > Google Gemini API > Email Personalisation Agent

Email Personalisation Agent

Author: Venkata Sudhakar

Generic mass emails achieve low open rates and even lower conversions. Personalised emails that reference a customer's recent purchases, browsing history, and location consistently outperform generic blasts. ShopMax India can use a Gemini-powered agent to craft individual emails at scale.

This tutorial builds a Gemini ADK agent that looks up a customer's profile and recent activity, then generates a personalised email with a relevant product recommendation, a personalised subject line, and a time-limited offer.

The below example shows an email personalisation agent for ShopMax India in a business context.

import asyncio
from google.adk.agents import LlmAgent
from google.adk.tools import FunctionTool
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.genai import types

# Customer profiles with purchase history and browsing
CUSTOMERS = {
    "C001": {
        "name": "Anita Sharma", "city": "Mumbai",
        "last_purchase": "Samsung Galaxy Tab - Rs 28,990",
        "browsed": ["iPad Pro", "Apple Pencil", "Tablet Stand"],
        "segment": "premium",
    },
    "C002": {
        "name": "Rajan Pillai", "city": "Bangalore",
        "last_purchase": "Sony WH-1000XM5 Headphones - Rs 24,990",
        "browsed": ["DAC Amplifier", "Audio Cable", "Headphone Stand"],
        "segment": "audiophile",
    },
}

def get_customer_context(customer_id: str) -> dict:
    customer = CUSTOMERS.get(customer_id)
    if not customer:
        return {"error": f"Customer {customer_id} not found"}
    return {
        "customer_id": customer_id,
        "name": customer["name"],
        "city": customer["city"],
        "last_purchase": customer["last_purchase"],
        "recently_browsed": customer["browsed"],
        "segment": customer["segment"],
        "email_brief": (
            f"Write a personalised marketing email for {customer['name']} in {customer['city']}. "
            f"They last bought: {customer['last_purchase']}. "
            f"They recently browsed: {', '.join(customer['browsed'])}. "
            f"Segment: {customer['segment']}. "
            "Include: subject line, greeting, 1 personalised product recommendation "
            "with price, a 48-hour offer, and a CTA button text. "
            "Tone: warm, professional. Use Indian English."
        ),
    }

customer_tool = FunctionTool(func=get_customer_context)

agent = LlmAgent(
    name="email_personalisation_agent",
    model="gemini-2.0-flash",
    description="Generates personalised marketing emails for ShopMax India customers.",
    instruction=(
        "You are an email marketing agent for ShopMax India. "
        "When given a customer ID, call get_customer_context to retrieve their profile, "
        "then write a personalised email following the email_brief in the response. "
        "Output: SUBJECT LINE, then the full email body."
    ),
    tools=[customer_tool],
)

async def main():
    session_service = InMemorySessionService()
    runner = Runner(agent=agent, app_name="email_app", session_service=session_service)
    session = await session_service.create_session(app_name="email_app", user_id="mktg1")
    msg = types.Content(role="user", parts=[types.Part(
        text="Generate a personalised marketing email for customer C001"
    )])
    async for event in runner.run_async(user_id="mktg1", session_id=session.id, new_message=msg):
        if event.is_final_response() and event.content:
            print(event.content.parts[0].text)

asyncio.run(main())

It gives the following output,

SUBJECT LINE:
Anita, complete your tablet setup - exclusive offer just for you

---

Dear Anita,

Thank you for your recent purchase of the Samsung Galaxy Tab!
We noticed you have been exploring accessories to complete your setup.

We think you will love this:

  Apple Pencil (2nd Generation)
  Perfect companion for note-taking, sketching, and creative work
  Price: Rs 9,990  |  No-cost EMI available

Special 48-hour offer for you:
  Use code ANITA10 for an extra 10% off - valid until tomorrow midnight.

  [ Shop Now - Exclusive Offer ]

Free delivery to your Mumbai address. Easy 10-day returns.

Warm regards,
ShopMax India Customer Experience Team

ShopMax India can generate personalised emails for its entire active customer base overnight and schedule delivery at optimal open-rate times by city. Connecting customer browsing data from the website analytics platform ensures recommendations stay current and relevant, significantly improving click-through and conversion rates compared to generic promotional blasts.

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