AI personalizes product announcements based on each customer's plan and usage patterns. Marketing reviews before every send.
Product announcements often fail to land because every customer gets the same generic message regardless of their plan, usage, or needs. Features that would delight power users get buried alongside updates irrelevant to new customers. The result is low engagement, missed adoption opportunities, and announcement fatigue.
MultiMail's AI agent analyzes each customer's plan level and usage patterns to personalize announcement messaging. Customers see how new features specifically benefit their workflow. With gated_send oversight, product marketing reviews every announcement for accuracy and brand alignment before delivery.
Provide the feature details, affected plans, and key benefits. The AI agent identifies which customer segments are most impacted by the update.
The agent uses search_contacts to group customers by plan tier, feature usage, and engagement level, creating targeted segments that each receive relevant messaging.
Using send_email, the agent drafts announcements that reference each customer's actual usage. A heavy API user learns about new rate limits differently than a dashboard-only user.
With gated_send, all drafts enter the approval queue. Product marketing reviews messaging accuracy and brand consistency before the announcements ship.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
response = requests.post(
f"{API}/send",
headers=HEADERS,
json={
"from": "[email protected]",
"to": ["[email protected]"],
"subject": "New: Webhook support is live on your Pro plan",
"text_body": (
"Hi team,\n\n"
"Great news! Webhooks are now available on your Pro plan. "
"Based on your API usage patterns, here&"cm">#039;s how webhooks "
"can replace your current polling setup:\n\n"
"- Real-time email delivery notifications\n"
"- Instant inbox triggers (no more polling every 30s)\n"
"- Reduced API calls by ~60%\n\n"
"Get started: https://docs.yourcompany.com/webhooks"
),
"html_body": "<h2>Webhooks Are Live</h2><p>Hi team...</p>"
}
)
print(f"Announcement queued: {response.json()[&"cm">#039;id']}")Announce a new feature with messaging tailored to the customer's plan and usage.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
"cm"># Find Pro plan customers who use the API heavily
pro_users = requests.get(
f"{API}/contacts/search",
headers=HEADERS,
params={"query": "pro-plan api-user"}
).json()
for customer in pro_users["results"]:
print(f"Customer: {customer[&"cm">#039;name']} ({customer['email']})")
"cm"># Draft personalized announcement for eachSearch contacts to build targeted announcement lists by plan tier.
"cm">// Find customers on Pro and Scale plans
const proCustomers = await mcp.search_contacts({
query: "pro-plan",
limit: 200
});
"cm">// Send personalized announcements
for (const customer of proCustomers.results) {
const result = await mcp.send_email({
to: customer.email,
subject: "New: Webhook support is live on your Pro plan",
text_body: `Hi ${customer.name}, webhooks are now available...`
});
await mcp.tag_email({
email_id: result.id,
tags: ["product-announcement", "webhooks-launch", "pro-segment"]
});
}Use MCP tools to manage a product announcement campaign across customer segments.
When customers see exactly how a new feature benefits their specific workflow, adoption rates increase dramatically compared to generic announcements.
Customers only receive announcements relevant to their plan and usage. No more tuning out product emails because most updates don't apply.
Gated send ensures product marketing reviews every announcement for factual accuracy. Incorrect feature descriptions or pricing details never reach customers.
Track engagement by customer segment to understand which features resonate with which audiences, informing future product and marketing decisions.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.