AI generates customer-specific usage insights with trends and recommendations. Scheduled delivery keeps customers informed without manual effort.
Manual report generation doesn't scale. As your customer base grows, producing individualized usage reports becomes impossible. Customers lack visibility into their consumption patterns, leading to surprise bills, underutilization of features, and preventable churn. Generic usage dashboards exist, but proactive email reports drive 3x more engagement than passive dashboards.
MultiMail's AI agent generates personalized usage reports on a configurable schedule — weekly, monthly, or quarterly. Each report includes consumption metrics, trend analysis, and AI-driven recommendations based on the customer's unique usage patterns. Autonomous oversight handles reliable, scheduled delivery at scale.
Your AI agent runs on a configurable schedule (weekly, monthly, etc.) and processes each customer's usage data for the reporting period.
The agent pulls usage metrics from your product database — API calls, feature adoption, storage consumption, or whatever metrics are relevant to your product.
The AI analyzes usage patterns and generates insights: month-over-month trends, underutilized features, approaching plan limits, and personalized recommendations.
Under autonomous oversight, the report is sent via send_email to the customer. Templated reports with customer-specific data are safe for autonomous delivery.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
def generate_usage_report(customer: dict, period: str):
usage = get_usage_data(customer["id"], period)
trends = calculate_trends(usage)
recommendations = generate_recommendations(usage, customer["plan"])
report = (
f"Hi {customer[&"cm">#039;name']},\n\n"
f"Here&"cm">#039;s your {period} usage report:\n\n"
f"Emails processed: {usage[&"cm">#039;emails_processed']:,} "
f"({trends[&"cm">#039;emails_change']:+.0f}% vs last period)\n"
f"Mailboxes active: {usage[&"cm">#039;active_mailboxes']}\n"
f"Storage used: {usage[&"cm">#039;storage_mb']:.0f} MB of "
f"{customer[&"cm">#039;storage_limit_mb']} MB\n"
f"Delivery rate: {usage[&"cm">#039;delivery_rate']:.1f}%\n\n"
f"Insights:\n"
+ "\n".join(f"- {r}" for r in recommendations)
)
requests.post(
f"{API}/send",
headers=HEADERS,
json={
"from": "[email protected]",
"to": customer["email"],
"subject": f"Your {period} usage report: {usage[&"cm">#039;emails_processed']:,} emails processed",
"text_body": report,
"html_body": build_report_html(usage, trends, recommendations)
}
)Aggregate usage data and generate a personalized report email.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
def send_monthly_reports():
customers = get_all_active_customers()
for customer in customers:
try:
generate_usage_report(customer, "February 2026")
print(f"Report sent to {customer[&"cm">#039;email']}")
except Exception as e:
print(f"Failed for {customer[&"cm">#039;email']}: {e}")
# Log failure and retry later
queue_retry(customer, str(e))
print(f"Sent {len(customers)} usage reports")Generate and send reports for all customers on a schedule.
"cm">// Using MultiMail MCP tools for usage reports
async function sendUsageReport(customer: Customer, period: string) {
const usage = await getUsageData(customer.id, period);
const trends = calculateTrends(usage);
const insights = generateInsights(usage, customer.plan);
"cm">// Send personalized report
await mcp.send_email({
to: customer.email,
subject: `Your ${period} usage report: ${usage.emailsProcessed.toLocaleString()} emails`,
text_body: [
`Hi ${customer.name},`,
``,
`Here's your ${period} summary:`,
` Emails processed: ${usage.emailsProcessed.toLocaleString()}`,
` Delivery rate: ${usage.deliveryRate}%`,
` Storage: ${usage.storageMb}MB / ${customer.storageLimit}MB`,
``,
`Insights:`,
...insights.map(i => ` - ${i}`)
].join("\n")
});
"cm">// Update contact with report metadata
await mcp.add_contact({
email: customer.email,
metadata: { last_report_sent: new Date().toISOString() }
});
}Generate and send usage reports using MultiMail MCP tools.
Customers receive insights without logging into a dashboard. Proactive reports drive 3x more engagement than passive analytics and build trust through transparency.
Reports that show approaching plan limits or declining usage create natural upgrade and re-engagement touchpoints before customers churn.
Autonomous mode sends personalized reports to every customer on schedule. Whether you have 100 or 100,000 customers, each one gets an individualized report.
Each report includes personalized recommendations based on the customer's actual usage patterns — underutilized features, optimization opportunities, and relevant plan upgrades.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.