AI identifies satisfied customers from usage data and drafts personalized testimonial requests. Your marketing team reviews the timing and approach.
Marketing teams struggle to collect testimonials because they don't know which customers are happiest or when to ask. Generic requests get ignored, while personalized outreach at the right moment gets results — but identifying those moments and crafting individual asks doesn't scale.
MultiMail's AI agent identifies optimal testimonial candidates based on usage metrics, NPS scores, and support interactions. It drafts personalized requests citing the customer's specific success metrics. With gated_send oversight, marketing reviews the timing and messaging before delivery.
The AI analyzes usage metrics, NPS scores, and support interaction sentiment to identify customers most likely to provide positive testimonials.
The agent composes a testimonial request that references the customer's specific success — their delivery rate, email volume growth, or time saved. This personal touch dramatically improves response rates.
With gated_send, marketing verifies the request is well-timed — not during a support escalation or right after a billing change. They also ensure the ask aligns with current campaign needs.
Approved requests are sent. The agent monitors for positive replies and routes them to the marketing team for case study development.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
def request_testimonial(customer: dict, metrics: dict):
body = (
f"Hi {customer[&"cm">#039;name']},\n\n"
f"Your team has processed over {metrics[&"cm">#039;total_emails']:,} "
f"emails with a {metrics[&"cm">#039;delivery_rate']}% delivery rate "
f"since joining MultiMail. That&"cm">#039;s impressive!\n\n"
f"Would you be open to sharing a brief testimonial about "
f"your experience? It can be as simple as 2-3 sentences "
f"about what&"cm">#039;s working well for your team.\n\n"
f"If you&"cm">#039;re interested in a full case study, we'd love to "
f"highlight your success story on our website."
)
return requests.post(
f"{API}/send",
headers=HEADERS,
json={
"from": "[email protected]",
"to": customer["email"],
"subject": "Would you share your experience with MultiMail?",
"text_body": body
}
).json()
# Find high-satisfaction customers
happy_customers = get_happy_customers(min_nps=9, min_emails=10000)
for customer in happy_customers:
metrics = get_customer_metrics(customer["id"])
request_testimonial(customer, metrics)Find happy customers based on usage metrics and send personalized testimonial requests.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
"cm"># Check for replies to testimonial requests
inbox = requests.get(
f"{API}/mailboxes/marketing-mailbox-id/inbox",
headers=HEADERS,
params={"status": "unread"}
).json()
for message in inbox["emails"]:
email = requests.get(
f"{API}/emails/{message[&"cm">#039;id']}",
headers=HEADERS
).json()
sentiment = analyze_sentiment(email["text_body"])
if sentiment == "positive":
requests.post(
f"{API}/emails/{email[&"cm">#039;id']}/tags",
headers=HEADERS,
json={"tags": ["testimonial-accepted", "follow-up-needed"]}
)
print(f"Testimonial accepted by {email[&"cm">#039;from']}")Monitor replies to testimonial requests and route positive responses to the marketing team.
"cm">// Testimonial request workflow via MCP
"cm">// 1. Search for high-usage customers
const happyCustomers = await mcp.search_contacts({
tags: ["high-nps", "active"]
});
"cm">// 2. Send personalized requests
for (const customer of happyCustomers.contacts) {
await mcp.send_email({
from: "[email protected]",
to: customer.email,
subject: "Would you share your experience with MultiMail?",
text_body: `Hi ${customer.name}, your team has been crushing it with MultiMail. Would you share a brief testimonial?`
});
}
"cm">// 3. Check for responses
const replies = await mcp.check_inbox({
mailbox_id: "marketing-mailbox-id",
status: "unread"
});Use MultiMail MCP tools for testimonial request workflows.
AI identifies customers with the highest satisfaction signals — high NPS, strong usage metrics, positive support interactions — and requests testimonials when sentiment is highest.
Referencing specific success metrics in the request makes customers feel recognized and increases willingness to share their experience.
Gated send lets marketing verify timing and coordinate testimonial requests with ongoing campaigns, launches, and content calendars.
Tag and track every testimonial request, acceptance, and delivered testimonial to maintain a healthy pipeline of customer stories.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.