AI Agent B2B Email Marketing Marketing Automation User Operations

AI Agents in B2B Email Marketing: A Dedicated Operations Agent for Every Lead

Marketing automation has been around for a decade—so why is it still so hard to use? The missing piece is a user operations role. AI Agents now make it possible to assign every lead a one-to-one steward, moving B2B email from mass blast to precision drip nurturing.

TorpedoYu (Yu Lei)
2026-02-27
~12 min read

A Decade of Marketing Automation Stagnation

In B2B, there is something called marketing automation. Frankly, this is a 10-year-old concept, and I find it very hard to use in practice. To make it work, you need a user operations role—someone in operations who thinks carefully about:

User Segmentation
Outreach Strategy
Campaign & Content Push
Live Event Invites
Coupon Distribution
Offline Event Invites

"These actions are not limited to B2B. Look at Luckin Coffee's latest earnings—they launched a new Agent and lifted returning customer conversion. That is fundamentally a nurturing logic that works just as well in B2B."

B2B Nurturing Logic from Luckin Coffee

Luckin Coffee's latest earnings report revealed key metrics:

Luckin Lucky Air 1.0 Agent Results

Q4 paid member ratio

28-30%

↑ +3 pp vs. Q3

Paid member average order value

+30-40%

vs. regular users

Key drivers: membership upgrade + owned-channel offers + Lucky Air 1.0 Agent precision push

Think about it—isn't this fundamentally a nurturing logic? It applies equally in B2B. Luckin used AI Agents for precise returning-customer outreach and personalized recommendations, lifting both paid member ratio and average order value. That mirrors the logic of fine-grained lead nurturing in B2B.

"If we treat every lead like a member and let an AI Agent decide when, through which channel, and with what content to reach them—that is B2B's version of Lucky Air."

The User Operations Dilemma: Clear Vision, No Headcount

On the user operations role, we have observed many companies and found: most organizations struggle to staff this function. Large companies may have someone; small ones usually do not. Even at large companies, frankly, what one person can accomplish is limited.

Why? They must pull resources from many teams—for example, asking someone for content. If one person does only this, the workload is not always full; but to do it well, the workload becomes enormous.

Dedicated Full-Time Hire

Workload not saturated enough to justify the role's ROI

Doing It Properly

Requires cross-functional coordination, behavior analysis, content matching—workload explodes

Why Can't We Get Granular?

When you segment audiences yourself, what is the basis? Often it is gut feel. Someone says, we should have a manufacturing solution and send this content to manufacturing users—that sounds right. But most of the time, segmentation logic does not work that way.

"The right logic is: What did the user do recently? In the past 7 days, who had active engagement with us? What follow-up strategy fits each of them?"

The Right Methodology: From Mass Blast to Precision Drip Operations

Sound user operations should rely on behavior-driven dynamic segmentation, not static industry tags:

Fine-Grained Segmentation Examples

1

Active + behavioral history + recent company news

→ Send customized/personalized follow-up email aligned with their company dynamics

2

Very early stage

→ Continue sending varied campaigns or content to invite engagement

3

Needs offline meeting interaction

→ Invite to offline event—different logic, requires deeper analysis

This requires someone to analyze very carefully. How granular should it be? Drip-level granularity—not mass blast.

Mass Blast

Everyone gets the same email

Drip Operations

Every lead, tailored

"What is the best education? One-to-one. Why is one-to-one hard? Because it is expensive. Marketing exists to aggregate—to help sales create and follow up on leads at scale. Now AI drives the cost of one-to-one nurturing toward zero."

Once you see this clearly—marketing's essence is helping sales acquire or follow up on customers. In key accounts, sales sometimes does marketing work—major account expansion, networking. This function was undervalued because it was underused; now there is much more you can do because you can go very granular—as if you had an army doing it.

Core Solution: User Operations Agent (Alex Agent)

You can follow up on every one of 100,000 leads in your database with extreme granularity. How? With what we call a user operations Agent. I sometimes name it Alex—after Alexander Hamilton, one of America's founding fathers. Alex Agent is smart and strategic.

Alex Agent

User Operations Agent · Dedicated steward for every lead

Analyze what each user should do next → orchestrate different AI Agents → deliver one-to-one precision nurturing

How Does Alex Agent Orchestrate Omnichannel Outreach?

Alex Agent Workflow

Step 1: Intelligent Analysis

Analyze user behavior data and determine the next best action

Email Follow-Up Needed

→ Orchestrate AI EDM Agent to draft and send personalized follow-up email

Offline Invite Needed

→ Orchestrate AI SMS Agent to send invitation and invite to offline event

Phone Conversation Needed

→ High-priority leads: assign to human sales
→ Standard priority: orchestrate AI outbound Agent to call

"Look at Alex Agent this way and the picture changes—you have placed a user operations role beside every lead, a steward, a nurturer. You watch each one and deliver one-to-one nurturing. The upside? It is extraordinary."

Top Sales Insights: The Anti-Human Skill of Persistent Follow-Up

On marketing automation—think about what defines Top Sales. I once discussed this with the CEO of Baiwang Cloud, a Hong Kong-listed fintech company:

Core Traits of Top Sales

Persistent Follow-Up

Never Annoying

Right Timing

Right Channel

Proactive, effective, persistent follow-up

"At the right time, through the right channel, proactive, effective, persistent follow-up. That is anti-human—few people can do it. Alex Agent can."

Persistent follow-up without annoying the prospect sounds simple; almost no one does it well. It requires strong time management, emotional control, and strategic thinking. Human reps are limited by energy, mood, and memory—they cannot maintain just-right follow-up across hundreds of leads. AI Agents have no such limits. They can deliver personalized, persistent follow-up 24×7 for every lead.

Personalization at Scale: Custom Content for Every Lead

How do you actually do this? Send a campaign when it is a campaign, content when it is content? That is too simplistic.

Even your campaigns must be matched individually. The white paper you send should be tailored to their industry. Your generic white paper may not target industrial buyers—but you can reframe it for industrial use cases.

Or your white paper covers many topics but is not highly relevant to them. Can you combine and match from ten historical assets in your library?

Three Layers of Personalized Content

1

Industry Matching

Adapt a generic white paper into a version for the user's industry

2

Relevance Extraction

From ten historical assets, select the content fragments most relevant to this user

3

Dynamic Recomposition

Based on user behavior and company dynamics, combine and generate new personalized content in real time

"All of this is worth thinking through. When we design user operations today, we should assign every lead a user operations Agent for one-to-one nurturing. That changes the logic entirely."

Summary: One AI Agent, the Output of an Operations Team

100K+

Every lead, one-to-one follow-up

24×7

Continuous operations, never tiring

Drip

Precision outreach, never annoying

This is the value of the user operations Agent:
A dedicated steward for every lead

From our B2B experience, we have always needed this AI Agent—we call it the user operations Agent. Alex Agent. Think along these lines: does traditional marketing automation matter as much as we used to think?

Today, when we design user operations, we should assign every lead a user operations Agent for one-to-one nurturing. That changes the logic entirely. We will continue researching and bringing this capability to market.

Key Takeaways

Marketing automation's 10-year adoption gap stems from missing the user operations role

User operations is drip, not mass blast

AI Agents drive one-to-one nurturing cost toward zero

Segmentation should be behavior-driven, not static tags

Content must be matched and customized for every lead

Top Sales' anti-human follow-up skill can be scaled by Agents

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