USE CASE
AI Marketing Ops: Replace Marketo, Pardot, and ActiveCampaign
Build an AI marketing operations team that scores leads intelligently, runs nurture sequences, and automates your entire marketing stack—without $12,000/year for automation software.
Marketing automation promised to make everything easier. Instead, you got complex workflows, brittle integrations, and a tool that requires a full-time admin. Marketo at $12,000/year. Plus the person to run it: $70,000/year.
What do you actually get? A visual workflow builder that takes weeks to master. Lead scoring rules that no one remembers writing. Email sequences that feel robotic because they are robotic.
What if marketing ops just worked? Leads come in, get scored based on real buying signals, get nurtured with contextually relevant content, and get handed off to sales at exactly the right moment—all automatically, all intelligently.
The Marketing Automation Tax
Here's what marketing automation platforms actually cost (before implementation and ongoing management):
| Tool | Price/Month | Annual Cost |
|---|---|---|
 Marketo | $1,000+ | $12,000+ |
 Pardot | $1,250 | $15,000 |
 HubSpot | $800 | $9,600 |
 ActiveCampaign | $199 | $2,388 |
Prices for professional/growth tiers as of December 2025. Enterprise tiers cost 2-5x more.
You're paying $12,000+/year for software that still requires a marketing ops person to run. The AI does both.
What Marketing Automation Actually Is
Strip away the branding and what are you left with?
| Marketing Feature | What It Really Is |
|---|---|
| Lead Scoring | Point system based on arbitrary rules (opened email = +5, visited pricing = +10) |
| Email Sequences | Scheduled emails with if/then logic and merge fields |
| Audience Segmentation | Database queries filtering by field values |
| Multi-touch Attribution | Spreadsheet math on UTM parameters and timestamps |
| Campaign Management | Folder structure for organizing email templates |
Marketo is a $12,000/year spreadsheet with a visual workflow builder.
What an AI Marketing Ops Agent Actually Does
An AI marketing ops agent isn't just a chatbot that answers questions about campaigns. It's a persistent agent that actively manages your marketing operations—and works alongside your sales agent for seamless handoffs:
Scores leads with real understanding
Nurtures intelligently and adaptively
Coordinates multi-channel campaigns
Reports on pipeline impact, not vanity metrics
Hands off to sales with full context
A Day in the Life: Your Marketing AI Team
Here's what it looks like when AI agents manage your marketing operations. Watch how they score leads, optimize campaigns, and coordinate with sales:
Hot Lead Alert
via Slack - #marketing-opsHigh-Intent Leads Detected
| Lead | Score | Key Signal |
|---|---|---|
| Sarah Chen (Acme Corp) | 92 | Pricing page 3x, case study download, 5 blog posts |
| Mike Johnson (TechStart) | 87 | Demo video watched 100%, competitor comparison page |
| Lisa Park (GlobalCo) | 84 | Integration docs, API reference, returned 4 days in a row |
Sarah Chen has enterprise signals—large company, technical research pattern. Recommend immediate sales outreach. Hand off to Sales Agent?
Campaign Performance Analysis
November Campaign Performance Report
| Campaign | Leads | MQLs | Pipeline |
|---|---|---|---|
| Product Launch Webinar | 247 | 43 | $127,000 |
| Competitor Comparison Guide | 189 | 52 | $156,000 |
| ROI Calculator | 312 | 28 | $84,000 |
| Case Study Series | 156 | 67 | $201,000 |
The competitor comparison guide has the best MQL rate (27.5%) and pipeline per lead ($825). Case studies drive the most total pipeline. Webinar had high attendance but lower conversion—recommend shorter format or different topic for next month.
Nurture Sequence Optimization
via Slack - #marketing-opsNurture Sequence Performance Alert
The enterprise nurture sequence is underperforming. Here's the breakdown:
| Open Rate | CTR | Status | |
|---|---|---|---|
| Email 1: Welcome | 62% | 12% | ✅ Good |
| Email 3: Case Study | 28% | 2% | ⚠️ Underperforming |
| Email 5: Demo Request | 15% | 1% | ❌ Poor |
Email 3's subject line mentions 'case study'—enterprise buyers may perceive this as too promotional at this stage. Recommend testing 'How [Similar Company] solved [Problem]' framing instead.
Weekly Pipeline Report
Weekly Marketing Report — Week of Dec 16
| Metric | This Week | vs Last Week |
|---|---|---|
| New leads | 342 | +18% |
| MQLs generated | 47 | +8% |
| Sales handoffs | 23 | +15% |
| Pipeline influenced | $312,000 | +22% |
| Cost per MQL | $127 | -12% |
Top source: LinkedIn ads (38% of MQLs). Organic search climbing—up 45% since SEO content push in October.
The competitor comparison campaign is now our #1 pipeline driver. Recommend doubling ad spend next month.
Full report saved to /marketing/reports/weekly-2025-12-16.md
The Killer Feature: A Connected Marketing Workspace
Here's what makes this fundamentally different from any marketing automation tool you've used before. In Lazarus, your AI agents share a persistent workspace—the same leads, the same content, the same campaign data.
When your lead scoring agent identifies a hot prospect, it writes to the shared leads database. Your nurturing agent reads engagement data to personalize sequences. Your sales agent gets the full picture when a lead is handed off. No sync issues, no data silos—just agents collaborating in real time.
/marketing
├── leads/
│ ├── all-leads.csv
│ ├── scored-leads.csv
│ └── mql-handoffs.csv
├── campaigns/
│ ├── active-campaigns.csv
│ └── campaign-performance.md
├── sequences/
│ ├── enterprise-nurture/
│ ├── smb-nurture/
│ └── trial-onboarding/
├── content/
│ ├── email-templates/
│ └── landing-pages/
└── reports/
├── weekly-pipeline.md
└── attribution-analysis.mdNo per-contact pricing
Full data ownership
Sales and marketing alignment built in
Intelligence compounds over time
This isn't a tool that helps you do marketing ops. It's a marketing ops team that does marketing ops.
Build Your Marketing AI Team in 15 Minutes
Here's how to build your first marketing ops agent—and set up the foundation for full marketing automation:
Step 1: Create the agent and write instructions
Open Lazarus and create a new agent. Name it 'Marketing Ops Agent' or 'Lead Manager.' Then describe what you want:
"You are my marketing ops agent. Score all leads in /marketing/leads/ based on engagement signals. Run nurture sequences from /marketing/sequences/. Hand off leads to Sales Agent when score exceeds 80. Generate weekly pipeline reports. Alert me to underperforming campaigns."
Step 2: Connect your lead sources
Forms, landing pages, ad platforms—connect where leads come from. The agent will capture, deduplicate, and start scoring immediately.
Step 3: Define your scoring model
What behaviors indicate buying intent? Pricing page visits, content downloads, return visits? The agent learns your patterns and refines over time.
Step 4: Build your content library
Email templates, nurture sequences, sales collateral—the agent pulls the right content for each lead based on their stage and interests.
Step 5: Connect to your Sales Agent
Link your Marketing Ops Agent to your Sales Agent for seamless handoffs. When a lead is ready, sales gets the full picture automatically.
That's it. You've built marketing operations that run automatically while you focus on strategy.
The Full Picture: Your Marketing AI Team
Build a team of specialized agents that share the same workspace—each focusing on what they do best, all working together:
| Agent | Role | Workspace Access |
|---|---|---|
| Lead Scoring Agent | Evaluates and scores all leads based on behavior | Reads /leads/*, writes /leads/scored-leads.csv |
| Nurturing Agent | Manages sequences and personalized outreach | Reads /leads/*, /content/*, writes /sequences/ |
| Campaign Manager Agent | Tracks performance and optimizes campaigns | Reads /campaigns/*, writes /reports/ |
| Marketing Analyst Agent | Attribution analysis and pipeline reporting | Reads all, writes /reports/attribution/ |
How They Work Together
New lead comes in → Lead Scoring Agent evaluates based on firmographics and initial behavior → writes to /leads/scored-leads.csv
Nurturing Agent picks up leads based on score tier → runs appropriate sequence → tracks engagement → updates lead score
Lead hits MQL threshold → Marketing Ops Agent notifies Sales Agent with full context → lead moves to sales pipeline
Campaign Manager tracks which sources, content, and sequences drive the best results → feeds insights back to optimize scoring and nurturing
No handoff meetings. No 'where did this lead come from?' Every agent sees the full picture.
Four agents. One workspace. Zero data silos. Complete marketing visibility.
Stop paying $12,000/year for marketing automation you still need someone to run.
Marketo + marketing ops hire costs $80,000+/year. Your marketing AI team costs a fraction of that—and actually does the work.
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