Marketing Ops

Central command for marketing operations — routing questions, orchestrating campaigns, managing MarTech, and coordinating across all marketing functions.

Table of Contents

• Keywords
• Quick Start
• Skill Routing Matrix
• Campaign Orchestration
• MarTech Stack Management
• Marketing Automation Framework
• Data Management
• Attribution Framework
• Marketing Audit
• Best Practices
• Integration Points

Keywords

marketing ops, marketing operations, MarTech stack, marketing automation, campaign orchestration, skill routing, marketing coordination, data management, attribution, marketing technology, campaign management, workflow automation, lead management, marketing analytics, marketing infrastructure, CRM integration, email automation, lead scoring

Quick Start

Route a Marketing Question

1. Identify what the user is trying to accomplish
2. Match to the routing matrix below
3. Route to the correct skill with context
4. If multiple skills are needed, create an orchestration plan

Orchestrate a Campaign

1. Check that marketing context exists (if not, create it first)
2. Identify all skills needed for the campaign
3. Sequence skills in the correct order
4. Execute each phase, passing outputs to the next
5. Measure results using campaign analytics

Skill Routing Matrix

Content Skills

SEO Skills

Conversion Skills

Channel Skills

Strategy Skills

Campaign Orchestration

Campaign Type: Product/Feature Launch

Sequence:
1. Marketing Context (verify foundation exists)
2. Content Strategy (plan launch content)
3. Copywriting (write landing page and email copy)
4. Landing Page Generator (build the conversion page)
5. Ad Creative (create ad copy for paid promotion)
6. Paid Ads (set up campaign targeting and budget)
7. Social Content (create organic social posts)
8. Cold Email (targeted outreach to prospects)
9. Campaign Analytics (measure results)

Campaign Type: Content Marketing Sprint

Sequence:
1. Content Strategy (plan topics and calendar)
2. Content Production (research, write, optimize each piece)
3. Content Humanizer (polish for natural voice)
4. AI SEO (optimize for AI search citation)
5. Social Content (distribute across platforms)
6. Campaign Analytics (track performance)

Campaign Type: Lead Generation Blitz

Sequence:
1. Marketing Context (verify ICP and messaging)
2. Landing Page Generator (build conversion pages)
3. Ad Creative (generate ad variations)
4. Paid Ads (launch campaigns)
5. Cold Email (parallel outbound effort)
6. Campaign Analytics (measure and optimize)

Campaign Type: Brand Awareness

Sequence:
1. Marketing Context (define brand foundation)
2. Brand Guidelines (establish visual and verbal standards)
3. Content Strategy (plan thought leadership content)
4. Social Content (build social presence)
5. Content Production (create pillar content)
6. Campaign Analytics (measure reach and engagement)

Campaign Type: Conversion Optimization

Sequence:
1. Marketing Psychology (identify behavioral levers)
2. Copy Editing (audit existing page copy)
3. Copywriting (rewrite underperforming sections)
4. Landing Page Generator (redesign conversion pages)
5. Campaign Analytics (set up A/B tests and track results)

MarTech Stack Management

Core Stack Components

Stack Evaluation Framework

When evaluating new tools:

Rule: Never add a tool that does not integrate with your CRM. Disconnected data is worse than no data.

Stack Audit Checklist

• Every tool has a clear owner responsible for it
• Every tool connects to CRM or central data warehouse
• No overlapping tools doing the same job
• All contracts reviewed annually for cost optimization
• Data flows documented between tools
• Integration health monitored (failures flagged within 24 hours)
• Tool adoption measured (tools nobody uses should be cut)

Marketing Automation Framework

Automation Priority by Impact

Lead Scoring Model

Lead score thresholds:

• 0-25: Nurture (automated email sequences)
• 26-50: Marketing Qualified Lead (MQL) — deeper engagement
• 51-75: Sales Qualified Lead (SQL) — route to sales
• 76+: Hot lead — immediate sales outreach

Email Automation Sequences

Data Management

Data Quality Framework

Data Hygiene Schedule

UTM Parameter Standards

Consistent UTM tagging is foundational for attribution:

utm_source: [platform] — google, linkedin, facebook, email, partner-name
utm_medium: [channel type] — cpc, organic, email, social, referral
utm_campaign: [campaign name] — product-launch-q1, blog-promo-march
utm_content: [variant] — headline-a, cta-blue, audience-cmo
utm_term: [keyword] — for paid search only

Rules:

• Always lowercase
• Use hyphens, not spaces or underscores
• Document all campaign names in a shared registry
• Validate UTMs before launching any campaign

Attribution Framework

Attribution Models

Attribution Implementation Checklist

• UTM parameters standardized and enforced
• All marketing channels tagged consistently
• CRM captures source/medium/campaign for every lead
• Conversion events defined and tracked
• Attribution model selected and documented
• Reporting cadence established (weekly + monthly)
• Channel ROI calculated and compared monthly

Marketing Audit

Full Marketing Audit Structure

Audit Scoring

For each area, score 1-5:

Best Practices

1. Context first, always — Check that marketing context exists before any marketing work. Everything works better with context.

2. Route precisely — A question routed to the wrong skill produces wrong-shaped output. Use the routing matrix.

3. Orchestrate, do not fragment — Multi-skill campaigns need a sequence plan. Ad hoc execution produces inconsistent results.

4. Own the data — Marketing ops is responsible for data quality. Bad data produces bad decisions.

5. Standardize UTMs — Inconsistent UTM parameters make attribution impossible. Enforce standards before launching campaigns.

6. Audit tools annually — Every tool should justify its cost and usage. Cut tools nobody uses.

7. Automate the repeatable — If you do it every week, automate it. Manual processes do not scale.

8. Document everything — Campaign playbooks, automation logic, data flows, tool configurations. Tribal knowledge is fragile.

9. Align with sales — Marketing ops and sales ops must share data definitions, lead scoring criteria, and attribution models.

10. Measure what matters — Track leading indicators (MQLs, pipeline velocity) alongside lagging indicators (revenue, ROI).

Integration Points

• Marketing Context — Foundation for all marketing operations. Create this first.
• Campaign Analytics — Use for measuring outcomes of orchestrated campaigns.
• All Marketing Skills — Marketing Ops routes questions and orchestrates workflows across the full skill ecosystem.
• Content Strategy — Coordinate content calendar with campaign schedule.
• Paid Ads — Coordinate paid campaigns with organic efforts and landing pages.
• Cold Email — Coordinate outbound with inbound campaigns to avoid audience overlap.

Troubleshooting

Success Criteria

• All MarTech tools connected to CRM with verified data flow
• MarTech stack audit score above 70/100 with zero critical gaps
• Lead scoring model validated: high-scored leads convert at 2x+ rate of low-scored
• UTM parameters 100% standardized and validated before every campaign launch
• Campaign orchestration follows documented sequences with context verified first
• Budget allocation reviewed and adjusted quarterly based on channel ROI data
• Data quality: <5% duplicate rate in CRM, <2% email bounce rate, >95% required fields complete

Scope & Limitations

In Scope: Skill routing and orchestration, campaign sequencing, MarTech stack management and auditing, marketing automation (email sequences, lead scoring, lead routing), data quality management, UTM standardization, attribution framework setup, marketing audit methodology, budget allocation.

Out of Scope: Individual channel execution (see channel-specific skills), analytics implementation (see analytics-tracking skill), content creation (see content-creator skill), sales operations and CRM administration (sales ops function).

Limitations: Marketing ops is the coordination layer, not the execution layer. Tool auditing uses self-reported utilization data; actual usage may differ. Lead scoring models require minimum 50+ historical conversions for meaningful validation. Budget allocation assumes linear channel scaling; real channels have diminishing returns.

Scripts

scripts/martech_stack_auditor.py

python scripts/martech_stack_auditor.py stack.json --demo

scripts/campaign_budget_allocator.py

python scripts/campaign_budget_allocator.py campaigns.json --budget 100000 --strategy balanced

scripts/lead_scoring_simulator.py

python scripts/lead_scoring_simulator.py leads.json --demo