marketing-ops

Overview of marketing-ops skill

What marketing-ops is for

The marketing-ops skill is a central router and campaign coordinator for a broader marketing skill ecosystem. Instead of treating every marketing request as a generic strategy prompt, it helps decide which specialist skill should handle the work, in what order, and with what context. It is best for Marketing Operations, growth teams, founders, PMMs, and AI operators who need to coordinate content, SEO, CRO, paid channels, email, analytics, and launch work without losing the campaign thread.

Best-fit use cases for Marketing Operations

Use marketing-ops when the request is broad, cross-functional, or ambiguous: “What should we do next?”, “Plan a campaign,” “Audit our marketing,” “Coordinate launch assets,” or “Which marketing skill should I use?” Its value is highest when there are multiple workstreams, dependencies, deadlines, and owners. It can route simple tasks, but its strongest fit is campaign orchestration and marketing audits.

What makes this skill different

A normal prompt may produce a single plan. The marketing-ops skill is designed to act like an operating layer: it checks for product-marketing context, routes requests through a matrix of specialist skills, and can coordinate a multi-step campaign sequence. The repository also includes scripts/campaign_tracker.py, a practical helper for tracking tasks, owners, deadlines, statuses, and skills used across a campaign.

When this skill may be too much

If you only need one asset, such as a single ad headline or a short blog outline, a specialist skill may be faster. marketing-ops is not a replacement for channel expertise; it decides when to use content strategy, copywriting, paid ads, analytics, CRO, or other marketing skills. It also depends heavily on good business context, so vague inputs will lead to generic routing.

How to Use marketing-ops skill

marketing-ops install and first files to inspect

Install the skill with:

npx skills add alirezarezvani/claude-skills --skill marketing-ops

After installation, start with SKILL.md at marketing-skill/skills/marketing-ops/SKILL.md. Read the “Before Starting,” “How This Skill Works,” and routing matrix sections first, because they explain when the skill should route a question, orchestrate a campaign, or run a marketing audit. Then inspect scripts/campaign_tracker.py if you want a lightweight campaign status structure you can adapt for your team.

Inputs the skill needs to work well

For strong marketing-ops usage, provide context before asking for a plan. Useful inputs include product category, target audience, ICP, current funnel stage, main goal, budget range, timeline, channels already in use, analytics maturity, team roles, and constraints. If .claude/product-marketing-context.md exists, the skill is designed to read it first. If it does not exist, the skill may recommend running marketing-context before deeper orchestration.

A weak prompt is: “Help with marketing.”

A stronger prompt is: “Use marketing-ops to plan a 6-week launch campaign for a B2B SaaS analytics feature. ICP is RevOps leaders at 200-1000 employee companies. Goal is demo requests. Channels available: SEO, email, LinkedIn, paid search. Team: one PMM, one content marketer, one designer. Budget: $15k. We need task sequencing, specialist skills to invoke, owners, and tracking metrics.”

Practical workflow for campaign orchestration

Start by asking marketing-ops to classify the request: route, campaign orchestration, or audit. For a campaign, ask it to produce the skill sequence before generating assets. A good sequence might begin with marketing context, then launch strategy, content strategy, landing page copy, email sequence, social content, paid ads, ad creative, analytics tracking, and CRO review.

For execution, request outputs in phases: strategy, asset plan, production tasks, measurement plan, and QA checklist. This prevents the skill from jumping into copy before the campaign architecture is clear.

Using the campaign tracker script

The included scripts/campaign_tracker.py shows a JSON-style model for campaign tasks: skill, task, owner, deadline, and status. Treat it as a starting point rather than a finished project-management system. It is useful when you want the AI workflow to produce a structured task list that can later be transferred into tools like Asana, Linear, Notion, Airtable, or a spreadsheet.

marketing-ops skill FAQ

Is marketing-ops only for large marketing teams?

No. Small teams can use it to avoid scattered execution, especially during launches or growth pushes. The difference is scale: a solo founder might use it to decide the next three marketing moves, while a larger Marketing Operations team might use it to coordinate multiple specialist outputs, owners, deadlines, and analytics dependencies.

How is this better than asking for a marketing plan?

A generic marketing plan often blends strategy, tactics, copy, and measurement into one broad answer. The marketing-ops skill adds decision logic: it identifies the type of marketing problem, routes work to specialist skills, and keeps campaign dependencies visible. That matters when SEO, paid ads, email, creative, landing pages, and tracking all need to align.

Do I need the rest of the marketing skill ecosystem?

You can still use marketing-ops as a planning guide, but it is designed to coordinate other marketing skills. Its routing matrix is most valuable when those specialist skills are available. If you do not have them installed, use its output as a map for manual work or install the relevant skills as your campaign requires them.

When should I not use marketing-ops?

Do not use it as the first stop for highly specific production tasks when you already know the specialist needed. For example, “write five subject lines” belongs with an email or copywriting skill. Also avoid using it without product, audience, and goal context; the output will be more generic and less operational.

How to Improve marketing-ops skill

Improve marketing-ops results with sharper context

The fastest way to improve marketing-ops output is to supply decision-making context, not just a goal. Include the business model, funnel bottleneck, audience sophistication, sales cycle, current conversion rates if known, channel constraints, and what has already been tried. This helps the skill choose between SEO-led growth, launch sequencing, CRO fixes, paid acquisition, lifecycle email, or content production.

Ask for routing before execution

A common failure mode is asking for final campaign assets too early. Instead, ask: “Route this request first, explain which specialist skills should be used, then produce the execution order.” This forces the skill to behave like Marketing Operations rather than a general copy generator. For complex campaigns, also ask it to identify dependencies, risks, and missing inputs before assigning tasks.

Turn first outputs into operating artifacts

After the first plan, ask the skill to convert recommendations into practical artifacts: a RACI table, weekly campaign timeline, task tracker fields, analytics checklist, QA checklist, or channel-by-channel handoff brief. These formats make the output easier to execute and reduce the gap between AI planning and team operations.

Iterate with performance and constraint feedback

After launch or audit work begins, feed results back into marketing-ops: CTR, conversion rate, CAC, demo quality, content rankings, email engagement, landing page drop-off, or sales feedback. Ask it to reprioritize the campaign based on evidence. This is where the skill becomes more useful than a one-time marketing plan: it can keep coordinating the next best action across channels.