Marketing Strategy logo

Marketing Strategy

Organization
LeadMagic
marketing-strategy

Build complete B2B marketing strategies — channel mix, budget allocation, content strategy, demand generation, brand building, and measurement framework. Use when building a marketing plan, allocating marketing budget, designing multi-channel campaigns, or creating a marketing operating system. Triggers on: "marketing strategy", "marketing plan", "demand generation", "brand strategy", "marketing budget", "channel strategy", or any marketing planning request.

Overview

PublisherLeadMagic
Repositorygtm-skills
Skill namemarketing-strategy
Stars
72
Forks
18
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LeadMagic on GitHub. Read the source before you install it.

Installation

Install the Marketing Strategy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/LeadMagic/gtm-skills/tree/main/skills/analytics/marketing-strategy
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LeadMagic/gtm-skills.git /tmp/gtm-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-skills/skills/analytics/marketing-strategy .claude/skills/marketing-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Marketing Strategy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Marketing Strategy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Marketing Strategy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Marketing Strategy

Overview

Marketing strategy is the allocation of scarce resources across channels to maximize pipeline and revenue. Not "what should we post?" — "given our ICP, budget, and stage, where does every dollar and hour go?"

This skill builds a complete marketing operating plan: channel mix, budget allocation by funnel stage, content strategy, demand generation, brand building, and measurement. The output is a strategy document, not a list of tactics.

Authoritative Foundations

  • Eugene Schwartz — Breakthrough Advertising — Match the message to the market's awareness level, from unaware to most aware.
  • Les Binet and Peter Field — The Long and the Short of It — Balance long-term brand building with short-term activation instead of spending only on conversion.
  • Byron Sharp — How Brands Grow — Grow by increasing mental and physical availability with the whole category, not only loyal buyers.
  • Joe Pulizzi — Content Inc. (content tilt) — Find a content niche where you can be the leading voice before expanding.

When to Use

  • "Build our marketing strategy"
  • "Plan our marketing for Q1"
  • "Allocate marketing budget"
  • "Which channels should we invest in?"
  • "Design a demand generation engine"
  • "Create a marketing operating plan"
  • "What should marketing own vs sales?"

Step-by-Step Process

Phase 1: Channel Mix by Stage

Stage<$1M ARR$1-10M ARR$10M+ ARR
PrimaryFounder-led content + outboundContent + paid + eventsBrand + multi-channel
ContentLinkedIn (founder), blogBlog, newsletter, webinarsEditorial, video, podcast
PaidNone (too early)LinkedIn + Google (test)LinkedIn + Google + Meta + programmatic
EventsNone1-2 conferences/yearOwned events + major conferences
PR/MediaPodcast guestingTrade publicationsTier 1 media + analyst relations
PartnersNoneIntegration partnersFull partner ecosystem

Phase 2: Budget Allocation

Marketing budget as % of ARR:

  • <$1M ARR: 20-40% (investment mode, founder-led)
  • $1-5M ARR: 15-25%
  • $5-20M ARR: 10-20%
  • $20M+ ARR: 8-15%

Allocate across channels:

ChannelSeed/<$1MGrowth/$1-10MScale/$10M+
Content & SEO40%30%25%
Paid acquisition0%25%30%
Events & field10%15%20%
Brand & PR5%10%15%
Product marketing15%10%5%
Tools & ops30%10%5%

Phase 3: Demand Generation Architecture

Top of funnel (awareness): Content marketing, paid social, PR, events. Goal: reach ICP, generate traffic and brand searches. Metric: traffic, brand search volume, social following.

Middle of funnel (consideration): Webinars, case studies, comparison pages, gated content. Goal: capture contact information, educate buyer. Metric: MQLs, email subscribers, content downloads.

Bottom of funnel (conversion): Demo requests, free trials, sales outreach. Goal: create sales-qualified opportunities. Metric: pipeline generated, opportunities created.

Post-funnel (expansion): Customer marketing, advocacy, referrals. Goal: expansion revenue and word-of-mouth. Metric: NRR, referral revenue.

Phase 4: Brand Building

Brand compounds. It's the reason someone chooses you over a cheaper competitor.

Brand assets to build:

  • Distinctive point of view (not "we're the best" — "here's what we believe that others don't")
  • Original research and data (your unique data is your best content)
  • Customer stories (named, specific, quantified)
  • Executive thought leadership (founder brand = company brand at <$10M ARR)
  • Visual identity and design system (consistent across every touchpoint)

Measurement: Brand search volume, direct traffic growth, win rate on competitive deals, inbound demo request growth.

Phase 5: Marketing-Sales Handoff

Marketing generates demand. Sales converts it. The handoff is where most companies break.

MQL definition (marketing side): ICP fit confirmed + meaningful engagement (content download, webinar attendance, pricing page visit). Clear criteria, not "they seem interested."

SQL definition (sales side): MQL + explicit buying signal (demo request, trial sign-up, contact form with budget information).

SLA: MQL → first sales touch within 15 minutes (speed-to-lead is the single biggest conversion lever). Track: MQL→SQL conversion rate, SQL→ opportunity rate, marketing-sourced pipeline.

Output Format

Marketing strategy document with: channel mix by stage, budget allocation, demand generation architecture, brand building plan, content calendar (quarterly), marketing-sales SLA, and KPI dashboard.

Quality Check

  • Channel mix appropriate for ARR stage
  • Budget allocation by channel with rationale
  • MQL and SQL definitions documented and agreed upon
  • Marketing-sales SLA defined and measured
  • Brand building plan (not just demand gen)
  • Measurement framework: pipeline and revenue, not just leads

Common Pitfalls

  1. No strategy, just tactics. "Let's post on LinkedIn and run some ads" without a channel mix and budget is a tactic list, not a strategy.

  2. Too many channels too early. A $1M ARR company doesn't need events, programmatic, and TikTok. 2-3 channels done well beats 8 channels done poorly.

  3. Marketing-sales misalignment. Marketing measured on MQLs, sales measured on closed revenue. Different incentives, different behaviors. Align on pipeline generated, not leads.

  4. Brand as an afterthought. Brand is the thing that makes outbound reply rates go up, paid CPC go down, and win rates increase. Invest before you need it.

Execution Artifacts

  • references/framework-notes.md — named frameworks, citation anchors, and operating assumptions
  • templates/output-template.md — copy-paste deliverable structure for the user
  • scripts/check-output.py — local checklist validator for required sections This skill includes lightweight artifacts the agent can load on demand: Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.

Related Skills

  • paid-advertising: Paid channel execution
  • content-marketing: Content strategy and SEO
  • content-distribution: Multi-channel content distribution
  • attribution: Marketing ROI measurement

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Marketing Strategy AI skill do?

Build complete B2B marketing strategies — channel mix, budget allocation, content strategy, demand generation, brand building, and measurement framework. Use when building a marketing plan, allocating marketing budget, designing multi-channel campaigns, or creating a marketing operating system. Triggers on: "marketing strategy", "marketing plan", "demand generation", "brand strategy", "marketing budget", "channel strategy", or any marketing planning request.

Why use Marketing Strategy on TypingMind?

Because you install it once and use it with any model. Marketing Strategy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Marketing Strategy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeadMagic/gtm-skills/tree/main/skills/analytics/marketing-strategy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Marketing Strategy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Marketing Strategy?

As many as you like. As long as a model supports skills, you can use Marketing Strategy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Marketing Strategy AI skill free?

Yes. It is published on GitHub by LeadMagic under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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