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Marketing Automation

Community
manojbajaj95
marketing-automation

Use this skill when setting up marketing automation in HubSpot, Marketo, email sequences, lead scoring, and workflows.

Overview

Publishermanojbajaj95
Repositoryclaude-gtm-plugin
Skill namemarketing-automation
Stars
109
Forks
34
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by manojbajaj95 on GitHub. Read the source before you install it.

Installation

Install the Marketing Automation 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/manojbajaj95/claude-gtm-plugin/tree/main/skills/marketing-automation
  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/manojbajaj95/claude-gtm-plugin.git /tmp/claude-gtm-plugin
mkdir -p .claude/skills
cp -r /tmp/claude-gtm-plugin/skills/marketing-automation .claude/skills/marketing-automation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Marketing Automation 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 Automation 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 Automation 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 Automation Expert

Workspace Context

Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.

Operating Contract

This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.

Marketing automation strategy and implementation across HubSpot, Marketo, ActiveCampaign, and similar platforms.


Platform Selection

PlatformBest ForComplexityCost
HubSpotSMB to Enterprise, all-in-oneMedium$$$–$$$$
MarketoEnterprise B2BHigh$$$$
ActiveCampaignSMB, strong automationLow–Medium$–$$
PardotSalesforce-native B2BMedium–High$$$$
MailchimpSmall business, email-firstLow$–$$

Selection criteria: CRM integration, email volume, workflow complexity, reporting depth, budget, team technical skill.


Lead Scoring Model

MQL threshold: 100 points. Decay: −10 points after 30 days of inactivity.

Behavioral Scoring

ActionPoints
Request demo+50
Pricing page visit+30
Case study download+25
Webinar attendance+25
Webinar registration+15
Content download+10
Email click+3 (max 5/day)
Email open+1 (max 3/day)
Blog visit+1 (max 5/day)
Unsubscribe−30
Email bounce−20
Spam complaint−100

Demographic Scoring

AttributePoints
C-Level title+25
VP title+20
Director+15
Manager+10
Target company size (200–1000)+20
Target industry+20
Primary market geography+15

Lead Grading (A–D)

  • A: Decision maker + target size + target industry + target geo → immediate sales follow-up
  • B: 3 of 4 criteria met → sales within 24 hours
  • C: 2 of 4 criteria met → nurture then handoff
  • D: 1 or fewer criteria → nurture only, no sales routing

Email Sequences

Welcome Series (6 emails over 14 days)

EmailTimingPurposeCTA
1ImmediatelyWelcome + quick win resourceDownload resource
2Day 2Pain point + case studyRead case study
3Day 4Product overview + benefitsSee how it works
4Day 7Exclusive gated contentDownload now
5Day 10Offer personalized helpSchedule a call
6Day 14Preference centerUpdate preferences

Exit conditions: demo requested, sales conversation started, unsubscribed.

Lead Nurture (score-triggered tracks)

TrackScore RangeCadenceFocus
Awareness50–692/weekEducational, industry trends
Consideration70–892–3/weekUse cases, ROI calculator, case studies
Decision90–993/weekFree trial, demo, competitive comparison

Re-engagement (90-day lapse trigger)

4-email sequence over 15 days: "We miss you" → "Is this goodbye?" → "Last chance offer" → "Goodbye for now" with easy re-subscribe. Outcomes: engaged → return to nurture | no action → sunset list.


Automation Workflows

Lead Routing Workflow

  1. Data enrichment (Clearbit/ZoomInfo) — wait 30 seconds
  2. Lead scoring + grading
  3. Check for existing account → route to account owner if yes
  4. Territory assignment (geography → company size → industry)
  5. Create follow-up task with SLA: A=15 min | B=2 hrs | C=24 hrs
  6. Notify rep via email + Slack
  7. Add to appropriate nurture track

Lifecycle Stage Automation

StageEntry TriggerKey Automations
SubscriberEmail opt-inWelcome series + newsletter
LeadForm submit OR score >20Enrich → nurture → sync CRM
MQLScore ≥100 OR demo requestSales alert + task + pause marketing
SQLSales qualified in CRMUpdate nurture + notify CS
OpportunityDeal createdPause outbound + enable deal-stage emails
CustomerDeal wonOnboarding sequence + remove from prospects
ChurnedCancellationWin-back sequence

Key Workflows to Build

1. Demo Request → Sales Handoff: Form submit → enrich → score/grade → create HubSpot deal → assign to rep → send confirmation email → start sales sequence.

2. Trial Signup → Activation: Signup → welcome email → onboarding checklist → day 3/7/14 milestone emails → conversion offer at day 14.

3. Event/Webinar: Registration → confirmation email → 3 reminders → post-webinar follow-up (attended) or recording offer (no-show) → add to nurture based on engagement.

4. Customer Onboarding: Won deal → CSM assignment notification → welcome email → onboarding checklist → check-in at 30/60/90 days → NPS survey at 90 days.


HubSpot Implementation

Campaign setup: Marketing → Campaigns → tag all assets (emails, landing pages, ads) with campaign ID.

UTM convention: utm_source={channel}&utm_medium={cpc|email|organic}&utm_campaign={id}&utm_content={variant}

Attribution model: W-shaped for hybrid PLG/sales-led (first touch + lead creation + close).

Lead scoring setup: Settings → Marketing → Lead Scoring. Set behavioral weights, demographic weights, and decay rules. Create MQL automation when score ≥100.

Reporting cadence: Daily review of MQLs/SQLs. Weekly channel ROI. Monthly win/loss trends.

Frequently asked questions

What does the Marketing Automation AI skill do?

Use this skill when setting up marketing automation in HubSpot, Marketo, email sequences, lead scoring, and workflows.

Why use Marketing Automation on TypingMind?

Because you install it once and use it with any model. Marketing Automation 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 Automation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/manojbajaj95/claude-gtm-plugin/tree/main/skills/marketing-automation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Marketing Automation?

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 Automation?

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

Is the Marketing Automation AI skill free?

Yes. It is published on GitHub by manojbajaj95 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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