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Ad Campaign Management

Community
manojbajaj95
ad-campaign-management

Use when creating, managing, or optimizing paid advertising campaigns across any platform. Covers ad copy generation, ad creative strategy, campaign management, and competitive intelligence. Triggers on: ad copy, ad creative, paid ads, paid advertising, Facebook ads, LinkedIn ads, Google ads, Meta ads, ad campaign, ad strategy, ad testing, competitive ads, competitor ads, ad library, ad analysis, ad creative generation, campaign management, ROAS, CPC, CTR. Use this skill whenever the user mentions ads, paid channels, ad campaigns, ad copy, ad performance, or wants to analyze competitor advertising.

Overview

Publishermanojbajaj95
Repositoryclaude-gtm-plugin
Skill namead-campaign-management
Stars
109
Forks
34
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Ad Campaign Management 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/ad-campaign-management
  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/ad-campaign-management .claude/skills/ad-campaign-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ad Campaign Management 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 Ad Campaign Management 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 Ad Campaign Management 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.

Ad Campaign Management

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.

End-to-end paid advertising: write ad copy, develop creative strategy, manage campaigns, and analyze competitor ads.

Use the Workspace Context above first; only ask for ad-platform inputs not covered there.


1. Ad Copy Creation

Platform Constraints

PlatformElementLimit
Google Ads (RSA)Headline30 chars × 15
Google Ads (RSA)Description90 chars × 4
Meta (FB/IG)Primary text125 chars visible
Meta (FB/IG)Headline40 chars
LinkedInIntro text150 chars recommended
LinkedInHeadline70 chars recommended
TikTokAd text80 chars recommended
Twitter/XTweet280 chars

For full format specs, see references/platform-specs.md.

Copywriting Frameworks

AIDA — Attention → Interest → Desire → Action PAS — Problem → Agitate → Solution 4Ps — Promise → Picture → Proof → Push Before-After-Bridge — Current pain → Desired state → Your solution

Headlines That Work

  • Specific over vague: "Cut reporting time 75%" not "Save time"
  • Benefits over features: "Ship code faster" not "CI/CD pipeline"
  • Include numbers when possible: "3x faster," "in 5 minutes," "10,000+ teams"
  • Each RSA headline must stand alone — they're combined randomly
  • Include at least: 1 keyword headline, 1 benefit headline, 2–3 CTA headlines

Platform Best Practices

Google: Include keywords; use numbers/stats; power words (Free, Proven, New) Meta: Hook in first 3 words; ask questions; social proof performs well; emojis B2C only LinkedIn: Professional but not boring; lead with value; stats resonate with B2B TikTok: Casual/authentic tone; hook in 1–2 seconds; strong CTA at end

A/B Testing Variables

  • Headlines: Question vs. statement; benefit-led vs. feature-led; with/without numbers
  • Primary text: Short vs. long; problem-focused vs. solution-focused; with/without social proof
  • CTAs: Direct ("Buy Now") vs. soft ("Learn More"); benefit-based vs. action-based
  • Protocol: One variable at a time; min 7 days or 1,000 impressions; 95% significance before declaring winner

Output Format

Organize by angle with character counts:

## Angle: [Pain Point — Manual Reporting]

### Headlines (30 char max)
1. "Stop Building Reports by Hand" (29)
2. "Reports Done in 5 Min" (21)

### Descriptions (90 char max)
1. "Marketing teams save 10+ hours/week. Start free." (49)

Offer CSV format for 10+ variations:

csv
headline_1,headline_2,description_1,platform
"Stop Manual Reporting","Automate in 5 Min","Save 10+ hrs/week. Start free.","google_ads"

2. Creative Strategy

Define Angles First

Before writing copy, establish 3–5 distinct angles (different reasons someone clicks):

CategoryExample
Pain point"Stop wasting time on X"
Outcome"Achieve Y in Z days"
Social proof"Join 10,000+ teams who..."
Curiosity"The secret top companies use"
Comparison"Unlike X, we do Y"
Identity"Built for [specific role]"
Contrarian"Why [common practice] doesn't work"

Generate Variations Per Angle

Vary: word choice, specificity (numbers vs. general), tone (direct/question/command), structure (short punch vs. full benefit).

Iterating from Performance Data

  1. Analyze winners — identify winning themes, structures, word patterns by CTR/CVR/ROAS
  2. Analyze losers — find what falls flat (too generic, wrong tone, too long)
  3. Generate new creative — double down on winning themes, test 1–2 new angles, avoid loser patterns
  4. Document iterations:
## Iteration Log
- Round: [N] | Date: [date]
- Top performers: [list with metrics]
- Winning patterns: [summary]
- New angles tested: [list]
- Angles retired: [list]

Generating Ad Visuals

For image and video creative, use AI tools. See references/generative-tools.md for:

  • Image generation: Flux, Ideogram, Nano Banana Pro (Gemini) for static ad images
  • Video generation: Veo, Kling, Runway, Sora, Seedance, Higgsfield
  • Voice/audio: ElevenLabs, OpenAI TTS for voiceovers
  • Code-based video: Remotion for templated, data-driven video at scale

Recommended workflow: Generate hero creative with AI → build Remotion templates from winners → batch-produce variations at scale.


3. Campaign Management

Key Metrics

TypeMetrics
CostCPM, CPC, CPL, CPA/CAC
PerformanceCTR, CVR, ROAS, LTV:CAC

Campaign Structure

Google Ads: Account → Campaign (budget, geo) → Ad Group (keyword theme) → Keywords + Ads

Meta Ads: Campaign (objective) → Ad Set (audience, placement, budget) → Ads (creative, copy)

Bidding strategies:

  • Target CPA — optimize for conversions at target cost
  • Target ROAS — optimize for conversion value
  • Maximize conversions — spend budget for max conversions
  • Manual — full control, time-intensive

Audience Targeting

Meta:

  • Core: demographics, interests, behaviors, location
  • Custom: website visitors, customer lists, engagement audiences
  • Lookalike: based on high-value customers, 1–10% similarity

LinkedIn:

  • Company: industry, size, name
  • Job: title, function, seniority
  • Professional: skills, groups, interests

Optimization Cadence

Daily: Budget pacing, cost metrics, major anomalies Weekly: CTR/CVR trends, top/bottom performers, search term review (Google) Monthly: Overall ROAS/ROI, audience performance, creative fatigue, strategic adjustments

Quick Optimization Wins

  1. Pause underperforming ads
  2. Increase bids on top performers
  3. Add negative keywords (Google)
  4. Refine audience targeting
  5. Refresh fatigued creative

Budget Allocation

  • Testing phase: 10–20% on new ideas
  • Proven performers: 60–70% of budget
  • Retargeting: 10–20% of budget
  • Scaling: increase budget gradually (max 20%/week) on winning audiences/creative

4. Competitive Intelligence

Use ad libraries (Facebook Ad Library, LinkedIn Ad Library) to extract and analyze competitor ads.

Extraction Process

Extract all current ads from [Competitor] on Facebook Ad Library
Scrape ads from [Company A], [Company B], [Company C] — compare approaches
Get LinkedIn ads from [Competitor] — analyze their B2B positioning

Analysis Output

For each competitor, deliver:

# [Competitor] Ad Analysis

## Overview
- Total ads: [N] active | Primary themes: [breakdown]
- Ad formats: [static/video split] | CTA patterns: [list]

## Key Problems They're Highlighting
1. [Pain point] ([N] ads) — Copy: "..." — Why it works: [reason]

## Successful Creative Patterns
- Pattern 1: [description + frequency]
- Pattern 2: [description + frequency]

## Best Headlines
1. "[headline]" → [why it works]

## Recommendations for Your Ads
1. [Actionable insight based on their patterns]

What to Analyze

  • Messaging: What problems they emphasize, how they position vs. competitors
  • Creative patterns: Visual styles, video vs. static, layout trends
  • Copy formulas: Headline structures, CTA patterns, length and tone
  • Campaign strategy: Seasonal campaigns, retargeting patterns, feature announcements

Competitive Intelligence Workflows

Ad Campaign Planning: Extract competitor ads → identify patterns → note messaging gaps → draft test variations

Positioning Research: Analyze 5 competitors → map their positioning → find underserved angles → develop differentiated messaging

Trend Tracking: Compare competitor ads across quarters to spot messaging evolution

Legal & Ethical

✓ Use for research and inspiration only ✓ Adapt patterns — don't copy ads directly ✓ Respect intellectual property ✗ Don't plagiarize copy or steal designs


5. References

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 Ad Campaign Management AI skill do?

Use when creating, managing, or optimizing paid advertising campaigns across any platform. Covers ad copy generation, ad creative strategy, campaign management, and competitive intelligence. Triggers on: ad copy, ad creative, paid ads, paid advertising, Facebook ads, LinkedIn ads, Google ads, Meta ads, ad campaign, ad strategy, ad testing, competitive ads, competitor ads, ad library, ad analysis, ad creative generation, campaign management, ROAS, CPC, CTR. Use this skill whenever the user mentions ads, paid channels, ad campaigns, ad copy, ad performance, or wants to analyze competitor adve...

Why use Ad Campaign Management on TypingMind?

Because you install it once and use it with any model. Ad Campaign Management 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 Ad Campaign Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/manojbajaj95/claude-gtm-plugin/tree/main/skills/ad-campaign-management. 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 Ad Campaign Management?

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 Ad Campaign Management?

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

Is the Ad Campaign Management 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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