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  1. Home
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  3. Marketing Demand Acquisition
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Marketing Demand Acquisition

Multi-channel demand generation, paid media optimization, SEO strategy, and partnership programs for Series A+ startups. Includes CAC calculator, channel playbooks, HubSpot integration, and international expansion tactics. Use when planning demand generation campaigns, optimizing paid media, building SEO strategies, establishing partnerships, or when user mentions demand gen, paid ads, LinkedIn ads, Google ads, CAC, acquisition, lead generation, or pipeline generation.

Alireza Rezvani

Core Features

Ready to Use

Quick integration into your workflow with minimal setup

Community Verified

Active open-source community with continuous updates

Completely Free

MIT/Apache licensed for commercial and personal use

Flexible Extension

Customizable and extendable based on your needs

How to Use

1Get Skill File

Download or copy the skill file from the source repository

2Install to Claude

Place the skill file in Claude's skills directory (usually ~/.claude/skills/)。

3Start Using

Restart Claude or run the reload command to load the skill

Tip: Read the documentation and code carefully before first use to understand functionality and permission requirements

Related Tags

#automation#python#testing

Technical Information

Author
Alireza Rezvani
Category
Development
File Size
32.99 KB
Source Repository
alirezarezvani__claude-skills
Metadata
Includes YAML metadata
License
MIT

All Skills from open-source community, preserving original authors' copyrights

alirezarezvani__claude-skills/marketing-skill/marketing-demand-acquisition/skill.md

Why Choose This Skill

Proven benefits and measurable impact

10x

Faster Data Access

Save time with AI-ready datasets, skipping manual preprocessing.

30%

Improved Model Accuracy

Boost predictions with curated, high-quality therapeutic data.

5x

Reduced R&D Costs

Lower expenses by avoiding redundant data collection efforts.

Use Cases

Perfect for these scenarios

🔬

Drug Discovery Research

Access curated datasets for ADME, toxicity, and DTI predictions.

📊

ML Model Benchmarking

Evaluate model performance using standardized benchmarks and splits.

🧪

Pharmacological Prediction

Leverage molecular oracles for therapeutic ML insights.

🚀

Accelerate R&D

Skip data prep and focus on building ML models for drug discovery.

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