Verified:GitHub

demand-research

Analyze search query data from advertising platforms to identify missed demand and wasteful spending.

13|5|Updated Mar 12, 2026

Search Tags:#keyword analysis #budget optimization #negative keywords #demand research #search semantics #seasonal forecasting

Ready to run

npx skills add https://github.com/awaik/direct-mcp-ai-project --skill demand-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: demand-research
Source: https://github.com/awaik/direct-mcp-ai-project/tree/main/.claude/skills/demand-research
Command: npx skills add https://github.com/awaik/direct-mcp-ai-project --skill demand-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and config (resource) components.

What problem does it solve?

This Skill helps you discover untapped market demand, identify wasted ad spend, and optimize your advertising budget by analyzing search queries and seasonal trends.

Core Features & Use Cases

Missed Demand Analysis: Find keywords that drive conversions but aren't yet targeted, and identify wasteful queries.
Seasonal Budget Forecasting: Predict optimal budget allocation across months based on historical search volume trends.
Intent Verification: Determine if search queries are commercial or informational to refine targeting.
Use Case: A marketing manager wants to increase campaign ROI. They use this Skill to analyze their search query data, identify new high-converting keywords to add, and add wasteful queries as negative keywords, while also adjusting their monthly budget based on seasonal demand forecasts.

Quick Start

Use the demand-research skill to analyze search queries from 'search_queries.csv' and identify opportunities and waste.

Frequently Asked Questions about demand-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I find missed demand opportunities and wasteful spending in my ad campaigns?▼

Seasonal budget forecasting uses historical search volume data to predict optimal budget allocation across months. This approach helps adjust monthly ad spend based on seasonal demand trends.

Can I verify if search queries are commercial or informational to refine ad targeting?▼

To analyze search queries for demand research, use a CSV file like 'search_queries.csv' containing your platform data. The skill processes this input to identify new keyword opportunities and wasteful spending.

Does this demand research tool integrate with Wordstat and direct ad platform APIs?▼

Yes, the demand research process integrates with Wordstat and direct ad platform APIs. This integration provides actionable insights by pulling historical search volume data directly into the analysis.

What is the best way to optimize ad spend using search semantics and negative keywords?▼

The best way to optimize ad spend using search semantics is to analyze query data and apply negative keywords. This blocks wasteful queries while identifying untapped demand to maximize campaign ROI.