How to Use KDROI - Complete Guide
Learn how to find profitable keywords and generate actionable site building plans in minutes.
Quick Start in 3 Steps
1. Upload CSV
Export keyword data from Semrush, Ahrefs, or any SEO tool. Upload the CSV/XLSX file.
2. Analyze Keywords
View KDROI scores, filter by difficulty, and identify the best opportunities.
3. Generate Plan
Get a complete site building plan with revenue projections and content outlines.
Understanding KDROI
KDROI = (Volume × CPC) / (KD + 1)
KDROI (Keyword Difficulty Return on Investment) combines search volume, cost-per-click, and keyword difficulty into a single score that represents profitability potential.
KDROI Score Ranges
Uploading Your Data
Required Columns
Your CSV file must include these columns (we auto-detect common variations):
- Keyword - The search keyword text
- Volume - Monthly search volume (also: Search Volume)
- KD - Keyword Difficulty 0-100 (also: Keyword Difficulty)
- CPC - Cost per click in USD
Exporting from SEO Tools
Semrush
Keyword Magic Tool → Select keywords → Export → CSV
Ahrefs
Keywords Explorer → Export → Full export CSV
Understanding Site Type Judgment
Our AI analyzes your keyword and recommends the best site type to build:
Tool Site
Best for keywords containing: calculator, converter, generator, checker, tool, etc.
Example: "mortgage calculator", "unit converter", "password generator"
Content Site
Best for informational queries: how to, guide, tutorial, review, comparison, etc.
Example: "how to invest in stocks", "best running shoes 2025"
Hybrid Site
When the keyword could benefit from both tool functionality and content.
Example: "calorie counter" (tool + diet content)
Tips for Success
Focus on KDROI > 1000
Keywords with KDROI above 1000 offer the best balance of effort vs. reward.
Balance KD and Volume
High volume with high KD requires significant SEO effort. Start with KD under 30 for quick wins.
Start with Low Competition
Build domain authority with easy keywords first, then target harder ones.
Use Word Root Filtering
Filter by word roots to find related keyword clusters for content planning.