What metrics are included in the final opportunity score?

The final score is a weighted average of the Market Gap (40%), Demand Score (25%), Growth Potential (20%), and Affordability/Rent Index (15%).

Does it account for existing business locations?

The skill is configured to automatically exclude areas where branches already exist, such as Tyre, Jnah, and Batroun, ensuring recommendations focus only on new expansion opportunities.

Can I filter recommendations for specific regions?

Yes, you can pass parameters to filter results by specific governorates like Beirut or Mount Lebanon, or set a minimum population threshold for the analysis.

How does this skill determine the best location?

It uses a Polynomial Ridge Regression model trained on Lebanese demographic data to predict expected competitor counts; locations where actual competitors are fewer than predicted are flagged as high-opportunity market gaps.

Lebanon Market Gap Analyzer

Name: Lebanon Market Gap Analyzer
Author: sabaronnie

bysabaronnie

0•

Data Science & ML

Analyzes Lebanese market gaps using Ridge Regression to recommend optimal locations for new business branches based on demographic and competitor data.

The Lebanon Market Gap Analyzer is a data-driven expansion tool that utilizes Polynomial Ridge Regression to identify the most underserved areas in Lebanon. By evaluating 24 distinct regions across metrics like population density, social activity, traffic indices, and current competitor saturation, the skill provides a weighted opportunity score for strategic site selection. It helps businesses move beyond guesswork by calculating the delta between expected and actual market capacity, allowing for precise targeting of high-growth zones while filtering for specific governorates or population thresholds.

Key Features

01Real-time competitor density comparison against predicted market capacity

02Geospatial filtering by Lebanese governorate and population density

03Comprehensive scoring based on demand, affordability, and growth potential

04Automated exclusion of existing branch footprints to find new opportunities

050 GitHub stars

06ML-powered market gap analysis using Polynomial Ridge Regression

Use Cases

01Identifying the most profitable Lebanese areas for retail or F&B expansion

02Analyzing competitor saturation vs. population demand in specific governorates

03Generating data-backed site selection reports for corporate stakeholders

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sabaronnie/ai-driven-cronut-ceo-agent conut-location

For use in Claude.ai and ChatGPT

Key Features

01Real-time competitor density comparison against predicted market capacity

02Geospatial filtering by Lebanese governorate and population density

03Comprehensive scoring based on demand, affordability, and growth potential

04Automated exclusion of existing branch footprints to find new opportunities

050 GitHub stars

06ML-powered market gap analysis using Polynomial Ridge Regression

Use Cases

01Identifying the most profitable Lebanese areas for retail or F&B expansion

02Analyzing competitor saturation vs. population demand in specific governorates

03Generating data-backed site selection reports for corporate stakeholders

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add sabaronnie/ai-driven-cronut-ceo-agent conut-location

For use in Claude.ai and ChatGPT