AgentSkillsCN

Evaluate Franchise Opportunity

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SKILL.md

Skill: Evaluate Franchise Opportunity

Domain

retail

Description

Evaluates franchise investment opportunities analyzing unit economics, territory potential, and franchisor track record for investment decisions.

Tags

franchise, investment, retail, due-diligence, unit-economics

Use Cases

  • •Franchise investment analysis
  • •Territory evaluation
  • •Unit economics modeling
  • •Franchisor assessment

Proprietary Business Rules

Rule 1: Unit Economics Validation

Analysis of per-unit profitability and payback period.

Rule 2: Territory Potential Assessment

Market size and competitive density evaluation.

Rule 3: Franchisor Track Record

Historical performance and franchisee satisfaction analysis.

Rule 4: Investment Return Modeling

IRR and cash-on-cash return projections.

Input Parameters

  • •opportunity_id (string): Opportunity identifier
  • •franchise_info (dict): Franchise concept details
  • •territory_data (dict): Market demographics
  • •investment_terms (dict): Investment requirements
  • •unit_financials (dict): Unit-level economics
  • •franchisor_data (dict): Franchisor information

Output

  • •investment_score (float): Overall opportunity rating
  • •unit_economics (dict): Per-unit financial analysis
  • •territory_assessment (dict): Market evaluation
  • •return_projections (dict): Financial return estimates
  • •risk_factors (list): Investment risks identified

Implementation

The evaluation logic is implemented in franchise_evaluator.py and references data from CSV files:

  • •category_benchmarks.csv - Reference data
  • •market_factors.csv - Reference data
  • •franchisor_standards.csv - Reference data
  • •projection_params.csv - Reference data
  • •evaluation_weights.csv - Reference data
  • •investment_thresholds.csv - Reference data
  • •royalty_benchmarks.csv - Reference data
  • •parameters.csv - Reference data.

Usage Example

python
from franchise_evaluator import evaluate_franchise

result = evaluate_franchise(
    opportunity_id="FRN-001",
    franchise_info={"brand": "FastServe", "category": "QSR", "units_nationwide": 500},
    territory_data={"population": 150000, "median_income": 65000, "competitors": 3},
    investment_terms={"franchise_fee": 45000, "buildout": 350000, "royalty_pct": 0.06},
    unit_financials={"avg_revenue": 1200000, "avg_ebitda_margin": 0.15},
    franchisor_data={"years_franchising": 15, "franchisee_satisfaction": 85}
)

print(f"Investment Score: {result['investment_score']}")

Test Execution

python
from franchise_evaluator import evaluate_franchise

result = evaluate_franchise(
    opportunity_id=input_data.get('opportunity_id'),
    franchise_info=input_data.get('franchise_info', {}),
    territory_data=input_data.get('territory_data', {}),
    investment_terms=input_data.get('investment_terms', {}),
    unit_financials=input_data.get('unit_financials', {}),
    franchisor_data=input_data.get('franchisor_data', {})
)