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Guide for Restaurant Location Assessment with TargomoLOOP

Purpose of This Guide

This guide provides a comprehensive overview of how to use TargomoLOOP to assess and validate potential locations for restaurant or food outlet expansion. Whether you're evaluating a single site or comparing multiple opportunities, this step-by-step guide will help you make data-driven location decisions.

1. When to Use TargomoLOOP

Use TargomoLOOP when:

  • You have specific locations in mind and want to assess their viability
  • You want to compare multiple potential sites against each other
  • You need to evaluate performance and revenue potential based on business KPIs
  • You want to find available commercial properties suitable for restaurants

2. Key Steps to Use the Platform

Step 1: Set Up Your Restaurant Network

Add your existing restaurant locations

  • Import your current portfolio of restaurants
  • Upload locations via CSV file or manually pin them on the map

Step 2: Add Competitive landscape

Map competitors and points of interest

  • Add competitor restaurant locations to understand market saturation
  • Include relevant POIs such as:
    • Public transport stations (metro, bus, train)
    • Shopping centers and retail districts
    • Hotels and tourist attractions
    • Universities and educational institutions
    • Residential complexes

Step 3: Create Catchment Areas

Define trade areas for analysis

  • Create catchments (e.g., 5-minute walk, 10-minute walk, 5-minute drive)
  • Customize catchments based on your restaurant format:
    • QSR/Fast casual: eg. 5-10 minute walk
    • Casual dining: eg. 10-15 minute walk or 5-10 minute drive
    • Fine dining: eg. 15-20 minute drive
  • View catchments of individual selected sites or your entire network

Step 4: Import and Visualize Data Layers

Analyze location characteristics with key data

Restaurant clients frequently use these data layers to evaluate locations:

Demographic Data:

  • Population density
  • Age distribution
  • Household composition
  • Income levels and purchasing power

Economic Data:

  • Spending power index
  • Disposable income

Mobility Data:

  • Footfall volumes (daily, weekly patterns)
  • Pedestrian traffic by time of day
  • Tourist vs. local visitor split

See all the available datasets here - https://app.targomo.com/data-explorer/


Visualize these data layers on the map with color-coded heat maps and overlays to quickly identify opportunities.

Step 5: Identify White Spaces

Find underserved areas with high potential

  • Enable network-wide catchment visualization to see your current coverage
  • Use scoring heat maps to identify gaps where there is demand but limited supply
  • Look for areas with:
    • High footfall but low competitor density
    • Strong demographics but no brand presence

Step 6: Identify Success Factors

Understand what makes your locations perform

  • Use correlation analysis to identify factors correlating with success.

Step 7: Forecast Performance with GeoAI

Predict revenue before you invest

  • Use GeoAI to analyze potential sites and forecast performance

Learn more about GeoAI →

Step 8: Simulate Network Impact

Test scenarios before committing

  • Simulate the opening of a new location to analyze its impact
  • Understand potential cannibalization of existing stores
  • See how the new site affects:
    • Overall network coverage
    • Individual store performance
    • Impact to overall network
  • Test multiple locations to find the optimal expansion strategy

3. Best Practices for Location Analysis

Quick Comparison Checklist

When evaluating potential sites, consider these key questions:

✓ Does the location meet minimum footfall requirements?
✓ Is the demographic profile aligned with your target customer?
✓ How does it compare to your top-performing locations?
✓ What is the competitive density within the catchment?
✓ Are there any cannibalization risks with existing stores?
✓ What is the predicted ROI based on GeoAI forecasts?

Common Pitfalls to Avoid

  • Over-reliance on single metrics: Look at multiple data layers together, not in isolation
  • Ignoring temporal patterns: Check footfall by time of day and day of week
  • Forgetting about seasonality: Consider tourist patterns and seasonal variations
  • Overlooking accessibility: Ensure the location is easy to reach by your target customers
  • Skipping cannibalization analysis: Always simulate impact on existing network

4. Support Resources

  • GeoAI Documentation: Learn more - https://info.targomo.com/targomoloop/help/whats-geo-ai-and-how-to-use-it-in-loop
  • Available Data sets: https://app.targomo.com/data-explorer/