Multi-Location LTV Comparison Tool

What is Multi-Location LTV Comparison?

Multi-location LTV comparison allows franchise owners, regional managers, and multi-site business operators to understand how customer value differs across their locations. Instead of analyzing each location separately, this tool provides a unified view of customer lifetime value, retention, and user metrics across all your sites.

How does this tool work?

Our multi-location comparison tool makes it easy to analyze all your locations at once:

1. Upload CSV files for each location (or use demo data to explore)
2. Automatic column detection identifies date, customer ID, and revenue fields
3. Side-by-side LTV comparison at 1, 3, 6, 12, and 24-month intervals
4. Monthly user metrics showing new, returning, and total active customers
5. Individual location drill-down with detailed cohort analysis

What data format do I need?

Each location’s CSV file needs three columns:

Column	Description	Example
date	Transaction date	2024-01-15
user_id	Unique customer ID	cust_12345
net_revenue	Transaction amount	49.99

ClassBug users: The tool automatically detects ClassBug export format and creates customer IDs from First Name + Last Name fields.

What metrics does the comparison show?

Summary Comparison Table

• 1-Month LTV: Early customer value indicator
• 3-Month LTV: Short-term engagement metric
• 6-Month LTV: Medium-term customer value
• 12-Month LTV: Annual customer value
• 24-Month LTV: Long-term loyalty indicator
• Total Cohorts: Number of monthly cohorts analyzed

Monthly User Metrics

For any selected month, see across all locations:

• New Users: First-time customers that month
• Returning Users: Customers from previous cohorts
• Total Active: All active customers

Visual Comparison

Bar charts make it easy to spot which locations are outperforming and which need attention.

Individual Location Analysis

Drill down into each location to see:

• Retention curves over time
• Cumulative LTV curves
• Detailed cohort performance tables

How many locations can I compare?

You can compare up to 10 locations simultaneously. Each location is assigned a unique color for easy identification across all charts and tables.

Is my data secure?

Absolutely. All calculations run locally in your browser using Pyodide (Python compiled to WebAssembly). Your transaction data:

• Never leaves your computer
• Is never sent to any server
• Is not stored anywhere

What insights can I gain from multi-location comparison?

Identify Top Performers

See which locations generate the highest customer lifetime value and study what they’re doing differently.

Spot Underperformers Early

Low LTV at certain locations might indicate issues with:

• Customer experience
• Pricing strategy
• Staff training
• Marketing effectiveness

Optimize Resource Allocation

Use data to decide where to invest in marketing, staffing, and improvements.

Standardize Best Practices

When you identify high-performing locations, implement their practices across all sites.

Compare New vs. Established Locations

Understand how new locations are ramping up compared to mature ones.

How do I interpret the retention curves?

Retention curves show what percentage of customers remain active over time:

• Steep early drop: May indicate onboarding or first-experience issues
• Gradual decline: Normal pattern for most businesses
• Flat tail: Strong loyal customer base

Comparing curves across locations helps identify where customers are being lost.

What’s the difference between new and returning users?

• New Users: Customers making their first purchase in that month (cohort_index = 0)
• Returning Users: Customers who first purchased in a previous month (cohort_index > 0)

A healthy location should have a balance of both—new users for growth and returning users for stability.

Can I use this for seasonal analysis?

Yes! Use the month selector to compare user metrics across the same period (e.g., comparing December performance across all locations) or track how each location performs during peak seasons.

Tips for Multi-Location Analysis

Ensure Data Consistency

Use the same date range and data export process for all locations to ensure fair comparisons.

Consider Location Age

Newer locations may not have 12 or 24-month LTV data—this is normal.

Look at Trends, Not Just Numbers

A location with lower absolute LTV but improving trend may be more promising than a high-LTV location that’s declining.

Account for Market Differences

Urban vs. suburban, demographic differences, and competition levels all affect LTV—use this tool as one input, not the only decision factor.