How to Use Sales by Location in Amazon: Step-by-Step Tutorial

Discover where your customers are located and unlock powerful insights to optimize your Amazon business strategy with geographic sales analysis.

Introduction to Sales by Location Analysis

Understanding where your Amazon customers are located is one of the most powerful yet underutilized insights available to sellers. Geographic sales analysis reveals patterns that can transform how you approach inventory management, advertising spend, fulfillment strategies, and market expansion.

When you analyze sales by location, you're answering critical business questions: Are your products resonating in urban or rural areas? Which states generate the highest revenue? Should you adjust your FBA vs FBM strategy based on regional performance? Where should you focus your advertising budget for maximum ROI?

This tutorial will walk you through the complete process of accessing, analyzing, and acting on your Amazon sales location data. Whether you're running a small operation or managing a large catalog, understanding your geographic customer distribution provides actionable insights that directly impact your bottom line.

What You'll Learn

Prerequisites and Data Requirements

Before diving into geographic analysis, ensure you have the following prerequisites in place:

Required Access and Tools

Understanding Your Account Type

Your Amazon account type affects available data. Whether you're using Amazon Business vs Individual seller accounts, both provide access to geographic order data, though Business accounts may have additional reporting features. Individual sellers can still perform comprehensive location analysis using standard order reports.

Data Quality Checklist

Before proceeding, verify your data quality:

Step 1: Access Your Amazon Order Data

The foundation of geographic analysis is your raw order data from Amazon Seller Central. Here's how to access it:

1.1 Navigate to Reports Section

  1. Log into Amazon Seller Central at sellercentral.amazon.com
  2. Click on Reports in the top navigation menu
  3. Select Fulfillment from the dropdown menu
  4. Choose All Orders to access comprehensive order reports

1.2 Generate Your Order Report

Configure your report parameters to capture the data you need:

Report Type: All Orders
Date Range: Last 90 days (or your preferred timeframe)
Format: CSV or TXT
Include: Ship-to City, Ship-to State, Ship-to Postal Code
  1. Click Request Report
  2. Wait for Amazon to generate the report (typically 5-15 minutes)
  3. Download the completed report to your computer

1.3 Expected Data Structure

Your downloaded order report should contain these key fields for geographic analysis:

order-id | purchase-date | buyer-email | buyer-name | ship-city | ship-state | ship-postal-code | item-price | quantity-purchased
AMZ-001  | 2024-01-15    | [redacted]  | John D.    | Los Angeles | CA        | 90001           | 29.99      | 1
AMZ-002  | 2024-01-15    | [redacted]  | Sarah M.   | Austin      | TX        | 78701           | 45.50      | 2
AMZ-003  | 2024-01-16    | [redacted]  | Mike R.    | Seattle     | WA        | 98101           | 29.99      | 1

Verification Point: Ensure your downloaded file contains ship-city, ship-state, and ship-postal-code columns. If these are missing, return to Step 1.2 and verify your report configuration.

Step 2: Prepare Data for Geographic Analysis

Raw Amazon data requires cleaning and structuring before meaningful analysis can begin.

2.1 Clean Your Dataset

Open your downloaded CSV file and perform these cleaning steps:

  1. Remove Canceled Orders: Filter out any orders with status "Canceled" or "Pending"
  2. Standardize State Codes: Ensure all states use two-letter abbreviations (CA, NY, TX, etc.)
  3. Handle Missing Data: Remove or flag orders with incomplete shipping information
  4. Format Currency: Ensure all price fields are numeric (remove currency symbols)

2.2 Create Analysis Columns

Add calculated fields to enable deeper analysis:

// Example formula for total order value (in Excel/Google Sheets)
=item-price * quantity-purchased

// Group by region (example for categorizing states)
=IF(OR(ship-state="CA",ship-state="OR",ship-state="WA"),"West Coast",
  IF(OR(ship-state="NY",ship-state="MA",ship-state="CT"),"Northeast",
  IF(OR(ship-state="TX",ship-state="FL",ship-state="GA"),"Southeast","Other")))

2.3 Aggregate by Location

Create summary tables to see totals by geographic unit:

State | Order Count | Total Revenue | Average Order Value
CA    | 145         | $4,350.55    | $30.00
TX    | 98          | $3,234.20    | $33.00
NY    | 87          | $2,871.45    | $33.00
FL    | 76          | $2,432.80    | $32.01

Verification Point: Your aggregated data should show every state where you've made sales, with corresponding order counts and revenue totals. The sum of all state revenues should match your total revenue for the period.

Step 3: Analyze Geographic Distribution Patterns

Now that your data is prepared, it's time to extract meaningful insights from geographic patterns.

3.1 Identify Top Performing Regions

Sort your aggregated data by total revenue to identify your strongest markets:

  1. Create a bar chart showing top 10 states by revenue
  2. Calculate each state's percentage of total sales
  3. Identify concentration: Do 80% of sales come from 20% of states?

3.2 Analyze Population-Adjusted Performance

Raw numbers can be misleading. A state with high population naturally generates more orders. Calculate revenue per capita to find true opportunities:

// Revenue per 100,000 population
State | Revenue  | Population (millions) | Revenue per 100K
CA    | $4,350   | 39.5                 | $11.01
TX    | $3,234   | 29.1                 | $11.11
WY    | $245     | 0.58                 | $42.24  ← High performer!

This reveals markets like Wyoming or Vermont where your products resonate particularly well relative to population size, suggesting strong product-market fit worth exploring further.

3.3 Map Urban vs Rural Distribution

Use postal codes to categorize orders into urban, suburban, and rural areas. This analysis informs fulfillment method decisions and shipping cost optimization.

3.4 Seasonal and Temporal Patterns

Compare geographic distribution across different time periods:

Verification Point: You should be able to answer: What are my top 5 states by revenue? What percentage of orders come from urban areas? Are there any surprising geographic strongholds for my products?

Step 4: Use Advanced Analytics Tools

While spreadsheet analysis is valuable, specialized tools can unlock deeper insights with less manual effort.

4.1 Leverage Geographic Analysis Platforms

The Geographic Analysis tool automates much of the manual work described above and provides interactive visualizations:

4.2 Connect Multiple Data Sources

Combine geographic sales data with other metrics for comprehensive analysis:

Analysis Dimensions:
- Geographic location + advertising spend = Regional ROAS
- Geographic location + return rates = Quality issues by region
- Geographic location + delivery times = Fulfillment efficiency
- Geographic location + customer lifetime value = High-value markets

This multidimensional approach, similar to techniques used in statistical significance testing, helps you understand not just where customers are, but what makes each region unique.

4.3 Set Up Automated Monitoring

Configure alerts for significant geographic changes:

Step 5: Interpret Your Results and Take Action

Data without action is just numbers. Here's how to translate geographic insights into business improvements.

5.1 Optimize Fulfillment Strategy

If 60% of your orders come from the West Coast but you're using a single fulfillment center in Kentucky, you're likely facing higher shipping costs and longer delivery times for your core market.

Action Items:

5.2 Refine Advertising Targeting

Geographic data reveals where to concentrate (or reduce) advertising spend:

High Performance Regions (increase ad spend):
- States with high revenue per capita
- Growing markets (month-over-month increase)
- Low competition markets (high conversion rates)

Low Performance Regions (reduce or pause):
- High ad cost with low conversion
- Returns significantly above average
- Persistently low order values

5.3 Identify Expansion Opportunities

Look for adjacent markets showing promise:

5.4 Understand Competitive Dynamics

Weak performance in expected markets may indicate strong local competition:

5.5 Seasonal Planning

Different regions may show different seasonal patterns:

Verification Point: Create an action plan with at least three concrete changes you'll implement based on your geographic analysis. Each action should have a measurable outcome.

Step 6: Advanced Geographic Insights

Once you've mastered basic geographic analysis, these advanced techniques can provide competitive advantages.

6.1 Customer Lifetime Value by Region

Track not just first orders but repeat purchase rates by geography:

State | Avg First Order | Repeat Rate | Avg CLV
CA    | $32.00         | 34%         | $87.20
TX    | $35.00         | 28%         | $82.50
NY    | $38.00         | 41%         | $124.60 ← High CLV market

This reveals that while New York may not have the highest order volume, customers there have significantly higher lifetime value, justifying increased acquisition costs.

6.2 Product Performance by Region

Different products may resonate in different markets:

6.3 Competitive Intelligence

Compare your geographic distribution to category benchmarks:

6.4 Integrating External Data

Enhance your analysis by incorporating external datasets:

This approach aligns with modern AI-first data analysis methodologies that combine multiple data sources for comprehensive insights.

Automate Your Geographic Analysis

Manual geographic analysis provides valuable insights, but it's time-consuming and prone to errors. The Amazon Geographic Analysis tool from MCP Analytics automates this entire process:

Try Geographic Analysis Free →

Join thousands of Amazon sellers who have optimized their fulfillment, advertising, and inventory strategies using data-driven geographic insights.

Common Issues and Solutions

Even with careful execution, you may encounter challenges. Here are solutions to the most common problems:

Issue 1: Missing Geographic Data in Order Reports

Symptoms: Downloaded order report lacks ship-city, ship-state, or ship-postal-code columns.

Solution:

  1. Return to Reports → Fulfillment in Seller Central
  2. Select "Customize Report" before requesting
  3. Ensure all shipping address fields are checked
  4. Save as a custom report template for future use

Issue 2: Inconsistent State Abbreviations

Symptoms: Some states appear as "California" while others show "CA," splitting data.

Solution:

// Excel/Google Sheets formula to standardize
=IF(LEN(A2)>2, VLOOKUP(A2, StateConversionTable, 2, FALSE), A2)

// Or use find-and-replace:
Find: California → Replace: CA
Find: New York → Replace: NY
// Repeat for all full state names

Issue 3: Insufficient Data for Analysis

Symptoms: You have fewer than 50 orders, making patterns unreliable.

Solution:

Issue 4: PO Box Addresses Skewing Results

Symptoms: Large clusters of orders at single postal codes that don't match typical residential patterns.

Solution:

Issue 5: Seasonal Skew Distorting Patterns

Symptoms: Q4 data shows completely different geographic patterns than other quarters.

Solution:

Issue 6: Privacy Concerns with Customer Data

Symptoms: Uncertainty about handling customer shipping information.

Solution:

Issue 7: FBA vs FBM Orders Show Different Patterns

Symptoms: Geographic distribution differs significantly between fulfillment methods.

Solution:

Next Steps with Amazon Geographic Analysis

You've now learned how to extract, analyze, and act on geographic sales data from Amazon. Here's how to continue improving your geographic strategy:

Immediate Actions (This Week)

  1. Download Your Data: Pull your most recent 90 days of order data following Step 1
  2. Create Your First Analysis: Build a simple state-by-state revenue breakdown
  3. Identify One Opportunity: Find your single most actionable geographic insight
  4. Implement One Change: Adjust advertising, inventory, or targeting based on your findings

Ongoing Optimization (Monthly)

Advanced Techniques (Quarterly)

Continuous Learning

Geographic analysis is just one dimension of Amazon success. Continue developing your analytical capabilities:

Get Expert Help

If you're managing significant order volume or multiple marketplaces, the professional Geographic Analysis service provides:

Conclusion

Understanding where your Amazon customers are located transforms abstract sales data into actionable business intelligence. By following this step-by-step tutorial, you've learned how to extract geographic data from Amazon, analyze patterns, and implement optimizations that directly impact profitability.

The most successful Amazon sellers don't just react to overall sales numbers—they understand the nuanced patterns within their customer base. Geographic analysis reveals opportunities for fulfillment optimization, targeted advertising, inventory placement, and market expansion that remain invisible in aggregate reports.

Start with the basics covered in this tutorial, use the Geographic Analysis tool to accelerate your insights, and continuously refine your strategy as you gather more data. Your competitive advantage lies not in having data, but in consistently acting on the insights it provides.

Where are your customers located? Now you have the tools to answer that question—and use the answer to build a stronger, more profitable Amazon business.

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