First Product Report

The First Product report provides insights into customer purchasing behavior by analyzing products that customers buy in their first order, and tracking their subsequent purchase patterns. This report helps identify which products are effective at acquiring customers and driving repeat purchases.

Overview​

This report tracks customer lifetime value from the perspective of their first product purchase. It shows how many customers who first purchased each product went on to make additional orders, providing valuable insights into product performance for customer acquisition and retention strategies.

The report groups customers by the first product they purchased and tracks their ordering behavior across up to 4+ orders. This analysis helps identify which products are most effective at bringing in customers who continue to purchase from your store.

Report Logic Summary​

The report processes orders by:

1. Customer Grouping: Groups all orders by customer email address
2. First Order Identification: Identifies each customer's chronologically first order
3. Product Attribution: Attributes all subsequent customer behavior to the products in their first order
4. Order Sequence Tracking: Counts customer orders up to 4+ orders (1st, 2nd, 3rd, 4th+)
5. Refund Integration: Includes refund data matched to products and time periods
6. Multiple Calculations: Supports different calculation methods (count, sales totals, AOV, percentages)

Important: If a customer's first order contains multiple products, each product in that first order gets credit for the customer's entire subsequent purchasing behavior.

Column Definitions​

Core Metrics​

Report Variations​

The report supports four different calculation methods:

Order Count (Default)​

• Purpose: Count the number of orders at each stage
• Calculations:
  • All columns show order counts
  • Additional Order Rate = (2nd + 3rd + 4th+ orders) ÷ 1st orders
  • Refunds show refund transaction counts

Order Total (Sales)​

• Purpose: Show revenue values at each stage
• Calculations:
  • All columns show monetary values from orders
  • Uses the first order's total value for attribution
  • Additional Order Rate = Additional order revenue ÷ 1st order revenue
  • Refunds show total refund amounts

Order AOV (Average Order Value)​

• Purpose: Display average order values at each stage
• Calculations:
  • Shows average order value for each order number
  • Additional Orders column shows average of 2nd, 3rd, 4th+ AOVs
  • Additional Order Rate = Combined AOV ÷ 1st order AOV
  • Refunds show average refund amount per refund transaction

Percent of First-Order​

• Purpose: Show percentages relative to first orders
• Calculations:
  • 1st Order shows 100% (or ratio to base count)
  • Other columns show percentages of first-order volume
  • Additional Order Rate remains a standard percentage
  • Useful for understanding retention rates

Report Features​

• Product Limit: Displays top 1000 products by total volume
• Automatic Sorting: Products are ranked by total metric value (descending)
• Totals Row: The first row shows aggregated totals across all products (except for AOV variation)
• Multiple Time Periods: View data by day, week, month, quarter, year, or custom date ranges
• Currency Formatting: Monetary values displayed in store currency format
• Comparison Support: Compare against previous periods or goals

Interpreting Results​

High-Performing First Products​

• High Additional Order Rate: Products with >30% additional order rates indicate strong customer retention
• Growing Order Values: Products showing increasing AOV in later orders suggest customer value growth
• Low Refund Rates: Products with <5% refund rates indicate good product-market fit

Customer Acquisition Analysis​

• Products with high 1st order volumes are effective customer acquisition tools
• Compare 1st order performance across products to identify top acquisition drivers
• Use Percent of First-Order variation to understand retention patterns

Lifetime Value Insights​

• Products with strong 4th+ order performance drive long-term customer value
• Compare total revenue attribution across first products to understand LTV drivers
• Identify products that generate customers who become high-value repeat buyers

Technical Details​

Data Processing​

• Customer Attribution: All customer behavior is attributed to every product in their first order
• Date Filtering: Respects selected date ranges for both orders and refunds
• Order Sequencing: Orders are sorted chronologically per customer to determine sequence
• Refund Matching: Refunds are matched to products and aggregated by date
• Memory Optimization: Limited to 1000 top products to manage performance

Calculation Methodology​

• Multi-Product First Orders: If a customer's first order has 3 products, each product gets full credit for that customer's behavior
• Order Capping: Customer order sequence is capped at 4+ orders to prevent data skewing
• Date Boundaries: Both order dates and refund dates must fall within the selected reporting period

FAQ​

Why do revenue numbers differ between First Product report and other reports?​

The First Product report uses a unique attribution methodology that can create discrepancies with other reports:

First Product Report "1st Orders":

• Attributes the full order value to every product in the first order
• If a $100 first order contains 3 products, each product gets credited with $100
• This creates "inflated" totals because multi-product orders are counted multiple times

Dashboard "New Revenue":

• Counts actual new customer revenue without duplicate attribution
• Each order is counted only once regardless of product count
• Represents true revenue from new customers

New vs Returning "New Gross Sales":

• May use different customer identification logic or date boundaries
• Could exclude certain order types or apply different filtering
• Might have stricter definitions of "new" customers

Recommendation: Use Dashboard "New Revenue" for accurate financial reporting, and First Product report for understanding which products drive new customer acquisition behavior.

How should I interpret the Additional Order Rate?​

The Additional Order Rate shows what percentage of customers who first purchased a specific product went on to make additional purchases. For example:

• 40% rate means 4 out of 10 first-time buyers of this product made at least one more purchase
• Higher rates indicate products that attract customers with stronger lifetime value potential
• Compare rates across products to identify your best customer acquisition products

Why might a product show high 1st orders but low additional orders?​

This pattern suggests the product is effective at attracting new customers but may not encourage repeat purchases:

• The product might be a one-time purchase (consumables that last long)
• Price point could be too high for regular repurchasing
• Product satisfaction might be lower, reducing repeat purchase likelihood
• Consider bundling strategies or follow-up product recommendations

How does the report handle customers with multiple products in their first order?​

Each product in a multi-product first order receives full attribution credit for that customer's entire purchasing journey. This means:

• A customer's first order with 3 products credits each product with the full customer lifecycle
• This is intentional to help identify which products contribute to acquiring valuable customers
• The totals will exceed actual customer counts/revenue due to this multi-attribution approach

What time period should I use for meaningful insights?​

Recommended time periods depend on your business:

• Monthly/Quarterly: Good for identifying trends and seasonal patterns
• 6-12 months: Ideal for understanding true customer lifetime value patterns
• Yearly: Best for strategic product portfolio decisions
• Avoid very short periods (weekly/daily) as they don't capture repeat purchase cycles

How do refunds affect the calculations?​

Refunds are included based on the report variation:

• Order Count: Shows number of refund transactions
• Sales: Shows monetary refund amounts
• AOV: Shows average refund amount per transaction
• Refunds are matched to products and time periods, so timing of refunds affects which period they appear in