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Average Spend Per Box Report Documentation

Menu Location: Reports > Billing Reports > Average Spend Per Box Per Box Type Report

Access Level: Manager / Administrator

Last Updated: 2026-03-01

Overview

The Average Spend Per Box Report analyzes add-on purchasing behavior by box type. It shows average and median add-on spending, percentage of boxes with add-ons, and helps identify upsell opportunities and customer buying patterns.

Primary Functions:

  • Calculate average add-on spend per box type
  • Compare all boxes vs boxes with add-ons
  • View median spending to understand typical customer behavior
  • Identify which box types generate most add-on revenue
  • Track percentage of customers adding extras to orders

Page Layout

Header Section

  • Page Title: Billing Reports / Average Spend Per Box Per Box Type Report
  • Column Headers: Two-tier header distinguishing "All Boxes" vs "Only Boxes With Addons"

Filter Controls

  • From/To Date Pickers: Define the analysis period
  • Search Button: Generates report with current settings

Main Content Area

  • Comprehensive Table: 12 columns of data per box type
  • Color-Coded Columns: Purple for all-boxes data, blue for addons-only data
  • Example Explanation: Bottom section explains how to read the first row
  • Hover Tooltips: Column headers have popover explanations

Report Data & Columns

All Boxes Columns (Purple Background)

Column Description Calculation
Count Total boxes of this type delivered COUNT of orders with this box type
Add-on Total Sum of all add-on spending SUM of extras_total for all orders
Average Average add-on per box (including zeros) Add-on Total ÷ Count
Median Middle value of all add-on amounts Statistical median including $0 orders

Only Boxes With Addons Columns (Blue Background)

Column Description Calculation
Count Boxes that included at least one add-on COUNT where extras_total > 0
Add-on Total Sum of add-on spending (excluding $0 boxes) SUM of extras_total where > 0
Average Average add-on for boxes with add-ons Add-on Total ÷ Count (addons only)
Median Middle value of non-zero add-on amounts Statistical median excluding $0 orders

Additional Analysis Columns

Column Description Calculation
Boxes w/ Add-ons Percentage of boxes with add-ons (Addons Count ÷ All Count) × 100
Boxes w/o Add-ons Percentage without add-ons ((All Count - Addons Count) ÷ All Count) × 100
Boxes w/o Add-ons Absolute count without add-ons All Count - Addons Count

Statistical Calculations

Median Calculation

Why Median Matters:

  • More representative of typical customer than average
  • Not skewed by outliers (very high spenders)
  • Shows what most customers actually spend

All Boxes Median:

  • Includes all boxes, even those with $0 add-ons
  • Often lower than average
  • Represents truly typical customer behavior

Addons-Only Median:

  • Excludes boxes with no add-ons
  • Shows typical spend when customer DOES buy extras
  • Higher than all-boxes median

Calculation Method:

  • For odd count: Middle value
  • For even count: Average of two middle values
  • Ordered by extras_total ascending

Average vs Median Example

Box Type: Medium Box (100 total orders)
Add-on amounts: 90 boxes × $0, 8 boxes × $15, 2 boxes × $100

All Boxes:

- Average: ($0×90 + $15×8 + $100×2) ÷ 100 = $3.20
- Median: $0 (middle values are both $0)

Only With Addons (10 boxes):

- Average: ($15×8 + $100×2) ÷ 10 = $32.00
- Median: $15 (middle values both $15)

Insight: While average is $3.20, median shows most customers spend $0.
Of those who DO buy addons, typical spend is $15.

Filters & Search Options

Date Range Selection

From Date:

  • Calendar picker with manual entry
  • Defaults to 3 weeks ago if not specified
  • Filters by deliver_on (order delivery date)

To Date:

  • Calendar picker with manual entry
  • Defaults to current time if not specified
  • Filters by deliver_on (order delivery date)

Important Notes:

  • Searches both current and archived databases (if enabled)
  • Excludes cancelled orders (status != 5)
  • Uses delivered orders only, not pending

Column Meanings & Tooltips

Column Tooltip Explanations:

Add-on Total (All Boxes): "The Sum of all the addons in the box type for all orders in the date range."

Average (All Boxes): "Average = Total / Count. This is the average addon total per box."

Median (All Boxes): "Median of the addons total in ALL the boxes of each type - not just the boxes that have addons"

Color Coding:

  • Purple (.bglightpurple): Includes ALL boxes (even $0 add-ons)
  • Blue (.bglightblue): Only boxes WITH add-ons
  • White: Analysis/percentage columns

Common Use Cases

Use Case 1: Identify Best Upsell Box Types

Goal: Find which box types have highest add-on conversion rates

Steps:

  1. Set date range to last quarter
  2. Click "Search"
  3. Sort mentally by "Boxes w/ Add-ons" percentage column
  4. Identify box types with 30%+ add-on rate
  5. Review what makes these boxes successful at upselling
  6. Apply learnings to lower-performing boxes

Example: "Family Box" shows 45% of customers add extras averaging $28, while "Single Box" shows only 12% adding extras averaging $8. Focus upsell efforts on Family Box customers.

Tips:

  • High percentage means good upsell strategy
  • High average means customers buy a lot when they do
  • Combine both metrics for best opportunities

Use Case 2: Set Realistic Revenue Per Box Targets

Goal: Calculate expected total revenue including add-ons for budgeting

Steps:

  1. Set date range to last 12 months
  2. Click "Search"
  3. Note "Average" in All Boxes section for each box type
  4. Add box base price + average add-ons = expected revenue
  5. Multiply by projected box sales
  6. Use for revenue forecasting

Example: Medium Box base price: $40 Average add-ons (all boxes): $4.50 Expected revenue per Medium Box: $44.50 Projected 1,000 sales = $44,500 total revenue

Tips:

  • Use "All Boxes Average" for conservative estimates
  • Use "Addons Only Average" for aggressive estimates
  • Build in seasonal variation

Use Case 3: Evaluate Add-On Strategy Effectiveness

Goal: Determine if recent add-on promotions increased spending

Steps:

  1. Run report for period BEFORE promotion (e.g., Jan-Mar)
  2. Note "Boxes w/ Add-ons %" and "Average" for target box
  3. Run report for period DURING promotion (e.g., Apr-Jun)
  4. Compare percentages and averages
  5. Calculate ROI of promotion

Example: Before: 25% add-on rate, $15 average After: 38% add-on rate, $22 average Improvement: 13% more conversions, $7 more per sale = successful campaign

Tips:

  • Look for both conversion rate AND average increase
  • Check if median also increased (means more typical customers buying)
  • Calculate total revenue impact: (% change × box count × average)

Use Case 4: Identify Underperforming Box Types

Goal: Find box types with low add-on engagement for improvement

Steps:

  1. Set date range to last 6 months
  2. Click "Search"
  3. Find box types with <15% in "Boxes w/ Add-ons" column
  4. Review what add-ons are offered for these boxes
  5. Survey customers about why they don't add extras
  6. Redesign add-on offerings or placement

Example: "Budget Box" shows only 8% adding extras with $5 average. Customers may be price-sensitive. Test lower-priced add-on options or bundle deals.

Tips:

  • Low engagement might indicate wrong add-ons offered
  • Could indicate add-on pricing too high
  • Might suggest poor add-on visibility in ordering flow

Use Case 5: Understand Customer Segments By Box Type

Goal: Profile customer types based on box selection and add-on behavior

Steps:

  1. Set date range to full year
  2. Click "Search"
  3. Create customer segments:
    • High-value: High % addons + high average
    • Price-conscious: Low % addons + low average
    • Inconsistent: Medium % addons but high variance
  4. Tailor marketing and offers per segment

Example: "Premium Box": 60% add-ons, $45 average = High-value customers, offer premium add-ons "Basic Box": 18% add-ons, $8 average = Price-conscious, offer budget-friendly extras

Understanding the Example Explanation

Bottom Section of Page: Shows a detailed example reading of the first row in the table. It explains:

  1. Total box count for the period
  2. Combined add-on total revenue
  3. How average is calculated (total ÷ count)
  4. What median represents
  5. How many boxes had no add-ons
  6. How many boxes had at least one add-on
  7. Total and average for just the add-on boxes
  8. Median for just the add-on boxes
  9. Percentage calculation for boxes with add-ons

Purpose:

  • Helps users understand complex statistics
  • Shows real data example from their system
  • Makes report less intimidating for non-analysts

Troubleshooting

Median Seems Wrong or Confusing

Symptoms: Median doesn't match what you expected

Check:

  1. Understand median includes $0 values in "All Boxes" columns
  2. Review that median is NOT the same as average
  3. Check if you're looking at right column (All vs Addons Only)
  4. Remember median represents middle value, not mean

Solutions:

  1. Use "Addons Only Median" to exclude $0 orders
  2. Compare to average to understand distribution
  3. Click modal link (if available) to see full distribution

Why It Matters: If median is $0 but average is $5, most customers buy nothing, but a few buy a lot.

Percentages Don't Add Up to 100%

Symptoms: "Boxes w/ Add-ons" + "Boxes w/o Add-ons" doesn't equal 100%

Check:

  1. Verify you're looking at the percentage columns (%)
  2. Check for rounding differences
  3. Ensure you're comparing correct columns

Solutions:

  1. Percentages should add to 100% (or very close due to rounding)
  2. If significantly off, may indicate data issue
  3. Contact support if difference is >1%

Box Type Not Showing in Report

Symptoms: Known box type missing from table

Check:

  1. Verify box had orders in date range
  2. Check if all orders were cancelled (status 5)
  3. Confirm box type exists in boxes table
  4. Expand date range to include box's active period

Solutions:

  1. Widen date range
  2. Check box configuration in settings
  3. Query database for orders with this box type
  4. Verify box wasn't discontinued before date range
  • Boxes Sold Report (how-many-boxes.php) - Count of boxes sold by type
  • Box Settings (settings-boxes.php) - Configure box types and pricing
  • Add-on Products (menu.php) - Manage available add-on items
  • Order Details (customer_order_info.php) - See individual order add-ons

Typical Workflow:

  1. Boxes Sold Report → Count volumes → Average Spend Report → Analyze profitability
  2. Average Spend Report → Find low engagement → Add-on Products → Adjust offerings
  3. Customer inquiry → Average Spend Report → Set expectations for typical spending

Permissions & Access

Required Access Level: View access (implied from code - no explicit permission check)

Access Level Capabilities:

  • Customer Service: View add-on spending patterns
  • Manager: Analyze upsell performance and set targets
  • Administrator: Full access to all data and date ranges
  • Kiva Admin: All features plus database access

Best Practices

Regular Analysis

  1. Run monthly reports to track add-on trends
  2. Compare quarter-over-quarter for seasonal patterns
  3. Monitor percentage changes more than absolute amounts
  4. Track both conversion rate and average spend

Data Interpretation

  1. Use median to understand typical customer
  2. Use average to calculate revenue projections
  3. Look at percentage with add-ons for engagement
  4. Compare All vs Addons Only to see true buying behavior

Strategy Development

  1. Focus upsell on box types with low % but high averages
  2. Increase add-on offerings for high % types
  3. Price-optimize for box types with medium engagement
  4. Don't force add-ons on clearly price-conscious segments

Things to Avoid

  • ❌ Don't confuse median with average - they mean different things
  • ❌ Don't ignore the "All Boxes" data - it's closer to reality
  • ❌ Don't compare percentages across different time periods without context
  • ❌ Don't assume low add-on rate means bad box type - might be intentional

Quick Reference Card

Task Action/Location
Find best upsell box Check highest "Boxes w/ Add-ons" %
Calculate revenue per box Box price + "All Boxes Average"
Understand typical customer Look at "All Boxes Median"
See actual addon spending Look at "Addons Only Average"
Identify low engagement Find lowest "Boxes w/ Add-ons" %
Track campaign impact Compare before/after time periods
Budget add-on revenue Box count × "All Boxes Average"
Profile customer segment Review % and average together
Find outlier impact Compare average to median
Read example explanation Scroll to bottom of page

FAQs

Why are there two sets of columns?

"All Boxes" includes every box (even those with $0 add-ons), showing overall behavior. "Only Boxes With Addons" excludes $0 orders, showing what customers spend WHEN they buy extras. Both perspectives are valuable.

What does it mean if median is $0?

It means more than half of customers don't buy any add-ons. This is common and not necessarily bad - it just means your market is price-sensitive or add-ons aren't compelling for this box type.

How is this different from the Boxes Sold Report?

Boxes Sold counts how many boxes were sold. This report analyzes HOW MUCH customers spend on add-ons per box type. They complement each other for complete product analysis.

Can I see the individual order add-on amounts?

The current version doesn't show order-by-order details in the main table. There's a disabled modal feature in the code that would show this. Contact Kiva Logic if you need this enabled.

Why does "Addons Only Average" seem high?

It excludes all the $0 orders, so it only averages customers who bought something extra. This is the true "when they buy, they buy X" metric. It will always be higher than the "All Boxes Average."

Change Log

2026-03-01

  • Initial documentation created
  • All sections completed based on average-spend-per-box-per-box-type-report.php code review
  • Documented All Boxes vs Addons Only column differences
  • Added median calculation explanations
  • Included statistical interpretation guidance
  • Noted disabled modal feature for median details

End of Documentation

For additional help, contact your system administrator or Kiva Logic support.