Skip to content

Weekly Report Documentation

Menu Location: Reports > Weekly Report

Access Level: Manager

Last Updated: 2026-03-01

Overview

The Weekly Report is the most comprehensive business intelligence dashboard in the system, providing detailed financial and operational metrics for each delivery week. This report helps you analyze revenue, track customer acquisition and retention, monitor order patterns, and make data-driven business decisions.

Primary Functions:

  • View comprehensive week-by-week business metrics
  • Analyze revenue breakdown (completed, pending, failed)
  • Track customer growth and churn rates
  • Monitor order counts and skip rates
  • Compare performance across multiple weeks
  • View three different report types (Overview, Box Types, Dollar Totals)

Page Layout

Header Section

  • Page Title: "Reports \ Weekly Report"
  • Refresh Cache button (recalculates all historical data)
  • Chart displaying trend data

Report Controls

  • From/To Week Selectors: Choose week range to display
  • Report Type Dropdown: Switch between Overview, Box Types, or Dollar Totals
  • Box Cost Input: (Dollar Totals only) Enter packaging cost per box
  • Update Report Button: Refresh with new parameters

Main Content Area

Large data table with week-by-week metrics (specific columns vary by report type)

Churn Section (Bottom)

Optional churn analysis showing net customer growth over various time periods (7, 14, 30, 60, 90, 120, 365 days)

Three Report Types

1. Overview Report (Default)

Most commonly used report showing operational metrics.

Key Metrics Per Week:

  • All Orders Generated (total orders attempted)
  • Skipped Orders (cancelled/skipped orders)
  • Paid Orders (orders with payment)
  • Promo Orders (orders below threshold, typically < $15)
  • Closed At (total deliveries = paid + promo)
  • Revenue (Failed, Pending, Completed)
  • Customer Signups (normal vs promo)
  • Customer Cancels
  • Customer Count (active customers at week end)

Chart Displays:

  • Closed orders over time
  • Skipped orders trend line

2. Box Types Report

Shows breakdown of orders by subscription box type.

Purpose: Understand which box sizes/types are most popular

Columns:

  • Week ID and Date
  • One column per box type (Small, Medium, Large, etc.)
  • Count of orders for each box type that week

Use Case: Inventory planning and menu creation based on box type popularity

3. Dollar Totals Report

Financial deep-dive showing revenue and cost analysis.

Key Metrics:

  • Box revenue (subscription box prices)
  • Add-ons (extra items purchased)
  • Delivery fees
  • Credits applied
  • Discounts applied
  • Actual payment received
  • Produce costs (from inventory data)
  • Box costs (packaging/delivery costs)
  • Add-on wholesale costs
  • All products wholesale costs
  • Net profit calculation

Purpose: Understand profitability and cost structure

Overview Report Columns

Order Metrics

All Orders Generated: Total orders created for the week (cancelled + promo + paid). Includes all order attempts regardless of final status.

Skipped Orders: Count of orders with cancelled status (customers who skipped that week). Important metric for engagement.

Skipped Revenue: Total box_total value of skipped orders. Shows potential lost revenue from skips.

Skipped AVG $: Average revenue per skipped order. Helps understand what customers are skipping.

Paid Orders: Count of orders with actual_total ≥ $15 (or configured threshold). These are standard paying orders.

Promo Orders: Count of orders with actual_total < $15. These are discounted/promotional orders. Click "Promo Orders" column header to adjust threshold.

Closed At: Total orders delivered that week (Paid + Promo). This is your actual delivery count.

Skipped Percent: Percentage of orders that were skipped: (Skipped ÷ (Skipped + Paid + Promo)) × 100%

Revenue Metrics

Failed: Total revenue from failed payments (payment_status = -1). Money you expected but didn't collect.

Pending: Total revenue pending collection. Includes orders with no payment attempt yet and payments still processing.

Completed: Total revenue successfully collected from payments (payment_status = 1) plus processing fees.

Failed + Pending + Complete = Total: Sum of all payment attempts. This is your total order value generated.

Addons: Total retail value of extra items purchased (from cust_order_contents). Products beyond base subscription.

Delivery Fee: Total delivery fees charged to customers.

Processing Fee: Total processing fees charged (if enabled).

Credits: Money applied from customer account credits towards orders. Shown as negative.

Discounts: Coupon/discount codes applied. Shown as negative.

Avg $ per paying order: Average revenue per order: Completed Revenue ÷ Paid Orders. Tracks average order value.

Customer Metrics

Normal Signups: Count of new customers who signed up WITHOUT a discount/promo code. Organic growth metric.

Promo Signups: Count of new customers who signed up WITH a discount/promo code. Shows promotion effectiveness.

Cust Cancels: Count of customers who cancelled their accounts during the week. Churn metric.

Cust Count: Total active customers at the closeout of that week. Helps track growth trajectory.

Data Source Indicator

SAVED (gray label): Stats were calculated and cached. Data is from previous calculation to speed up report loading.

LIVE (blue label): Stats are being calculated in real-time from database. Most recent data available.

Dollar Totals Report Columns

Column Description Calculation
ID Week ID number Sequential week identifier
Date Delivery date Date of that week's delivery
Box Box revenue SUM(box_total) for non-cancelled orders
Add-ons Extra items SUM(cost) from cust_order_contents
Delivery Fee Delivery charges SUM(delivery_fee) from orders
Credits Credits applied SUM(credits_total), shown negative
Discounts Discounts applied SUM(discounts_total), shown negative
Actual Payment received SUM(actual_total) for non-cancelled
Produce Costs Wholesale produce Calculated from menu_inventory
Box Costs Packaging/delivery Order count × box_cost config
Addons Wholesale Add-on costs Wholesale cost of extra items
ALL Products Wholesale Total product costs All menu items wholesale cost
Actual - Produce - Box - Addons Net calculation Shows remaining profit margin

Box Cost Configuration:

  • Enter your average packaging cost per box
  • Include cardboard, tape, labels, ice packs, etc.
  • Can include average delivery cost
  • Saved per report session

Purpose: See profitability after product and packaging costs

Box Types Report Layout

Shows order counts broken down by each subscription box type.

Columns:

  • ID (Week number)
  • Date
  • One column per box type name (varies by business)

Example: 

ID | Date        | Small Box | Medium Box | Large Box | Family Box
---|-------------|-----------|------------|-----------|------------
150| Jan 15 2026 | 45        | 123        | 67        | 34
149| Jan 8 2026  | 48        | 118        | 65        | 32

Use Case: Plan inventory and menu portions based on box type popularity

Search & Filtering

Week Range Selection

From Week: Dropdown showing all past weeks. Select starting week for report.

To Week: Dropdown showing all past weeks. Select ending week for report.

Default Range:

  • To: Current week
  • From: 12 weeks prior
  • Adjustable to any range

Tips:

  • Shorter ranges load faster
  • Compare similar date ranges year-over-year
  • Include enough weeks to see trends (8-12 minimum)

Report Type Selection

Overview: Complete operational metrics. Best for daily/weekly monitoring.

Box Type Breakdown: Order distribution by subscription type. Best for inventory planning.

Dollar Totals: Financial analysis with costs. Best for profitability analysis.

Update Report: Click after changing any filter to reload data.

Actions & Operations

Adjusting Promo Order Threshold

Purpose: Define what counts as a "promo order" vs regular order

Steps:

  1. Click "Promo Orders" link in column header
  2. Enter dollar threshold (default $15)
  3. Click "Save Promo Order Threshold"
  4. Report recalculates automatically

Example: If set to $15, orders under $15 are "promo", $15 and above are "paid"

Refreshing Cached Data

Purpose: Recalculate stats for all weeks from live data

When to Use:

  • After fixing data issues
  • When "SAVED" data seems incorrect
  • After major database updates

Steps:

  1. Click "Refresh Cache" button (top right)
  2. Wait for processing (can take 1-2 minutes)
  3. Page reloads with fresh calculations
  4. All weeks recalculated and saved

Note: Only use when necessary - uses significant processing

Re-lookup Single Week

Purpose: Recalculate one specific week without processing all weeks

Steps:

  1. Click "SAVED" label next to week
  2. Modal opens showing data source info
  3. Click "Re-lookup data Week ID #[number]"
  4. That week recalculates from live data
  5. Page reloads with updated week

Faster than: Refreshing entire cache

Customizing Table Columns

Purpose: Show/hide columns based on your needs

Steps:

  1. Click "Customize Table" button (above table)
  2. Column headers become interactive
  3. Click column header to toggle visibility
  4. Click "Done Customizing Table" when finished
  5. Preferences saved per admin user

Benefits:

  • Focus on metrics you care about
  • Cleaner view for specific analyses
  • Settings persist across sessions

Downloading Report Data

Purpose: Export data for external analysis (Excel, Google Sheets)

Steps:

  1. Configure report (dates, type)
  2. Use browser to select and copy table data
  3. Paste into spreadsheet application

Alternative: Print to PDF using browser print function

Loading Churn Report

Purpose: See customer acquisition vs cancellation trends

Steps:

  1. Scroll to bottom of page
  2. Click "Load Churn Report" button
  3. Displays net customer growth for 7, 14, 30, 60, 90, 120, and 365 days
  4. Green numbers = net growth
  5. Red numbers = net loss

Common Use Cases

Use Case 1: Weekly Business Health Check

Goal: Quick status check on current week's performance

Steps:

  1. Set To Week = current week
  2. Set From Week = 4 weeks ago (for context)
  3. Report Type = Overview
  4. Click "Update Report"
  5. Check:
    • Closed At (total deliveries)
    • Skipped Percent (should be <30%)
    • Completed revenue (cash collected)
    • Normal signups vs Cancels (net growth)

Example: Week 150: 450 closed, 25% skip rate, $18,500 revenue, +15 net new customers = Healthy week

Red Flags:

  • Skip rate >35%
  • Negative net growth (more cancels than signups)
  • High pending revenue (collection issues)

Use Case 2: Financial Month-End Review

Goal: Understand monthly profitability and costs

Steps:

  1. Set From/To to cover full month (4-5 weeks)
  2. Report Type = Dollar Totals
  3. Enter accurate Box Cost (your avg packaging cost)
  4. Click "Update Report"
  5. Review:
    • Actual total (money collected)
    • Produce costs (your biggest expense)
    • Box costs (packaging/delivery)
    • Net profit (rightmost column)
  6. Calculate margins: (Net Profit ÷ Actual Total) × 100%

Example: $75,000 actual - $32,000 produce - $8,000 boxes - $5,000 addons = $30,000 net (40% margin)

Tips:

  • Track margin trend month over month
  • If margin shrinking, investigate produce costs
  • Factor in all costs for accurate picture

Use Case 3: Analyzing Skip Rate Problem

Goal: Understand why customers are skipping orders

Steps:

  1. Report Type = Overview
  2. Set date range to last 8-12 weeks
  3. Look at Skipped Percent column
  4. Identify:
    • When did it increase? (specific week)
    • Is it trending up or stable?
  5. Check Skipped AVG $ (what's being skipped)
  6. Look at chart to visualize skip trend
  7. Cross-reference with:
    • Menu changes that week
    • Price changes
    • External factors (holidays, weather)

Example: Skip rate jumped from 22% to 35% in week 147. Menu that week had expensive lamb, low produce variety. Customers skipped high-value boxes.

Actions:

  • Improve menu variety
  • Survey customers about preferences
  • Consider skip feedback system

Use Case 4: Planning Inventory for Next Week

Goal: Determine how many orders to prepare for

Steps:

  1. Report Type = Overview
  2. Set From/To to last 8 weeks
  3. Note "Closed At" column for recent weeks
  4. Calculate average deliveries
  5. Check trend: growing, stable, or shrinking?
  6. Factor in:
    • Current Cust Count
    • Upcoming holiday (expect more skips)
    • Menu popularity (good menu = fewer skips)
  7. For box types, switch to Box Types report

Example: Last 8 weeks averaged 445 closed orders. Customer count up 3%. No holiday. Plan for 460 orders.

For Box Breakdown:

  • Switch to Box Types report
  • See distribution (e.g., 30% small, 50% medium, 20% large)
  • Apply percentages to expected orders
  • Plan produce inventory accordingly

Use Case 5: Evaluating Marketing Campaign

Goal: Measure impact of promo code campaign

Steps:

  1. Note campaign start week
  2. Set From = 2 weeks before campaign
  3. Set To = current week
  4. Report Type = Overview
  5. Compare "Promo Signups" before and during campaign
  6. Check "Promo Orders" (customers redeeming)
  7. Calculate:
    • Customer acquisition cost = campaign spend ÷ new signups
    • ROI = lifetime value - acquisition cost
  8. Track retention: do promo customers stay?

Example: Campaign week: 45 promo signups (vs usual 10). Cost = $800. CAC = $17.78. If avg LTV = $400, strong ROI.

Tips:

  • Track promo customer retention separately
  • Compare promo vs normal signup retention rates
  • Adjust campaigns based on quality of customers acquired

Chart Visualization

Overview Report Chart

Displays:

  • Line graph showing Closed orders over time
  • Optional: Skipped orders as second line
  • X-axis: Weeks (dates)
  • Y-axis: Order count

Purpose: Visualize trends at a glance

Reading the Chart:

  • Upward trend = business growing
  • Downward trend = shrinking customer base
  • Seasonal patterns visible
  • Sudden drops indicate issues

Dollar Totals Chart

Displays:

  • Multiple lines for different revenue types
  • Actual Total
  • Box Total
  • Extras Total
  • Delivery Fee
  • Credits
  • Produce Cost

Purpose: See financial trends and relationships

Insights:

  • Is produce cost growing faster than revenue?
  • Are add-ons increasing or flat?
  • Credits usage patterns

Troubleshooting

Report loading very slowly

Symptoms:

  • Page takes 30+ seconds to load
  • Browser appears frozen

Solutions:

  1. Reduce week range (try 4-8 weeks instead of 50+)
  2. Use cached data (SAVED tags) instead of forcing recalculation
  3. Check if "Refresh Cache" is running (wait for completion)
  4. Try different report type (Overview fastest, Dollar Totals slowest)

Common Causes:

  • Very large date range
  • Forcing recalculation of many weeks
  • Database load from other operations

Numbers don't match expectations

Symptoms:

  • Revenue doesn't match your records
  • Customer count seems wrong
  • Missing orders

Check:

  1. Are you looking at correct week? (check ID and date)
  2. Is data cached (SAVED) or live?
  3. If SAVED, try "Re-lookup" for that week
  4. Check definition of metric (e.g., Paid vs Closed)
  5. Verify date range is correct

Solutions:

  1. Click SAVED tag and re-lookup that week
  2. If multiple weeks wrong, use Refresh Cache
  3. Verify orders are in correct week (weekly_cycle_id)
  4. Check order statuses are correct

If Problem Persists:

  • Check database directly for that week
  • Review recent data migrations or imports
  • Contact Kiva Logic support

Churn report shows red (negative growth)

Symptoms:

  • Churn boxes show negative numbers
  • More cancels than signups

Check:

  1. Is this seasonal? (holidays = more cancels)
  2. Check Cancel reasons (if tracking)
  3. Review recent price changes
  4. Look at skip rate (precursor to cancels)
  5. Compare to previous same time period

Solutions:

  1. Improve retention:
    • Survey customers
    • Enhance menu variety
    • Better customer service
    • Loyalty incentives
  2. Increase acquisition:
    • Marketing campaigns
    • Referral programs
    • Seasonal promotions

Normal Patterns:

  • Some churn is normal (5-10% monthly)
  • Seasonal fluctuations expected
  • January often high cancel (post-holiday)

Promo Orders showing incorrectly

Symptoms:

  • Orders you consider paid showing as promo
  • Or vice versa

Check:

  1. Current threshold setting (click Promo Orders header)
  2. Order actual_total amount
  3. Are credits/discounts bringing total below threshold?

Solutions:

  1. Adjust threshold to match your definition
  2. Remember: threshold is actual_total (after credits/discounts)
  3. For different definition, use custom report

Understanding:

  • Default threshold: $15
  • Example: $25 box - $12 discount = $13 actual = Promo Order
  • This is intentional (low revenue orders)
  • Order Management (cust_order.php) - Detailed order view and management
  • Customer Reports (various) - Customer-focused metrics
  • Financial Reports (various) - Payment and revenue details
  • Email Reports (email-stats.php) - Communication metrics

Typical Workflow:

  1. Weekly Report (overview) → identify issue
  2. Drill into Orders page → find specific orders
  3. Review Customer page → understand customer behavior
  4. Take action → update prices, menu, policies

Permissions & Access

Required Access Level: Manager with PERMISSION_WEEKLYREPORTS

Manager Capabilities:

  • View all report types
  • Adjust date ranges
  • Customize table columns
  • Refresh cached data
  • Download/export data

Kiva Admin Additional Capabilities:

  • Access developer debug information
  • See system performance metrics
  • Direct database query access

Restricted Features:

  • None for authorized managers

Best Practices

Daily/Weekly Monitoring

  1. Check Overview report every Monday morning
  2. Focus on: Closed At, Skip %, Revenue Completed
  3. Compare to previous week (2-4 week rolling view)
  4. Flag anomalies for investigation

Monthly Analysis

  1. Run Dollar Totals for full month
  2. Calculate margins and trends
  3. Review customer acquisition costs
  4. Analyze skip patterns
  5. Load Churn report for retention check

Strategic Planning

  1. Use 12-week or longer ranges
  2. Identify seasonal patterns
  3. Plan inventory based on trends
  4. Set growth targets based on historical data
  5. Compare year-over-year performance

Things to Avoid

  • Don't refresh cache during business hours (slow for everyone)
  • Don't analyze single weeks in isolation (need context)
  • Don't ignore skipped revenue (lost opportunity)
  • Don't forget to adjust promo threshold if pricing changes
  • Don't use Box Cost feature without accurate cost data (misleading)

Quick Reference Card

Task Action/Location
View current week performance Set To = current week, From = 4 weeks ago
Check monthly revenue Use Dollar Totals, date range = full month
See which boxes are popular Switch to Box Types report
Find skip rate trend Overview report, Skipped Percent column
Calculate profitability Dollar Totals, rightmost column
Update cached week data Click SAVED tag, then Re-lookup
Recalculate all weeks Click Refresh Cache (top right)
Hide unnecessary columns Click Customize Table button
Check customer growth Overview, Normal Signups vs Cust Cancels
Adjust promo threshold Click Promo Orders column header
View churn analysis Scroll to bottom, Load Churn Report
Compare to last year Set same week range as last year

FAQs

What's the difference between Paid Orders and Closed At?

Paid Orders are orders with payment ≥ threshold ($15). Closed At includes both paid AND promo orders (under threshold). Closed At is your total delivery count. Paid Orders is your regular revenue orders.

Why does revenue show Failed, Pending, and Completed separately?

This shows the full picture of payment collection. Failed is money you expected but didn't get. Pending is still being processed. Completed is in your bank. Total = all three combined. This helps identify collection issues.

Can I see data for a specific customer?

No, this is aggregate report only. For customer-specific data, use Customer Reports or Order Management pages. This report is for business-level metrics.

How far back can I view reports?

As far back as you have data. However, very old weeks (years ago) may be archived and load slowly. Typical range: current week back 1-2 years is reasonable.

What does SAVED vs LIVE mean?

SAVED = stats calculated and cached (faster, but may be slightly outdated). LIVE = calculated right now from database (slower, but most current). For past weeks, SAVED is fine. For current week, LIVE is better.

Why is my skip rate so high?

Skip rate over 30% can indicate: (1) Menu not appealing that week, (2) Price increases, (3) Seasonal patterns (summer vacations), (4) Customer fatigue, (5) Subscription flexibility working as intended. Compare to historical average.

How do I use the Box Cost field?

Enter your average total cost per box delivered. Include: box/packaging ($1-3), dry ice/insulation ($2-5), average delivery cost ($3-7). Example: $1 box + $3 insulation + $5 delivery = $9 per box. This helps calculate net profitability in rightmost column.

Change Log

2026-03-01

  • Initial comprehensive documentation created
  • Documented all three report types in detail
  • Covered all metrics, filters, and troubleshooting
  • Added practical use cases and examples

End of Documentation

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