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Customer Product Matrix Documentation

Menu Location: Customers > Reports > Customer Product Graph

Access Level: Manager and above

Last Updated: 2026-03-01

Overview

The Customer Product Matrix page provides a visual graph showing how individual customers interact with products over time, especially focusing on product substitutions and preferences. This powerful analytical tool helps understand customer behavior patterns, identify preferred substitutions, and optimize product offerings.

Primary Functions:

  • Visualize customer product substitution patterns
  • Track product preferences over time
  • Identify most common substitutions
  • Analyze individual customer product journeys
  • Discover product pairing patterns
  • Optimize product recommendations
  • Improve automatic substitution suggestions

Page Layout

Header Section

  • Customer Search - Find specific customer to analyze
  • Date Range Selector - Choose timeframe for analysis
  • Product Filter - Focus on specific products or categories
  • Export Button - Download data for external analysis
  • View Toggle - Switch between graph and table views

Visualization Area

  • Interactive Graph - Visual product substitution flow
  • Time Axis - Shows progression over time
  • Product Nodes - Circles representing products
  • Connection Lines - Shows substitution relationships
  • Color Coding - Indicates substitution frequency
  • Hover Details - Additional info on mouse hover

Data Table

  • Customer Name
  • Original Product
  • Substituted With
  • Date of Substitution
  • Reason (if captured)
  • Frequency Count

Understanding the Graph

Visual Elements

Product Nodes (Circles):

  • Size - Larger circles = more frequently involved in substitutions
  • Color - Different colors for product categories
  • Position - Related products clustered together
  • Label - Product name (abbreviated if long)

Connection Lines (Arrows):

  • Direction - Arrow points from original to substitute
  • Thickness - Thicker lines = more frequent substitution
  • Color Intensity - Darker = recent, Lighter = older
  • Style - Solid (customer choice) vs. Dashed (system suggestion)

Example Reading: 

"Chicken Breast" (large blue circle)
    ↓ (thick dark line)
"Chicken Thighs" (medium blue circle)
Means: Customer frequently substitutes Chicken Breast with Chicken Thighs, and this is a recent pattern.

Color Coding

By Category:

  • Blue - Proteins/Meats
  • Green - Vegetables
  • Red - Fruits
  • Yellow - Dairy
  • Orange - Pantry items
  • Purple - Prepared foods

By Frequency:

  • Dark/Bold - Very frequent substitution (10+ times)
  • Medium - Common substitution (5-9 times)
  • Light - Occasional substitution (2-4 times)
  • Faint - Rare substitution (1 time)

Using the Product Matrix

Analyzing a Customer

Step-by-Step:

  1. Search for customer by name
  2. Select date range (e.g., "Last 6 months")
  3. Review graph visualization
  4. Click nodes for product details
  5. Follow substitution paths
  6. Identify patterns
  7. Export data if needed

What to Look For:

  • Products never substituted (strong preferences)
  • Consistent substitution patterns
  • Recent changes in behavior
  • Products with many outgoing substitutions (disliked?)
  • Products with many incoming substitutions (popular alternatives)

Common Patterns

The "Never Substitute":

  • Product node with no outgoing connections
  • Customer always keeps this product
  • Indicates strong preference
  • Action: Always ensure availability

The "Always Replace":

  • Product with thick outgoing line to one substitute
  • Customer consistently swaps A for B
  • Action: Consider offering preferred substitute by default

The "Explore":

  • Product with many outgoing lines to different products
  • Customer trying different alternatives
  • Action: Provide variety, customer is experimenting

The "Universal Substitute":

  • Product with many incoming lines
  • Frequently chosen as replacement
  • Action: Popular product, maintain good stock

Analysis Views

Individual Customer View

Focus on one customer's complete substitution history.

Use Cases:

  • Understanding personal preferences before customer call
  • Identifying why customer may be dissatisfied
  • Tailoring product recommendations
  • Predicting future substitution needs

Questions It Answers:

  • What are this customer's true favorites?
  • What don't they like?
  • Are they adventurous or creatures of habit?
  • What products work as substitutes for them?

Product-Centric View

Focus on one product across multiple customers.

Use Cases:

  • Understanding if a product has quality issues
  • Identifying best substitute products
  • Improving automatic substitution logic
  • Product discontinuation planning

Questions It Answers:

  • What do customers substitute this product with?
  • Is there a clear preferred alternative?
  • Are substitutions increasing over time?
  • Should we reconsider offering this product?

Time Series View

Track substitution patterns over time.

Use Cases:

  • Identifying seasonal preference changes
  • Tracking impact of product changes
  • Monitoring customer satisfaction trends
  • Evaluating new product performance

Questions It Answers:

  • Are substitution patterns changing?
  • Did a recipe change affect substitutions?
  • Are customers warming up to new products?
  • Is there a seasonal pattern?

Common Use Cases

Use Case 1: Optimize Product Selection for Customer

Goal: Ensure customer gets products they actually want

Steps:

  1. Open Customer Product Matrix
  2. Search for customer
  3. Select "Last 12 months"
  4. Identify products never substituted out
  5. Identify products always substituted away
  6. Check current order against findings
  7. Proactively adjust order before fulfillment

Example: Customer always keeps organic apples, always subs out regular bananas for organic bananas. Current order has regular bananas. Swap to organic before packing to increase satisfaction.

Use Case 2: Investigate Product Quality Concerns

Goal: Determine if multiple customers rejecting same product

Steps:

  1. Open Customer Product Matrix
  2. Filter to specific product (e.g., "Strawberries")
  3. Select "Last 30 days"
  4. Check how many customers substituting away
  5. Review what they're choosing instead
  6. Check if pattern recent or longstanding
  7. Investigate product quality if sudden increase

Pattern to Watch: If 15+ customers suddenly start substituting away from product they previously kept, likely indicates quality batch issue.

Use Case 3: Improve Automatic Substitution Logic

Goal: Make system better at predicting good substitutions

Steps:

  1. Open Customer Product Matrix
  2. Focus on one product (e.g., "Ground Beef")
  3. Review all substitutions across customers
  4. Identify most common substitutes
  5. Check if system already suggests these
  6. Update substitution rules if needed
  7. Monitor improvement

Example: 80% of customers substitute Ground Beef → Ground Turkey when beef unavailable. System currently suggests Ground Pork. Update system to suggest turkey first.

Use Case 4: Personalized Win-Back Strategy

Goal: Re-engage cancelled customer with products they loved

Steps:

  1. Open Customer Product Matrix for cancelled customer
  2. Review their entire substitution history
  3. Identify "never substitute" products (their favorites)
  4. Check which products they explored recently
  5. Craft win-back email highlighting these products
  6. Mention new products similar to their preferences

Example: Cancelled customer never substituted organic chicken, wild salmon, or kale. Win-back email: "We miss you! Your favorites (organic chicken, wild salmon, kale) are in stock, plus new wild-caught cod we think you'll love."

Use Case 5: New Customer Onboarding

Goal: Help new customer discover products they'll love

Steps:

  1. After first few orders, check their matrix
  2. Identify early patterns
  3. Recommend products similar to keepers
  4. Suggest alternatives to products they substituted
  5. Personalize their experience early

Export & Reporting

Export Options

CSV Export:

  • All substitution data in spreadsheet
  • Columns: Customer, Original Product, Substitute, Date, Count
  • Can be filtered in Excel/Sheets
  • Useful for bulk analysis

Graph Image Export:

  • PNG or PDF of visualization
  • Include in customer notes or presentations
  • Share with management
  • Document patterns visually

Summary Report:

  • Auto-generated insights
  • Top substitution patterns
  • Frequency statistics
  • Recommendations

Troubleshooting

Graph Not Displaying

Symptoms:

  • Blank visualization area
  • Loading indefinitely
  • Error message

Solutions:

  1. Reduce date range (try last 30 days)
  2. Clear browser cache
  3. Try different browser
  4. Check if customer has order history
  5. Refresh page

Common Causes:

  • Too much data to render
  • Browser compatibility issue
  • Customer has no substitution history
  • Date range includes no data

No Data for Customer

Symptoms:

  • Graph empty for specific customer
  • Message "No substitution data found"

Check:

  1. Verify customer has order history
  2. Check if they've ever made substitutions
  3. Expand date range
  4. Ensure customer has multiple orders
  5. New customers may not have enough data yet

Substitution Patterns Seem Wrong

Symptoms:

  • Data doesn't match memory
  • Unexpected substitutions shown
  • Frequency seems off

Verify:

  1. Check date range is correct
  2. Ensure looking at right customer
  3. Review actual orders to confirm
  4. Consider if system-suggested vs. customer-chosen
  5. Check for bulk order corrections that may skew data
  • Customers - Main customer search and list
  • Customer Detail - Individual customer account
  • Products - Product management
  • Love/Hate Report - System-wide product preference analysis
  • Product Sold History - Product sales over time

Permissions & Access

Required Access Level: Manager or higher

Access Level Capabilities:

  • Manager: View matrix for all customers, export data
  • Administrator: All Manager + system-wide pattern analysis
  • Kiva Admin: All features + edit substitution logic

Best Practices

Analysis

  1. Look at sufficient date range (at least 3-6 months)
  2. Compare individual patterns to overall trends
  3. Consider seasonal variations
  4. Don't over-interpret single substitutions
  5. Combine with customer notes for context

Customer Service

  1. Review matrix before difficult customer calls
  2. Use insights to personalize recommendations
  3. Reference customer preferences in communication
  4. Proactively optimize orders based on patterns
  5. Build customer loyalty through personalization

Product Management

  1. Track substitution patterns for all products
  2. Identify products consistently rejected
  3. Find unexpected popular substitutes
  4. Use data for product development
  5. Optimize product mix based on substitution analysis

Quick Reference Card

Task Action/Location
View customer matrix Navigate to Customers > Reports > Customer Product Graph
Search customer Use customer search bar at top
Change date range Select from date range dropdown
Focus on product Use product filter
View details Hover over nodes or lines
Switch to table Click "Table View" toggle
Export data Click "Export" button
Analyze pattern Follow connection lines on graph
Check frequency Look at line thickness
Identify favorites Find nodes with no outgoing lines

FAQs

What counts as a "substitution"?

Any time a customer changes a product in their order - either manually through their account or by contacting customer service - it's tracked as a substitution.

Does the graph show system-suggested substitutions?

Yes, but they're shown with dashed lines. Customer-chosen substitutions are solid lines.

How far back does the data go?

The system tracks all substitutions since the feature was implemented. You can view any date range, but most meaningful patterns emerge from 3-6 months of data.

Can I compare multiple customers?

The graph focuses on one customer at a time for clarity. Use the CSV export to compare multiple customers in a spreadsheet.

Why are some products not connected?

Products only show connections if substitutions have occurred. If a customer always keeps a product or it's never been in their orders, it won't have connections.

What if a customer has too many substitutions to display clearly?

Use the date range filter to focus on recent data, or use the product filter to show only specific categories. The table view can be easier for customers with extensive histories.

How often is the data updated?

The matrix updates in real-time as orders are modified. You're always seeing the most current substitution data.

Can I see why a customer made a substitution?

If the reason was logged (e.g., "didn't like taste", "allergy", "tried something new"), it may appear in hover details or the table view. However, many substitutions don't have recorded reasons.

End of Documentation

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