Contribution Groups Setup
What Are Contribution Groups?
Contribution groups organize your model variables into logical business categories for decomposition analysis. Instead of viewing the impact of dozens of individual variables, you group related variables together to understand contributions at a strategic level.
Purpose: Organize model variables into meaningful business categories (Media, Price, Promotions, etc.) to enable group-level decomposition analysis and insights.
Why Group Variables?
Strategic Clarity: See high-level contributions rather than getting lost in granular details
Executive Communication: Present results in business terms stakeholders understand
Simplify Analysis: Reduce dozens of variables into 5-10 meaningful groups
Enable Drill-Down: Start with group view, then drill into individual variables when needed
Consistent Reporting: Use standardized groups across all models and time periods
How Contribution Groups Work
The decomposition calculation works as follows:
Variable Contribution = Coefficient × Variable Value
For each time period, every variable's contribution is calculated by multiplying its coefficient by its value at that time.
Group Contribution = Sum of All Variables in Group
Variables assigned to the same group have their contributions summed together for each time period.
Total Predicted Value = Sum of All Group Contributions
All group contributions add up to equal the model's predicted value.
Accessing Contribution Groups
Navigation:
Click "Contribution Groups" in the left sidebar
Select your fitted model from the dropdown
View all variables in your model with their properties
Prerequisites:
Model must be fitted (OLS or Bayesian)
Model must have at least one variable besides the constant
Understanding the Variable Table
The Contribution Groups page displays a comprehensive table with the following columns:
Variable
Variable name from your model
TV_Spend_Ad70
Coefficient
Impact size (green=positive, red=negative)
2.45 (green)
T-Stat
Statistical significance (bold if |t| ≥ 1.96)
3.21
Transform
Data transformation applied
STA, SUB, MDV, ADBUG
Group
Business category you assign (editable)
Media
Adjustment
Optional mathematical adjustment
None, Min, Max
Color Coding:
Green coefficients: Positive impact on KPI
Red coefficients: Negative impact on KPI
Bold t-statistics: Statistically significant (|t| ≥ 1.96)
Variable Information Displayed
Coefficient:
Shows the impact size and direction
Positive values increase KPI
Negative values decrease KPI
Magnitude indicates strength of effect
T-Statistic:
Measures statistical significance
|t| ≥ 1.96 is significant at 95% confidence
|t| ≥ 2.58 is significant at 99% confidence
Bold formatting highlights significant variables
Transform:
Shows any transformations applied to the variable
STA: Standardized
SUB: Subset
MDV: Multiply/Divide
ADBUG: Adstock with Adbudg saturation curve
ADSUBICP: Adstock with SUB and ICP saturation
Multiple transformations may be chained
Organizing Variables into Groups
Step 1: Assign Group Names
Click the Group dropdown for each variable and select or type a group name:
Key Principles:
Use consistent naming across all variables
Choose business-relevant category names
Keep names short and descriptive
Use the same name for all related variables
Example Assignments:
Step 2: Use Multi-Selection for Efficiency
Multi-select features allow bulk operations:
Check boxes next to variables to select multiple
Select All using the header checkbox
Bulk assign group to all selected variables
Bulk set adjustment for all selected variables
Use Case: Select all digital channels at once and assign them to "Digital Media" group
Step 3: Review Group Organization
After assigning groups, review the organization:
Check for completeness:
Every variable should be assigned to a group
No variables left unassigned
Verify consistency:
Similar variables use the same group name
No typos or variations (e.g., "Media" vs "media" vs "Marketing")
Validate business logic:
Groups make sense for your business
Grouping aligns with how you think about drivers
Common Group Categories
Use these standard categories as a starting point:
Base:
Constant term (intercept)
Baseline variables
Trend variables
Purpose: Represents the KPI level when all marketing is zero
Media:
All advertising and marketing channels
TV, Radio, Display, Video, OOH
Both online and offline media
Purpose: Total marketing contribution
Digital:
Online marketing channels
Search, Social, Display, Video, Email
Sometimes separated from traditional Media
Purpose: Digital-specific attribution
Price:
Pricing variables
Discount rates
Price indices
Purpose: Price elasticity and impact
Promotions:
Promotional indicators
Sale events
Coupon campaigns
Purpose: Promotional lift measurement
Seasonality:
Holiday indicators
Monthly/quarterly dummies
Seasonal indices
Purpose: Seasonal effects on KPI
External:
Competitor activity
Economic indicators
Weather data
Purpose: Factors beyond your control
Distribution:
Store count
Distribution expansion
Availability metrics
Purpose: Distribution effects
Group Categories & Best Practices
Best Practices for Grouping
1. Align with Business Structure
Mirror your organization's marketing structure
Match how budgets are allocated
Reflect decision-making hierarchies
2. Balance Granularity
Not too few groups (lose insights)
Not too many groups (defeats the purpose)
Typically 5-10 groups is optimal
3. Consider Analysis Goals
For Budget Allocation:
Group by controllable spend categories
Separate fixed vs. variable costs
Match budget line items
For Channel Performance:
Group by media type
Separate brand vs. performance channels
Group by customer funnel stage
For Executive Reporting:
Use high-level business categories
Group by strategic initiatives
Match stakeholder mental models
4. Enable Drill-Down
Use group decomposition for detailed analysis
Keep individual variable names descriptive
Maintain hierarchical relationship
Strategic Grouping Patterns
Pattern 1: Media Type Grouping
Pattern 2: Funnel Stage Grouping
Pattern 3: Owned vs. Paid
Pattern 4: Brand vs. Performance
Color Assignment Strategy
Assigning Colors to Groups
Once variables are grouped, assign a distinct color to each group:
Access Color Picker:
Color picker appears below the variable table
Shows all unique groups
Click the color swatch to choose a color
Choosing Effective Colors:
Base
Gray (#808080)
Neutral, represents baseline
Media
Blue (#0078D4)
Professional, traditional for marketing
Digital
Teal (#00B7C3)
Modern, distinguishes from traditional
Price
Red (#E81123)
Alert color, represents impact
Promotions
Orange (#FF8C00)
Attention-grabbing, special events
Seasonality
Green (#107C10)
Natural cycles, recurring patterns
External
Purple (#5C2D91)
Distinct, outside control
Color Selection Principles:
1. Distinct Colors
Choose colors that are easily distinguishable
Avoid similar shades (e.g., two blues)
Test visibility in charts
2. Consistent Meaning
Use same colors across all models
Match company branding when appropriate
Align with industry conventions
3. Accessibility
Consider colorblind-friendly palettes
Ensure sufficient contrast
Avoid red-green combinations alone
4. Professional Appearance
Use muted, professional tones
Avoid overly bright/neon colors
Match corporate style guides
Color Persistence
Colors are saved with the model:
Consistency: Same colors used in all decomposition charts
Saved: Colors persist across sessions
Editable: Can be changed anytime
Exported: Colors included in Excel exports
Adjustment Parameters
Understanding Adjustments
Adjustments modify how variable contributions are calculated in decomposition:
None (Default):
Use the variable contribution as calculated
Contribution = Coefficient × Value
Most common setting
Min Adjustment:
Subtract the minimum contribution across all time periods
Shows only incremental effects above the minimum
Formula: Adjusted = Original - Min(Original)
Max Adjustment:
Subtract the maximum contribution across all time periods
Rarely used
Formula: Adjusted = Original - Max(Original)
When to Use Adjustments
None Adjustment (Recommended for Most Variables):
Default setting for all variables
Shows actual contribution values
Maintains interpretability
Min Adjustment Use Cases:
1. Baseline Removal
When you want to show only incremental effects
For variables with consistent baseline contribution
To highlight variability rather than absolute levels
2. Comparing Variable Contributions
Makes it easier to compare variables with different baselines
Focuses on changes rather than levels
Example:
Max Adjustment:
Rarely used in practice
Special analytical scenarios
Typically not needed for standard MMM
Adjustment Impact on Base Group
Important: When adjustments are applied, the subtracted values are added to the Base group to maintain the total predicted value.
Example:
If Min adjustment subtracts 100 from TV each period
Base group contribution increases by 100 each period
Total contribution remains unchanged
Saving Your Configuration
Save Button:
Click "Save Groups" when finished
Saves group assignments for all variables
Saves color selections
Saves adjustment settings
Confirmation:
Success message appears when saved
Configuration persists across sessions
Used automatically in decomposition analysis
When to Save:
After assigning all groups
After choosing colors
After setting adjustments
Before running decomposition
Workflow Summary
Follow this workflow to set up contribution groups:
Select Model: Choose fitted model from dropdown
Review Variables: Examine all variables and their properties
Assign Groups: Use dropdowns or multi-select to categorize variables
Choose Colors: Select distinct, professional colors for each group
Set Adjustments: Apply adjustments if needed (usually keep as None)
Save Configuration: Click "Save Groups" to persist settings
Run Decomposition: Navigate to Decomposition page to analyze
Tips for Success
Start Simple:
Begin with broad categories (Media, Price, Seasonality)
Refine grouping as analysis needs evolve
Don't overthink initial grouping
Test and Iterate:
Run decomposition to see if groups make sense
Adjust grouping based on chart readability
Refine until insights are clear
Document Decisions:
Keep notes on grouping logic
Explain choices to stakeholders
Maintain consistency across models
Consider Audience:
Group for your primary stakeholders
Use terminology they understand
Enable the conversations you need to have
Next Steps
After setting up contribution groups:
Navigate to Decomposition page
Run group-level decomposition analysis
Drill down into specific groups
Calculate ROI by group
Export results for reporting
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