Seasonal Patterns
Understanding Seasonality in MMM
Seasonality refers to regular, predictable variations in your KPI that occur at specific times. Decomposition helps isolate and quantify these seasonal effects.
Purpose: Identify seasonal patterns, quantify their impact, and align marketing strategies with natural demand cycles.
Types of Seasonality
Annual Seasonality
Yearly Patterns:
Holiday periods (Q4 for retail)
Summer vacation season
Back-to-school period
Tax season (for financial services)
In Decomposition:
If you have a "Seasonality" group, shows these patterns directly
Or visible in total KPI (black line) as regular annual rhythms
Quarterly Seasonality
Business Cycles:
End-of-quarter budget spending (B2B)
Fiscal year patterns
Seasonal product demand
Example:
Q1: Baseline performance
Q2: 10% above baseline
Q3: 5% above baseline
Q4: 25% above baseline (holiday season)Monthly Seasonality
Within-Year Patterns:
Payday cycles
Month-end effects
Specific holiday months
Weekly Seasonality
Within-Month Patterns:
Weekend vs. weekday
End-of-week patterns
Specific day-of-week effects
Finding Seasonality in Decomposition
Explicit Seasonality Group
If You've Grouped Seasonal Variables:
Look for "Seasonality" group contribution:
January Seasonality: $10,000
July Seasonality: $5,000
December Seasonality: $40,000
Pattern: Strong December peak, moderate January, low summerWhat's Included:
Holiday indicator variables
Monthly dummy variables
Seasonal indices
Weather effects
Implicit Seasonality
In Base Group or Overall KPI:
View the black line (Actual) in main chart:
Regular up-and-down patterns
Peaks at same times each year
Predictable cycles
Example - Retail:
Every year:
- January: Post-holiday dip
- Spring (Apr-May): Moderate
- Summer (Jun-Aug): Low season
- Fall (Sep-Nov): Building
- December: Peak (holiday)Quantifying Seasonal Impact
Seasonal Lift Calculation
Compare Peak to Baseline:
December (Peak):
Seasonality Contribution: $50,000
Base Contribution: $100,000
Total: $150,000
Average Month:
Seasonality Contribution: $10,000
Base Contribution: $100,000
Total: $110,000
Seasonal Lift: $50,000 - $10,000 = $40,000
Percentage Lift: 36% above average monthSeasonal Index
Normalize Each Period:
Average Monthly KPI: $500,000
January Index: $400,000 / $500,000 = 0.80 (20% below average)
December Index: $700,000 / $500,000 = 1.40 (40% above average)
Use: Budget allocation, forecastingMarketing Strategy by Season
Peak Season Strategy
High Natural Demand Period:
Characteristics:
Higher absolute sales
Strong seasonality contribution
Competitive advertising
Marketing Approach:
Maintain Presence:
Don't go dark during peak demand
Capture your fair share
Defend against competitorsBut Don't Over-Invest:
Marketing ROI may be lower (crowded market)
Focus on efficiency
Natural demand is already highExample - Holiday Retail (Q4):
Seasonality drives: +$200,000
Marketing contribution: +$150,000 (lower ROI than off-season)
Total lift: $350,000
Strategy: Moderate marketing, let seasonality work for youOff-Season Strategy
Low Natural Demand Period:
Characteristics:
Lower baseline sales
Negative or minimal seasonality contribution
Less competitive advertising
Marketing Approach:
Strategic Investment:
Marketing can have higher incremental impact
Less competition for attention
Opportunity to build brand
Smooth demand cycleExample - Summer for Winter Products:
Seasonality effect: -$50,000 (negative)
Marketing contribution: +$100,000 (higher ROI)
Net: +$50,000
Strategy: Invest to counteract seasonality, build off-season demandShoulder Seasons
Transition Periods:
Build Momentum:
Ramp up before peak season
Capture early demand
Pre-season promotions
Extend Season:
Keep demand going after peak
Capture late buyers
Clear inventory
Seasonal Budget Allocation
Traditional Approach (Follow Seasonality)
Allocate Budget to Match Demand:
Q1: 20% of annual budget (baseline)
Q2: 25% of annual budget (spring increase)
Q3: 20% of annual budget (summer dip)
Q4: 35% of annual budget (holiday peak)Pros: Maximize absolute sales, capitalize on demand Cons: Higher costs in Q4, competitive market
Counter-Seasonal Approach
Invest More in Off-Season:
Q1: 30% of budget (build demand)
Q2: 25% of budget (maintain)
Q3: 30% of budget (combat summer dip)
Q4: 15% of budget (ride natural demand)Pros: Better ROI, less competition, smooth demand Cons: Lower absolute sales, fight natural patterns
Balanced Approach (Recommended)
Combine Both Strategies:
High Season (Q4):
- 30-40% of budget
- Maintain presence
- Don't over-invest
Shoulder Seasons (Q2, Q3):
- 25-30% of budget
- Build momentum
- Capture opportunity
Low Season (Q1):
- 20-25% of budget
- Strategic investment
- Efficiency focusSeasonal Marketing Insights
Campaign Timing
Align with Seasonality:
Launch Before Peak:
Holiday season peaks in December
Launch campaigns in November
Build awareness before purchase intent peaksExtend Seasons:
Back-to-school traditionally August
Start promotions in July
Extend through SeptemberChannel Mix by Season
Different Channels Perform Differently by Season:
Example:
Summer (Low Season):
- TV less effective (people outdoors)
- Digital more efficient (targeted)
- Strategy: Shift to digital
Winter (High Season):
- TV more effective (people home)
- All channels competitive
- Strategy: Balanced mixPromotional Timing
Leverage or Counter Seasonality:
With Seasonality:
Holiday promotions when demand is naturally high
Amplify natural demand
Example: Black Friday, Christmas salesAgainst Seasonality:
Summer sales to combat low season
Create artificial demand peaks
Example: Summer clearance eventsYear-Over-Year Seasonal Comparison
Track How Seasonality Changes:
December 2023:
Seasonality Contribution: $180,000
December 2024:
Seasonality Contribution: $210,000
Change: +17% seasonal effect
Insight: Holiday season getting stronger
Action: Plan for continued growthHelps Identify:
Strengthening seasonal patterns
Weakening effects
Structural market changes
Consumer behavior shifts
Forecasting with Seasonal Patterns
Use Historical Patterns to Predict:
Step 1: Calculate Seasonal Indices
Each month's index = Month Average / Overall AverageStep 2: Apply to Forecast
Base forecast: $500,000/month
January index: 0.80
January forecast: $500,000 × 0.80 = $400,000Step 3: Add Marketing Plans
Planned marketing contribution: +$100,000
Total January forecast: $500,000Seasonal Analysis Checklist
Identify Patterns:
[ ] Clear seasonal group in decomposition?
[ ] Regular patterns in total KPI?
[ ] Same peaks each year?
Quantify Impact:
[ ] Peak vs. baseline difference?
[ ] Seasonal lift percentage?
[ ] Contribution by period?
Strategic Decisions:
[ ] Budget allocation by season?
[ ] Campaign timing optimized?
[ ] Channel mix adjusted seasonally?
Year-Over-Year:
[ ] Seasonal patterns strengthening?
[ ] New patterns emerging?
[ ] Historical trends continuing?
Common Seasonal Patterns by Industry
Retail:
Q4 peak (holidays)
January dip (post-holiday)
Back-to-school (Aug-Sep)
Travel:
Summer peak (Jun-Aug)
Holiday periods (Thanksgiving, Christmas)
Spring break (March)
Financial Services:
Tax season (Jan-Apr)
Year-end (Dec)
Quarterly patterns
B2B:
End-of-quarter budget spend
Fiscal year-end
Trade show seasons
E-Commerce:
Cyber Week (Nov-Dec)
Prime Day (July)
Monthly payday patterns
Summary
Key Takeaways:
Seasonality Shows:
Predictable demand patterns
Natural business cycles
Market rhythms
Use Seasonality To:
Time campaigns effectively
Allocate budgets wisely
Forecast accurately
Plan inventory and resources
Strategic Approaches:
Follow seasonality (maximize peaks)
Counter seasonality (smooth demand)
Balance both (optimal approach)
Best Practices:
Track year-over-year changes
Adjust marketing by season
Plan 12 months ahead
Don't fight strong seasonality
Next Steps:
Identify your seasonal patterns
Quantify seasonal impact
Develop season-specific strategies
Monitor and adjust over time
Last updated