Optimize Your Marketing ROI and Cost Efficiency in a Cookieless World
Marketing Mix Modelling
Introduction to MMM
Understand the Real Impact of your Marketing Activities on Sales
Marketing Mix Modelling (MMM) is statistical modelling technique to quantify the relationship between channel or campaign marketing investments (and media exposure – impressions, GRPs,…) and their impact on sales – thus measuring the ROI. Besides sales it is possible to measure impact on other metrics such as user acquisition or app installs.
MMM is a solution for marketing managers, CMOs and other executives with marketing and revenue responsibility to understand and measure marketing ROI, to plan monthly channel KPIs and optimize budget allocation.
Key Benefits of MMM in a Nutshell
Budget Optimization
Optimal channel budget allocation, automated monthly channel KPI planning
Cookieless Approach
Privacy first measurement. No cookie or user-level data needed.
Covers Online and Offline Channels
Search, display, video, social, influencers, CTV, TV, OOH and others. Impact on both online and offline sales.
Long-term Effects
Can measure advertising impact on sales for months after the campaign
Key Benefits of MMM in a Nutshell
Budget
Optimization
Optimal channel budget allocation, automated monthly channel KPI planning
Cookieless
Approach
Privacy first measurement. No cookie or user-level data needed.
Covers Online and Offline Channels
Search, display, video, social, influencers, CTV, TV, OOH and others. Impact on both online and offline sales.
Long-term
Effects
Can measure advertising impact on sales for months after the campaign
What MMM Solves
Key Challanges in Measurement & Marketing Cost Efficiency
How much sales (online and offline) did each media channel drive?
How would sales be impacted if I made "X" change to my marketing plan?
How much incremental revenue do trade and promotional activities drive?
How should I allocate budget by channel in order to maximize my KPIs?
What is the optimal level of spend for each marketing channel?
Where should the dollars come from if I needed to cut my marketing budget by X %?
Challenge 1
Missing Actionable Insights for Key Marketing Questions
Despite having reports and “analytics” in every possible tool, marketing and revenue executives still don’t get the actionable insights and answers they need:
Challenge 1
Missing Actionable Insights for Key Marketing Questions
Despite having reports and “analytics” in every possible tool, marketing and revenue executives still don’t get the actionable insights and answers they need:
How much sales (online and offline) did each media channel drive?
How would sales be impacted if I made "X" change to my marketing plan?
How much incremental revenue do trade and promotional activities drive?
How should I allocate budget by channel in order to maximize my KPIs?
What is the optimal level of spend for each marketing channel?
Where should the dollars come from if I needed to cut my marketing budget by X %?
Challenge 2
- iOS 14+ changes
- 3rd party cookies deprecation
- Consumer moving between online and offline all the time
- 10+ internet connected devices per household on average
- Explosive growth of marketing tools each having their own reporting methodology to “prove” their value
- Decline in trackability making difficult to get reliable insights from Multi-Touch Attribution tools
Learn how MMM can help you solve these issues
Learn how MMM can help you solve these issues
Sample MMM Results
Identify Hidden Opportunities for Growth or Cost Savings
Optimal vs actual levels of spend and ROI by channels
Revenue contribution according to the mix of individual marketing channels. Relationship between weekly cost and generated revenue
Features
Automated MMM Solution Based on Machine Learning
Budget Optimizer
Find the best allocation of marketing budget among all channels to achieve best possible revenue.
Clear recommendations where you should increase / descrease spend and by how much.
Typical opportunity is 8-15% of cost savings.
Use this feature for automated monthly KPI setting for all channels.
Understanding incrementality
Identify true incremental effect on revenue (or profit or app installs or new customer acquisition…).
Mi.MMM can be calibrated using marketing tests and experiments for ground truth.
Identify and measure long term effect of brand building or other non-performance marketing activities.
Planning And Scenario Modelling
Model various scenarios “what would happen if I change investment in channel X by Y” using intuitive UI.
Try different constraints such as “Investment into TV can increase by 20% maximum over last year” and find best budget allocation given those constraints.
Incorporate expected changes in media prices.
Automated data Integration
Online media data, offline media data, external signals like weather etc – all can be ingested automatically.
Market and competitor level data.
Continuous Insights
Daily or weekly updated model results and insights available to you through UI and integration to leading BI tools (Tableau, PowerBI, Google Data Studio,…).
Results and signals from Mi.MMM can be integrated with your bidding platforms and tools.
Cookieless & Privacy-Safe
No need for user-level data or cookies-based data.
Privacy-first solution.
How Much Does it Cost
Pricing
MMM One-time
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One time MMM analysis
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Data preparation and assessment
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Comprehensive output with recommendations on marketing spend optimization
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Executive summary for CMO
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Workshop to discuss results
MMM Basic
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Automated MMM, weekly updates
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Budget optimizer
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Tableau, PowerBI or Google Data Studio visualizations
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Continuous insights and daily results update
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Automated data ingestion + preparation
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No long-term commitment
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Support via email
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No IT needed for implementation
MMM Enterprise
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Everything in MMM Basic plus:
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Scenario modelling
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Unlimited models
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Dedicated consultant / analyst
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Regular insights and recommendations for your marketing team
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No IT needed for implementation
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Internal team training
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Enterprise-level SLA
Resources
Marketing Mix Modelling and Attribution Modelling have the same basic goal: measure the business impact of marketing channels and find out how to allocate marketing budget between channels in order to achieve the best possible results. The key difference between the two methods is that MMM analyzes effectiveness of marketing budget distribution from a top-down perspective, while attribution models are calculated at the level of a specific user (bottom-up approach).
Resources
Marketing Mix Modelling and Attribution Modelling have the same basic goal: measure the business impact of marketing channels and find out how to allocate marketing budget between channels in order to achieve the best possible results. The key difference between the two methods is that MMM analyzes effectiveness of marketing budget distribution from a top-down perspective, while attribution models are calculated at the level of a specific user (bottom-up approach).