Elena Docheva
Forget one-size-fits-all marketing. Enhanced by new advancements in machine learning and artificial intelligence, Media Mix Modelling (MMM) can help you make the most out of your marketing and brand investments.
What is MMM?
MMM is a statistical approach that analyses past-performance data to identify the most effective combinations of marketing activities that affect any conversion metric such as sales or revenue. The model’s drivers include an array of paid and organic marketing metrics and wider external market environment factors such as event and calendar-based factors.
As a measurement model that was first used in the 70s, it quickly became less efficient with the rise of digital due to the lack of granularity and transparency needed for making instant real-time decisions. However, with the data analytics and ML advancements in the last two years, MMM has become a lot quicker and effective in predicting the impact of different combinations of marketing efforts due to its ability to process large datasets and handle mixed sales channels.
With MMM it’s not just about measuring effects; it’s about understanding the underlying causes and leveraging those insights to forecast and shape future marketing spend strategies (Niskala et al., 2023).
Why is MMM a Game-Changer?
Privacy-Compliant Insights
With the new wave of consumer privacy requirements, MMM has become indispensable as a privacy-friendly modelling approach that does not require any user-specific data. With its use of privacy-friendly aggregate data, Meta announced an 80% increase in MMM adoption by marketers in 2022 with expectations of adoption growth in the future (Tayson, 2024).
Predictive Power and Real-Time Adjustments
With many marketers looking for new measurements of effectiveness, MMM slices through the growing complexity and breaks down channel contribution, allowing for all key tracked metrics to be refreshed constantly and recalibrated with new data. Utilising advanced analytics, MMM not only analyses past campaigns but also predicts future outcomes, allowing brands to dynamically adjust their strategies in real-time.
Comprehensive Data Integration and Accurate Forecasting
MMM can develop very granular monthly, weekly or daily forecasts that factor variables from diverse channels, ranging from ad spend to seasonality and calendar event impacts, removing guesswork from the whole process. This approach also offers a macro view of all digital interactions, traditional media exposure and consumer behaviour insights.
Can You Afford to Ignore MMM’s Strategic Benefits?
The advantages of employing MMM are manifold:
- Enhanced ROI Through Precision: MMM pinpoints which marketing initiatives are working and which aren’t, enabling more efficient use of budgets and higher returns on investment.
- Deeper Consumer Insights: It goes beyond surface-level analytics to provide a deep understanding of consumer behaviours and preferences, facilitating more personalised strategies.
- Accurately forecasting sales
- Scenario Planning: AI-enhanced MMM models allow marketers to simulate different strategies and predict their outcomes, providing a sandbox for strategic planning without the financial risks.
Is MMM Right for Your Brand?
While MMM offers significant benefits, it requires a sophisticated approach to data management and analysis:
- Data Quality and Volume: Effective MMM implementation depends on high-quality, comprehensive data.
- Limit on number of independent events: The MMM model cannot work effectively with too many variables, which could force channels or influences to be grouped into one, making it difficult to understand individual impacts.
- Data collection: MMM usually requires at least 2 years of historical data, making it difficult for newer smaller brands to utilise.
To use effectively, the goal of applying MMM is to capture the relevant insights and dynamics for appropriate budget allocation, while maintaining the necessary level of simplicity to ensure the model processes the data accurately.
Choosing the Right Tools: Why BoldLens Selects Robyn for Media Mix Modelling
At BoldLens, we’ve conducted extensive evaluations of several leading MMM methodologies, but our choice to integrate Robyn into our strategy was driven by its distinct advantages that align closely with our mission and the needs of our clients.
Why Robyn Stands out for Our Approach to MMM
Open-Source Flexibility: Unlike proprietary solutions, Robyn is an open-source framework, allowing for unparalleled customization, enabling the tailoring of models specifically to our clients’ needs without being locked into vendor-specific limitations or hidden processes.
High Interpretability: Robyn leverages a frequentist approach, providing clearer and more straightforward insights compared to Bayesian MMM. This ensures that the model’s results are easily understandable, facilitating better decision-making.
Focus on Budget Optimization: Robyn offers robust budget optimization capabilities, aligning marketing efforts with financial efficiency. Unlike time series methods, Robyn’s approach allows for precise allocation of resources, maximizing return on investment.
Not Merely Forecasting: While time series methods focus on forecasting, Robyn emphasizes comprehensive Marketing Mix Modeling (MMM). Provides a more holistic view of marketing performance, encompassing various factors beyond mere predictions.
The Strategic Fit
Choosing Robyn as our primary tool for MMM aligns with BoldLens’s strategic vision of empowering clients with actionable, data-driven insights from a single source of brand truth. Robyn’s comprehensive analytics capabilities enable us to deliver forward-looking recommendations for marketing budget spend, aiding to strategically plan for future successes.
Embracing Media Mix Modelling isn’t just a strategic move—it’s your competitive edge. BoldLens is leading the way, implementing MMM methodologies to empower our clients to foster a data-driven culture that drives effective decision-making. Don’t just keep pace; lead the charge.
