Home » Insights » Marketing Mix Modeling

Marketing Mix Modeling

Media Consulting

What questions does a MMM answer?

In a highly competitive business environment, marketing professionals are faced with the challenge of running their campaigns across more channels than ever before. This constant balancing act can make it difficult to determine which marketing activities are truly contributing to sales or brand visibility. This is where artificial intelligence can be used to optimize the media mix.

A fundamental tool for marketers to effectively understand and analyze all available data is the use of Marketing Mix Modeling (MMM). This methodology relies on the application of advanced statistical models to identify and quantify the interactions between key business variables, such as advertising, pricing, distribution and events, among others.


Marketing Mix Modeling can answer the following questions: 

  • Effectiveness of different media channels: Which media channels (e.g. television, radio, digital, OOH) are generating the most sales? Measuring which media channels are most impactful is crucial to make informed decisions, reach the target audience more efficiently and improve the return of investment (ROI).


  • Return on Investment (ROI) by Channel: What is the return on investment (ROI) for each media channel? Which media works best for ROI in the short term and which in the long term? By understanding the return of investment of each media channel, advertisers can invest more in channels that offer a higher ROI and reduce spending on those with lower returns. This short and long term vision provides better insights as some channels might be better for capturing initial interest while others excel at conversion. Understanding the role of each channel helps brands to create a more holistic marketing strategy.


  • Budget Optimization: How should I allocate my marketing budget between different media channels to maximize overall campaign effectiveness? By determining the optimal allocation of the advertising budget, marketers ensure to maximize their goals.


  • Impact of promotions: How many incremental sales are the promotions bringing me? Which promotion has worked best? Which message worked best? By identifying which promotions work best, businesses make data informed decisions about which types of promotions continue, refine or discontinue. And evaluating which message worked best helps in creating more compelling and engaging ads.


  • Competition: How does the activity of my competitors affect my sales? Being aware of and analyzing competitive activity allows to adapt, strategize and maintain a strong position.


  • Channel saturation: At what investment do they stop being efficient? Recognizing the point at which media channels become inefficient is vital for campaign planning and ensuring that marketing efforts are well-optimized.


  • Prices: How do price increases and decreases affect my sales? Understanding how changes in pricing influence sales is vital for effective revenue management.


  • Long term: What is the effect of long-term advertising on my sales? Long-term advertising helps in building and strengthening a brand’s identity. This brand equity can lead to increased customer trust, loyalty, and recognition, which can translate into sustained sales over time.


  • Planning: When should I invest to obtain better results? Strategic timing ensures that resources are allocated when they are most likely to generate the best results. This optimizes resource utilization and minimizes waste.


  • Prediction: What are my sales going to be based on the different media investment scenarios? Sales forecasting models help in optimizing resource allocation by identifying which media investment scenarios are most likely to yield the best results.


  • External factors: What is the effect of heat waves, or football or certain events on my sales? Recognizing the impact of external factors like weather or events is valuable to help in marketing resource allocation and tailoring marketing and sales strategies.


  • Seasonality: What is the intrinsic seasonality of my market? How would my sales in the market increase or decrease if I did not advertise? Understanding the intrinsic seasonality of the market is critical, as it enables to  focus advertising efforts and budgets during periods when sales are naturally higher.


How do the latest Marketing Mix Models enhance advertising budgets?

1. Data collection: MMMs start by collecting data of various marketing and advertising activities. This can include information on advertising spend, sales data, events, sponsoring, and more. The data can be gathered from various sources, such as company records, industry databases or third-party sources.

2. Data analysis: Since the data is collected, Machine Learning algorithms identify the relationships between different marketing inputs (e.g., TV ads, online ads, radio spots) and the desired outputs (e.g., sales, brand awareness). Statistical techniques using multi-linear regression are used to understand how changes in marketing variables impact the business objectives.

3. Model building: A statistical model is constructed to represent the relationships between marketing variables and outcomes. This model can be linear or nonlinear, depending on the complexity of the data and the business objectives. The model typically includes multiple independent variables (marketing channels) and a dependent variable (sales or other marketing KPIs). To achieve the most comprehensive and precise insights into the impact of marketing, it’s advisable to assess multiple models.

4. Model selection and validation: The models are then validated to ensure its accuracy. This involves testing it against historical data to see how well it predicts past performance. Adjustments are made to the model as needed.

5. Scenario testing: Once the model is validated, it can be used to simulate different scenarios. Marketers can input different budget allocations for various marketing channels to see how they would affect outcomes. This allows for the optimization of media budgets to achieve specific business goals.

6. Recommendations: Based on the analysis and scenario testing, MMMs provide recommendations on how to allocate marketing budgets for maximum impact. Marketers can make informed decisions about where to invest.

7. Iterative process: MMMs are not a one-time solution. They are used in an ongoing and iterative process. As new data becomes available, the model can be updated and refined to reflect changing market conditions and consumer behavior.



Indaru has developed AITA® (Artificial Intelligence Tool for Advertisers), a MMM program to assist marketers in gaining a deeper insight into their marketing expenditures and enhancing the allocation of their marketing budget.

The AITA® serves to eliminate human biases and aid in the planning of budgets. It is able to answer all the questions previously mentioned empowering advertisers to maximize the effectiveness of their marketing budget and enhance campaign performance.

MMM that were developed with AITA® exhibit greater flexibility and improved responsiveness to incoming data for accurate projections. These models can be updated as frequently as required without limitations. Moreover, it is also able to generate simulations of scenarios, such as increasing the Google ad campaign by 20%, to estimate its impact before implementation.

AITA® represents a new generation of MMM algorithms.


Do you have any doubts towards MMM or would you like to know more about AITA®?

Do not hesitate to contact us or follow us on our LinkedIn!

Click here to know more about AITA®

Image by a href on Freepik

Last insights

Sustainable attention

Optimizing Attention Time: A Strategy for Brands to Minimize Carbon Footprint The media sector has a responsibility to take the lead in reducing worldwide emissions. Technology and infrastructure associated with the internet contribute to about 4% of the overall...