What is the media mix modeling?

Media mix modeling (MMM) is a statistical method used to measure the impact of marketing and advertising campaigns on business outcomes. Here's an overview of the typical media mix modeling process.

Data Collection

The first step is gathering historical data on:

• Marketing inputs: Ad spend across different channels, pricing, promotions, etc.

• Business outcomes: Sales, revenue, conversions, etc.

• External factors: Seasonality, competitor activities, economic indicators, etc.

  
  

This data is usually aggregated at a weekly or monthly level over a period of 2-3 years.

Modeling

Next, statistical techniques like multiple linear regression are used to analyze the relationships between the marketing inputs and business outcomes. This involves:

• Identifying relevant variables

• Cleaning and preparing the data

• Building and testing different statistical models

• Selecting the best-fit model

Analysis and Insights

Once a model is finalized, it's used to:

• Measure the impact of each marketing channel on sales/revenue

• Calculate return on investment (ROI) for different channels

• Understand the effects of external factors

• Predict outcomes for different marketing scenarios

Optimization

Based on the insights, marketers can:

• Reallocate budgets to higher-performing channels

• Adjust marketing mix to maximize ROI

• Plan future campaigns more effectively

• Set realistic targets

Ongoing Refinement

The model should be regularly updated with new data and recalibrated to maintain accuracy over time.

While the process can be complex, working with a measurement partner or using specialized MMM software can help streamline implementation. The goal is to gain a holistic, long-term view of marketing performance to optimize campaigns and budget allocation.