MMM helps

• businesses to understand the effectiveness of their marketing strategies by analyzing data from multiple online and offline channels to provide a comprehensive view of marketing performances, and

• companies to allocate their marketing budgets accordingly.

The tool is aimed both at communication agencies and companies that have communication departments in-house.‍

Business problems addressed

Marketing attribution → identifies which marketing channels contribute most to sales → helps to allocate budgets more effectively.

ROI measurement → quantifies the return on investment for each marketing activity.

Strategic decision-making → provides insights for future campaign planning and budget optimization.

Budget optimization helps to identify saturation points for marketing spending → reallocates budget for maximum efficiency.‍

How does it work?

1. Data collection – the client provides sales data, media spending data, and any additional relevant data.

2. Modeling – the MMM uses this data to build a model that predicts the effect of each marketing campaign on sales volume.

3. Analysis – the model outputs detailed insights showing the impact of each campaign on sales, both in absolute terms and as a ratio of total sales.

4. Recommendations – based on the analysis, the client receives actionable recommendations for optimizing future marketing spend.‍

Use cases

Retail company – improved sales attribution for a mix of TV, radio, and online ads, leading to a 20% increase in marketing ROI.

E-commerce platform – identified the most effective digital marketing channels, optimizing budget allocation and reducing costs by 15%.

Consumer goods – analyzed seasonal campaigns to determine optimal spending periods, boosting holiday sales by 30%.‍

Our example #1

If sales increase by €10,000, MMM can pinpoint that a copywrite-article contributed €5,000, a billboard €3,000, and a social media campaign €2,000, with specific confidence levels (0-100%). We reached a 90% accuracy level during the testing phase, and with real data, an accuracy of 70-80% would be realistic.

MMM can also be used to estimate the budget for campaigns. For example, we can figure out what’s the optimal budget for channel X due to saturation effects (we spend $5,000 to get first 1000 customers via channel X, but to get another 1000 it will cost $15,000 - that money may be better spent elsewhere.

Our example #2

Before MMM you know that after a month filled with various marketing activities, your sales have increased, but you're not sure which activity deserves the credit, making it difficult to plan your next steps.

After MMM Implementation you learn precisely that:

• The article released early in the month generated an 80% confidence increase in sales by €5,000-6,000.

• The billboard, despite less digital traceability, contributed a 60% confidence increase in sales by €2,000-4,000.

• The social media campaign, highly trackable, had a 90% confidence impact, boosting sales by €2,000-2,500.

Project phases & timeline

• Initial consultation (1 week): Understanding client needs and collect initial data.

• Data integration and model setup (2 weeks): Integrating data and setting up the MMM model.

• Model calibration and testing (2-3 weeks): Calibrating the model and validating its accuracy.

• Analysis and reporting (1 week): Generating and delivering comprehensive reports.

• Review and optimization (ongoing): Providing ongoing support and model updates.