MMM Calculator

Unlock Marketing Spend Savings

With our MMM Calculator, you can gain a clearer picture of how to make the most of your marketing spend. Our calculator provides you with an estimate of the financial value you can save.


This MMM Calculator provides estimated savings based on modeled scenarios within your industry. It is intended for informational purposes only and serves as a quick overview of potential savings. For a comprehensive and accurate projection of marketing spend optimization tailored to your specific needs, please contact us.

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up to 18%
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Key Reasons to Integrate MMM into Your Marketing Strategy

Incorporating Marketing Mix Modeling into the marketing strategy can lead to more efficient resource allocation, increased profitability, and a better understanding of how marketing efforts impact business outcomes.

  • Data-Driven Decision Making

    Marketing Mix Modeling (MMM) offers an empirical and data-driven approach to understanding the impact of various marketing channels on sales and performance. By implementing MMM, a company can make informed decisions based on actual data, rather than relying on intuition or hunches.

  • Optimized Budget Allocation

    MMM provides insights into which marketing channels are most effective and which may be underperforming. This enables companies to allocate their marketing budgets more efficiently, directing resources where they can generate the highest ROI.

  • Improved ROI

    With the ability to measure and analyze the effectiveness of each marketing channel, MMM can help a company improve its return on investment. It allows for the identification of high-performing strategies and the elimination or optimization of underperforming ones, leading to greater overall ROI.

  • Market Response Analysis

    MMM can help companies understand how the market responds to their marketing efforts, including factors like seasonality, external events, and competitive actions. This insight allows for more agile and adaptive marketing strategies.

  • Competitive Advantage

    Implementing MMM can give a company a competitive edge by enabling it to fine-tune its marketing strategies more effectively. This can result in a stronger market position and increased market share.

  • Long-Term Strategy Alignment

    By continuously monitoring and analyzing the impact of marketing efforts, companies can align their long-term marketing strategies with changing market conditions and customer behavior. This adaptability is crucial in today's fast-paced business environment.


Frequently Asked Questions

Everything you need to know about the product and billing.

Sales or Conversions data is the foundation for all Forvio marketing mix models (MMM). This is because the main objective of MMM is to understand how marketing activities influence the target variable, which typically pertains to sales or conversions at specific points in the sales funnel. To ensure the effectiveness of your marketing mix model(s), it's essential that the sales or conversions data is granular on a daily level, as recent as possible, and of high quality

You can get this data from your POS, ERP, CRM, or web page tracking tools like Google Analytics. We recommend modelling several categories separately, like online and offline conversions, for more precise insights. Furthermore, splitting your data by country or region can yield improved results. In complex scenarios, an overarching business model can be assembled from individual models for a comprehensive understanding of your marketing impact.

Marketing activities data: Forvio provides native integrations to the most widely used marketing platforms such as Meta Ads, Google Ads, and Google Search Console. Keep in mind all paid marketing activities should be included using exposure metrics (e.g. impressions or views) along with their corresponding spends.

Here are some recommended metrics for different channels:

  • Digital activity: Focus on impressions; avoid using clicks
  • TV and Radio: Utilize metrics like Gross Rating Points (GRPs) or Target Audience Rating Points (TARPs) or Impressions for Display
  • Print (e.g. newspapers or magazines): Utilize readership metrics

Similarly, organic/non-paid marketing activities can be added in a form of exposure metrics, for instance tracking the number of emails sent.

Non-Marketing Variables: Keep in mind that marketing mix modeling is designed to quantify the incremental sales impact and ROI resulting from both marketing and non-marketing activities on a pre-defined KPI.

Non-marketing variables can greatly influence company sales, but they are not directly connected to marketing efforts. In order to avoid misattribution of results to media activities, MMM needs to account for the effects of these variables. These non-marketing factors may include promotions and discounts, macroeconomics factors, weather, competitor activities, and potentially, COVID-19 data.

Yes, Forvio includes automatic currency conversions across all data sources. When using Forvio’s native integrations, currency is automatically detected. For other manually loaded data sources, you can easily select the correct currency for each media during the integration step.

The final model’s reporting currency is configured within the model selection, ensuring that all data is calculated and presented in the chosen currency. For currency conversion, Forvio employs the European Central Bank exchange rate, which is updated daily.

Measuring long-term brand effects can be challenging. In Forvio, we address this by default by including organic search impressions data from Google Search Console in every model. This data serves as a proxy to represent brand presence in searches.

Media mix modeling (MMM) is most effective with a substantial volume of data for analysis. The minimum number of conversions isn't fixed; it varies depending on media channel diversity and data variability. Nevertheless, a widely accepted guideline recommends a minimum of several hundred conversions (200-500) for a meaningful analysis. Fewer conversions could compromise the model’s robustness, potentially leading to unreliable results.

Similar to the question above, there isn’t a fixed minimum spend requirement for effective MMM. The key is to distribute your spending across various media channels over time, allowing the model to identify patterns and estimate the impact of each channel. Generally, the more diverse and extensive your media spend, the more dependable your results from MMM will be.

Please be aware that in the USA, the cost of online impressions tends to be higher than in Europe and other regions, which may necessitate a higher spending threshold.

Yes, we strongly recommend including discounts and other promotional activities in your MMM. These factors can have a significant impact on customer behavior and, consequently, conversions. Integrating these factors into your model provides a more precise view of your media spending’s effectiveness.

The importance of weather as an external factor depends on the nature of your business and the nature of your products or services. For some businesses, weather might have a significant impact on sales (e.g., hospitality businesses or retailers of rain jackets), while for others, it might not matter as much. If you suspect weather might be a factor, it can be included in your model as an external variable.

Absolutely, campaign level data is suitable for MMM. In fact, granular data often provides deeper insights and allows for a more accurate estimation of the impacts of distinct media channels. We recommend organizing your campaigns into meaningful channels that represent distinct marketing tactics (e.g. Brand, Product, Awareness, Remarketing). Typically, these channels should account for between 5% and 20% of your overall spend. Forvio offers powerful data transformation capabilities to facilitate categorization of different marketing tactics.

The quantity of historical data needed can fluctuate based on the nature of your business and variations in your media spending. As a general guideline, having a minimum of two to three years of historical data is advisable. This timeframe allows for the capture of seasonality effects and provides a substantial dataset for modeling.

However, the exact amount of historical data needed may be influenced by your specific circumstances. In some cases, reliable models can be developed with as little as six months of daily granularity data.

A Forvio "workspace" is a dedicated and organized work environment within our platform designed for managing and conducting your marketing mix modeling (MMM) projects. Workspaces enable collaboration among team members, facilitating tasks such as data import, model development, and insights visualization. For agencies and freelancers, we recommend having dedicated workspaces for each client.

In the context of Forvio, a "media channel" refers to a specific platform or avenue used to deploy your marketing strategies and engage your intended audience. These channels encompass a wide array of mediums, such as TV, radio, online ads, social media, print media, and more.

To provide clarity, consider Facebook Ads and Instagram Ads as distinct media channels. It's worth noting that a single media channel can consist of various sub-channels where users ca split media into smaller elements.  For instance, within the realm of Facebook Ads, there exist sub-channels like branding campaigns for both Facebook Ads and Instagram Ads. Each of these sub-channels contributes to your overall usage limit.

A "stored model" refers to a previously created and saved marketing mix model that encapsulates your configurations and insights and relevant scenarios. Once you've input your data, adjusted parameters, and generated insights, you can save this model for future reference. This allows you to revisit and compare different models, track changes in your marketing strategies, and assess the performance of various scenarios over time. Stored models enable you to make informed decisions based on historical analyses and ongoing optimizations.

The Scenario Planner uses all calculated results from created model outputs and  is used to optimize budget allocation across your media mix for the next 7, 30, or 90 days. It helps you maximize your current allocations impact and experiment with scenarios of increased or decreased spending. This flexibility allows adaptation to varying market conditions while ensuring optimal budget distribution.

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