Let's start our "Marketing Mix Modelling (MMM)" journey!

My name is Nitin Patkar, and I have around 10 years of work experience around data and analytics.

As a Senior Solutions Engineer with #Supermetrics, my role often revolves around bridging the gap between data, technology, and business outcomes. 

One of the most powerful applications I've seen in recent years is the use of predictive analytics in Marketing Mix Modeling (MMM). The goal is to help companies optimize their marketing investments by giving them the tools and guidance needed to implement data-driven solutions. However, not every organization has the internal expertise or data science resources to build such solutions in-house. Fortunately, specialized vendors like Seeda.io and Mutinex—both of whom have strong relationships with Supermetrics—can provide a more accessible path to MMM for businesses without dedicated analytics teams.

In this guide, I’ll outline how companies can implement MMM by either leveraging Supermetrics in-house or utilizing the services of vendors like Seeda.io and Mutinex to fast-track their success.

The Challenge: Understanding Marketing Performance

Imagine a mid-sized e-commerce company that invests heavily across various marketing channels—Google Ads, Facebook Ads, LinkedIn Ads, YouTube, TV, and print media. They face the challenge of understanding which channels are driving sales and where to optimize their budget. Without clear visibility into which channels work best, they risk inefficient spending.

For companies that have internal data teams, Marketing Mix Modeling (MMM) combined with predictive analytics offers a clear solution. However, businesses lacking this expertise need alternative ways to implement MMM effectively. This is where specialized MMM vendors come into play.

Step 1: Centralizing Data with Supermetrics

The foundation of any MMM solution is clean, consolidated data. Here's how businesses can approach this step:

In-House Teams with Supermetrics

For companies with in-house teams, Supermetrics is the perfect tool to automate data collection from various platforms like Google Ads, Facebook Ads, LinkedIn Ads, and YouTube, as well as offline marketing channels. Supermetrics pulls data from these sources into platforms like Google Sheets, Excel, or data warehouses such as Google BigQuery, eliminating manual data collection tasks.

The key steps for companies using Supermetrics are:

1. Set up data connectors: Supermetrics automates the extraction of marketing data and feeds it into a centralized location.
2. Schedule automatic updates: This ensures that data remains up-to-date and eliminates manual intervention.
3. Consolidate and harmonize data: All marketing channels are now aligned in one place, ready for analysis.

For businesses that already have an internal data science or analytics team, this setup provides the foundation they need to build their own MMM and conduct predictive analysis.

The Role of Seeda.io and Mutinex for Companies Without Data Teams

For companies without an internal data science team or those unfamiliar with MMM, solutions like Seeda.io and Mutinex can be incredibly valuable. Both Seeda.io and Mutinex offer ready-made MMM platforms designed for businesses that want to implement sophisticated marketing analytics without needing a deep understanding of predictive modeling.

• Seeda.io: This platform specializes in helping businesses build and execute MMM models with minimal data science expertise. Their user-friendly interface and guided workflows make it easy for marketing teams to understand their data, test various marketing mix scenarios, and implement optimizations.
• Mutinex: Mutinex takes a similarly comprehensive approach by providing MMM as a service, helping companies forecast the impact of marketing investments and refine their strategies based on advanced statistical modeling. The platform is built for marketers, not data scientists, which means even smaller teams can quickly deploy MMM.

Both vendors have close partnerships with Supermetrics, allowing them to seamlessly ingest data from various platforms. For companies that don't have in-house capabilities, this partnership ensures a streamlined data integration process. Businesses can rely on Seeda.io or Mutinex to handle the technical heavy lifting, using Supermetrics to automate the flow of data from multiple sources.

Step 2: Building the Marketing Mix Model

Once data collection is centralized, the next phase is to build the actual Marketing Mix Model (MMM). Here’s how companies can approach this step based on their internal capabilities:

In-House Teams

For businesses with an internal team that can handle analytics, I recommend the following process:

1. Identify key metrics: This includes marketing spend, conversions, and sales performance across all channels.
2. Perform statistical analysis: Use predictive analytics (such as regression models) to measure the impact of each marketing channel. Tools like Python, R, or Tableau can be used to build and visualize the MMM.
3. Integrate external data: Factors like seasonality or economic conditions should also be incorporated into the model to enhance its predictive power.

Companies Using Seeda.io or Mutinex

For businesses without the necessary data science resources, Seeda.io and Mutinex offer a turnkey solution. Both vendors:

• Provide pre-built models tailored to specific industries.
• Offer automated data ingestion from Supermetrics, ensuring real-time data flows directly into their platforms.
• Include features for simulating marketing scenarios and forecasting outcomes based on different budget allocations.

These vendors enable companies to get the benefits of advanced MMM modeling without having to hire specialized talent. They make it easy to interpret the results and adjust marketing strategies on the fly, thanks to their intuitive, marketing-focused interfaces.

Step 3: Forecasting and Optimization

With the MMM built, the next step is using the model to forecast future outcomes and optimize marketing strategies.

In-House Teams

For teams managing their MMM in-house:

1. Run simulations: Test different spending strategies across various channels to determine which budgets will yield the best results.
2. Monitor performance: Use Supermetrics to automate data updates, ensuring that the model reflects real-time performance data. This enables agile decision-making based on current trends.
3. Refine the model: Continually improve the MMM by incorporating new data and adjusting for external factors.

Using Seeda.io and Mutinex

For businesses using Seeda.io or Mutinex, the platforms take care of the heavy lifting. Both vendors provide:

• Forecasting tools: These allow companies to simulate different budget allocations and measure the likely impact on sales.
• Optimization recommendations: Based on the data fed from Supermetrics, Seeda.io and Mutinex can automatically generate insights on where to shift budgets for maximum impact.

With their predictive capabilities, both platforms help marketers make data-driven decisions quickly and confidently, without needing a deep understanding of the underlying statistical models.

The Supermetrics Advantage and Vendor Relationships

A major reason why businesses—both large and small—are able to implement MMM so effectively is the relationship between Supermetrics and vendors like Seeda.io and Mutinex. Supermetrics ensures that all marketing data is accurately and efficiently collected, making it easier for these MMM platforms to work seamlessly.

By partnering with Supermetrics, Seeda.io and Mutinex eliminate the complex and time-consuming task of manual data collection, allowing businesses to focus on interpreting results and optimizing campaigns. This partnership is especially important for companies that don’t have the internal infrastructure or expertise to manage these processes themselves.

Conclusion: Tailoring MMM Solutions to Your Business

Whether a company has a sophisticated data team or lacks internal expertise, Marketing Mix Modeling is within reach through the right tools and partners. Businesses with data science capabilities can leverage Supermetrics to build and manage their own MMM systems, while companies without these resources can turn to vendors like Seeda.io and Mutinex for comprehensive solutions.

For companies looking to take their marketing to the next level, Supermetrics’ close relationship with these vendors ensures that the transition to MMM is smooth and efficient. By choosing the right approach—whether in-house or vendor-supported—businesses can unlock the full potential of their marketing data and make informed, impactful decisions.

Side note: Check out our webinar on Demystifying marketing mix modeling: When do you need the marketing mix? Hosted by my friend Daniel King and our tech. partners