The road to Marketing Mix Modeling success is not without obstacles, particularly when it comes to dealing with data silos and data activation. Find out how to overcome them:

2023 has presented marketers with a wake-up call. In a competitive landscape, all marketing efforts are being scrutinized for their return on investment and contribution to the bottom line. To meet these demands head-on, many are turning to Marketing Mix Modeling (MMM) to reveal the impact of marketing activities on business success.

However, MMM comes with its own set of challenges, particularly concerning data silos and data activation. Let's explore how overcoming these challenges is key to harnessing the full potential of MMM:

What is Marketing Mix Modeling (MMM)?

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Marketing Mix Modeling is a powerful statistical analysis method that empowers marketers to understand the role of each marketing channel or campaign in driving business growth. By examining how different marketing channels interact with one another, MMM identifies the most effective channels and campaigns, enabling marketers to optimize their marketing budgets and investments for future success.

This way, marketers can identify the most effective channels and campaigns, and make better decisions about where to invest their budgets in the future.

Building a marketing mix model can be a complex process, but it's worth the effort. However, there are two major challenges that marketers need to be aware of in order to ensure the success of their MMM project: data silos and data activation.

The Role of Data Silos in MMM's Effectiveness

Data silos pose a significant hurdle to the success of MMM. When marketing data is trapped in separate silos, it becomes challenging to access it, analyze it, and understand how various activities impact overall growth.

This lack of visibility hinders the understanding of how different channels interact, leading to inaccurate results in MMM models. Marketers need a complete picture of the impact of marketing activities on sales to make informed decisions about budget allocation.

Ways data silos can impact MMM:

• Inaccurate Results: Siloed data leads to incomplete and misleading insights in MMM models, adversely affecting decision-making about budget allocation.
• Increased Costs: Integrating data from various systems can be costly and may require additional resources or consultants.
• Delayed Insights: Integrating data from silos can be time-consuming, causing delays in obtaining valuable insights.

The Challenge of Data Activation

Once data is gathered, the next crucial step is data activation. Activating data involves preparing it for use in the MMM model. This includes cleaning and formatting the data, as well as ensuring that it is accurate and consistent.

Data activation can be a complex process, and it's important to make sure that your marketing data is accurate and consistent. If your data is not accurate, your MMM model will be inaccurate, and you won't be able to make informed decisions about your marketing budget.

There are a number of ways to ensure that marketing data is accurate and consistent. One way is to use a platform that helps you validate marketing data and ensure data quality.

Ways that data activation can impact the success of MMM.

• Accuracy: Accurate data is essential for accurate MMM models. If the data is not accurate, the results of the models will be inaccurate. This can lead to poor decision-making about how to allocate the marketing budget.
• Consistency: Consistent data is also important for MMM models. If the data is not consistent, the results of the models will not be consistent. This can make it difficult to track the performance of marketing campaigns and to make informed decisions about how to allocate the marketing budget.
• Timeliness: Timely data is also important for MMM models. If the data is not timely, the results of the models will not be timely. This can make it difficult to make informed decisions about how to allocate the marketing budget in real time.

Data silos pose a significant hurdle to the success of MMM. When marketing data is trapped in separate silos, it becomes challenging to access it, analyze it, and understand how various activities impact overall growth.

How to solve it

There are a number of things that marketers can do to bridge marketing data silos and improve data activation for MMM success.

• Identify data silos
  The first step is to identify the data silos that exist within your organization. This can be done by mapping out the different data sources and systems that are used by the marketing team.
• Determine the best way to integrate your data
  Once the data silos have been identified, the next step is to determine the best way to integrate the data. This may involve using a data warehouse or a data lake.
• Implement the integration solution
  Ensure the correct implementation of the chosen integration solution to unify data effectively.. This may involve some technical work, but it is important to make sure that the data is integrated correctly.
• Clean and format the data
  Once the data has been integrated, it is important to clean and format the data. This will ensure that the data is accurate and consistent, and that it is ready to be used in your MMM model.
• Ensure that the data is accurate
  This means checking for errors and inconsistencies, and making sure that the data is up-to-date.
• Train your team on how to use the data

In a nutshell

By bridging marketing data silos and improving data activation, you can improve the accuracy, cost-effectiveness, and timeliness of your MMM models. This will help you make better decisions about how to allocate your marketing budget and improve overall marketing performance.

Once the data has been integrated and cleaned, it is important to train your marketing team about it. This will help them to understand how to use it to improve their marketing campaigns.

About Diana Ellegaard-Daia: ‍

Diana Daia is the Head of Content Marketing at Accutics and a strategist with a no-nonsense growth approach. She is passionate about digital marketing, CRO, digital analytics, and account-based strategy. She works closely with collaborative content & influencer outreach by creating guest articles and deep-dive interviews with leading marketing and digital analytics experts.

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