Marketing Mix Modeling

The MMM differentiates itself by providing a holistic approach that considers multiple variables, such as pricing, promotions, advertising, weather, promotional dates, among others, to understand how each affects marketing results. This contrasts with other tools that may focus on specific metrics or a single marketing channel.

It absolutely makes sense to start working on an MMM even if you already have an MTA model. These models are complementary and address different aspects of marketing analysis. MTA focuses on granularity, detailing the customer journey and specific campaigns, while MMM focuses on making decisions at a higher level such as cross-channel and omnichannel strategies. Combining both models can provide a more comprehensive and strategic view of marketing performance.

Marketing Mix Modeling (MMM) offers several advantages for companies. Its omni-channel capability allows for the integration of online and offline data for a more complete view. In addition, it is privacy-friendly as it does not require specific user data.

This makes it more reliable and in line with current privacy policies. Finally, it provides a deep understanding of the impact of marketing on business results, enabling accurate assessment of ROI and identification of areas for improvement in resource allocation.

The MMM can help you optimize your marketing budget by identifying which marketing channels and activities are generating the greatest return on investment (ROI). By understanding the relative impact of each element of the marketing mix on sales and other business results, you can allocate your budget more effectively to maximize results.

MMM can help improve the effectiveness and efficiency of marketing campaigns by identifying which activities and channels generate the best results based on ROI and other KPIs. This allows companies to focus their efforts and resources on the most effective strategies, thus optimizing the overall performance of their marketing campaigns.

The MMM can analyze a wide range of metrics and KPIs related to business performance, such as sales, revenue, traffic, clicks, market share, return on advertising spend (ROAS), brand reach, among others. This enables a comprehensive assessment of the impact of marketing activities and other variables that affect the success of the brand on commercial results.

Yes, the MMM can identify the effect of interactions between different marketing channels by modeling how marketing activities in one channel can influence performance in other channels. This provides a more complete understanding of how omnichannel marketing strategies affect business outcomes and how to optimize resource allocation between different channels.

The accuracy and reliability of the MMM results are evaluated using various techniques, such as analysis of variance, hypothesis testing, cross-validation and comparison with real data. It is important to perform rigorous validation of the model using historical data and, where possible, to test in controlled environments before implementing changes to marketing strategies based on the model results.

It is possible that your brand does not yet have sufficient historical or volume data to reach statistically significant conclusions. Even so, we also support you in the preparation of the data so that the measurement is optimal and we can soon work on a model. Contact us so that we can review it together and draw up a strategic plan with different phases from data preparation to modelling and extraction of actionable insights.

The implementation of the MMM always starts with the review, collection and preparation of relevant data, within the scope of the model that is defined. From this data and a statistical modelling process, correlations are worked out, adjusting to the specific characteristics of your business and iterating on all those variables that can affect your target KPI. Once the model is trained and validated, it is time to analyse the output, draw conclusions and make informed decisions about the allocation of marketing resources. This process is continuous as the model is fed with new data on a recurring basis.

The time required to implement the MMM and see tangible results can vary depending on the complexity of your business, the availability and quality of the data, and the sophistication of the model used. However, in general, you can expect the implementation process to take several months, and it may take longer to see significant and sustainable results as the model is fine-tuned and validated.

Yes, the MMM can and should adapt to changes in the market and in marketing strategies to maintain its relevance and usefulness over time. This may involve regularly updating the model with new data, reviewing and adjusting model variables and parameters, and incorporating new techniques and approaches as the science of marketing analytics evolves.

Sensitivity analyses and simulations are important tools in MMM that allow companies to explore different scenarios and assess the potential impact of changes in marketing strategies. This may include changes in marketing budgets, adjustments in marketing tactics or the introduction of new products or services, helping to make more informed decisions and mitigate risks.

The MMM may require a wide variety of data, ranging from historical sales data to marketing spend information, economic data, market information, consumer data, among others. The more relevant data provided, the more accurate the model results will be.

Adsmurai's MMM tool works with integrations for most of the data sources you may need (ad platforms, CRMs, GA4...). In addition, those data that do not depend on the brand but on the ecosystem and the external context (holiday calendar of each country, special dates, macroeconomic factors...) we integrate them ourselves so that they are selectable for your model.

We can update the model on-demand, as often as needed. It will also depend on the subscription plan but at least monthly.

While MMM can benefit many companies by providing a deeper understanding of the impact of their marketing activities, it is important to consider factors such as the size of the company, the availability of internal data and resources, and the complexity of business operations.

That is why at Adsmurai we have developed an innovative tool to automate much of these processes and democratize Marketing Mix Modelling. Our goal is to make this methodology available not only to large brands, but also to small and medium-sized brands in development, thus facilitating their access to valuable insights to optimize their marketing strategies.