Watch outs when using MMM
We focus on four main watch out areas when using Market Mix Modelling (MMM). First, we'll ensure you have the right data and approach for your MMM. Then, we'll discuss the importance of having the right internal team or partner. Next, we'll dive into the software requirements for effective MMM delivery. Finally, we'll explore whether you have enough time and budget to commit to the level of MMM you need
Do you have the right data and approach for your Market Mix Modelling (MMM)?
Data quality is crucial! Make sure your data is accurate, complete, and reliable. Flawed insights and inaccurate recommendations can result from using inaccurate or incomplete data. Keep data quality in check by regularly auditing and validating your data sources. Imperfect data can still be used, but it's important to discuss any limitations or caveats with your MMM partner to ensure the outputs can be trusted.
Defining the scope and objectives of your MMM model is another key aspect. Ensure it captures all relevant marketing variables and factors that impact sales or business outcomes. Leaving out critical variables can lead to incomplete insights and suboptimal decision-making.
When it comes to the time period, be mindful of capturing long-term trends without diluting the impact of recent marketing activities. Generally, using 3-4 years of historical data is recommended. However, it's always a good idea to discuss shorter time periods with an expert before starting if you don't have all the historical data.
Validating your MMM model is essential. Ensure your MMM is statistically robust as well as compare its predictions with actual outcomes and real-world scenarios to assess accuracy and reliability. These validation processes help ensure the model aligns with historical performance.
Lastly, keep in mind that marketing dynamics and consumer behavior evolve over time. Continuously monitor the market, evaluate your model's performance, and adapt your MMM approach accordingly. Regularly update and refine the model as new data becomes available. The ideal frequency of updates depends on your business cycle and investment levels.
By following these guidelines, you'll be on the right track to ensure you have the right data and approach for your MMM, leading to accurate insights and informed decision-making.
Do you have the right internal team or analytics partner for your MMM?
They play a vital role in the success of your MMM implementation.
A key client contact is indispensable, serving as the bridge between you and the MMM team. They ensure effective communication, align objectives with strategic goals, and provide valuable knowledge and feedback for accurate modelling and interpretation of results. With their involvement, data gathering, stakeholder buy-in, and implementation of MMM recommendations are facilitated.
Your key analytic partner should possess expertise in MMM methodologies, statistical modelling, and data analysis. They collaborate closely with you, gather relevant data, and develop robust MMM models. Effective communication skills are crucial to explain technical concepts to non-technical stakeholders and provide guidance throughout the process.
To ensure actionable insights, make sure the MMM findings align with your company's strategic goals and can be practically implemented to optimize marketing strategies and investment decisions. Consider change management to smoothly integrate MMM insights into decision-making processes.
By ensuring you have the right team and partner you'll be well-equipped to leverage MMM for actionable insights and drive business success.
Is your software equipped to effectively deliver MMM
It's important to have the right tools to maximize the potential of your MMM efforts.
Firstly, the software should employ robust statistical modelling techniques like regression analysis, time series analysis, and machine learning algorithms. This allows for customization and flexibility in selecting the appropriate techniques based on your specific business context.
The software should also support analysis at different levels of granularity, such as region, store, product category, channel, or campaign. Being able to adjust the level of detail easily helps capture important variations in marketing activities and their impact on outcomes.
Scalability and performance are essential considerations. The software should handle large datasets efficiently, perform complex calculations quickly, and be scalable to accommodate growing data volumes and the increasing complexity of marketing models.
Visualization and reporting capabilities are vital for presenting modelling results effectively. Look for software that provides intuitive and interactive visualization features, allowing you to generate reports, charts, graphs, dashboards and run future facing optimisation and forecasting scenarios. Effective communication of insights to stakeholders in a clear and compelling manner is key.
Lastly, a user-friendly interface is important. The software should be intuitive and easy to navigate, catering to both technical and non-technical users. This ensures that everyone can effectively utilize its features and maximize its potential.
By ensuring you have the right software, you'll be equipped with the necessary tools to deliver successful MMM, gain actionable insights, and drive your business towards success.
Do you have enough time and budget to commit to the level of MMM you require?
MMM is not set up over night and requires time and investment to get it right.
Comprehensive data gathering and analysis are essential for accurate and meaningful results. This involves collecting data from various sources, cleansing it, and validating it. Sufficient time should be allocated to these tasks to ensure the data is reliable and of high quality.
Engaging and gaining buy-in from key stakeholders is crucial for successful MMM. This requires effective communication, collaboration, and education about the value and benefits of MMM. Allowing enough time for stakeholder engagement ensures their understanding and acceptance of the methodology, results, and recommendations. This leads to better adoption of insights in decision-making processes.
Implementing the recommendations derived from MMM is vital for driving improvements in marketing performance and business results. Sufficient resources, including time, should be allocated to execute strategic changes effectively. This ensures that the insights generated from MMM translate into actionable outcomes.
Budget plays a role in defining the complexity of the models and the frequency of updates. A larger budget allows for evaluating more key performance indicators (KPIs) and at a more granular level. Increasing the granularity captures intricate relationships and provides more accurate insights. A larger budget also permits more frequent MMM updates, allowing businesses to capture real-time market dynamics and make timely adjustments to their marketing strategies. However, if budgets are limited, there might need to be a compromise between the number and complexity of models and the frequency of updates.
Considering the available time and budget ensures that you can commit to the level of MMM required for accurate insights and effective decision-making.