Frequently Asked Questions
What is Marketing Mix Modeling?
What Is Marketing Mix Modeling or MMM?
Marketing Mix Modeling (MMM) is an advanced analytical technique that enables marketers to measure and improve the impact of their media and marketing efforts. It relies on statistical methods, namely multivariate regression analysis. It uses as input sales and marketing time series data to estimate the impact of various marketing tactics (marketing mix) on sales and then forecast their impact on future sets of tactics. It is often used to optimize advertising mix and promotional tactics respecting the sales revenue or profit.
What is Customer-segment Mix Modeling?
Customer-segment Mix Modeling (CMM) is based on the idea of segmenting the market to groups of customers who share similar behavior and reactions to marketing activities. Each one of the obtained segments need to be modeled to get detailed and very specific customer insight. This helps to get more accurate data-driven decisions. By focusing on the consumer segments, marketers will be able to have more targeted messages for each segment and therefore, embracing the customer first approach. Subsequently, this will lead the business to optimize future campaigns on the medium, short and long term.
CMM works at an individual consumer level, it is more actionable; more capable of measuring consumer relationships
with brands; better suited to measuring digital media; and tailored to an increasingly addressable advertising future.
In other words, CMM can measure marketing ROI at more sophisticated levels and is more actionable for the marketer because it can measure marketing ROI at an audience level and therefore direct targeting decisions.
What is the difference between Media Mix Modeling and Marketing Mix Modeling?
Media Mix Modeling is an analysis technique that allows marketers to measure the impact of their advertising campaigns based only on media variables to determine how various elements contribute to the evolution of the KPI.
Marketing Mix Modeling on the other hand, includes other variables such as promotion, price, product changes…
When it comes to modeling your KPI, we recommend to include as many variables impacting your KPI as possible so that will give you a holistic and rounded view on what’s really driving your performance.
Isn’t Marketing Mix Modeling just for large enterprise brands?
No it’s not. Regardless of their sizes, all companies will benefit from adopting MMM. Marketing Effectiveness helps your brand maximize on return and get a deeper understanding of how your business actually functions, and what channel works best. From these insights one can optimize their budgeting plan, maximize their revenues while minimizing their spend. And that can bring more benefits to small entreprises to raise their brand awareness and sales, thus growing the company.
MMM is also suitable for any media and analytics agency or advertiser no matter the size of the company. The only condition for conducting Marketing Mix Modeling analysis is to have enough data (usually a minimum of 2 years historical data). The data must also be reviewed and validated to be sure of its consistency and accuracy.
How to Measure Marketing Effectiveness?
Marketing effectiveness could be measured through Marketing Mix Modeling (MMM). It is an advanced analytical technique generally based on regression analysis. It enables marketers to:
- Measure ROI/MROI and impact of their media and marketing efforts.
- Optimize budgets across channels and campaigns.
- Simulate the outcome of various media and marketing plans.
→ MMM is based on applying regression techniques to historical time series to study the correlation between different independent variables ( e.g. Media, Marketing, Sesonality, Competition etc.) and a chosen KPI e.g. Sales, Conversion etc.
According to Gartner, measurement methods based on Marketing Mix Modeling Mesaurement can yield 20% to 30% improvement in the efficiency of marketing spending, primarily by optimizing media (Gartner 2016).
The Marketing Mix Modeling scenery is changing fast with companies of all sizes showing interest in adopting MMM techniques to measure the true impact of their marketing activities and optimizing their budgets. This need is fueled by the rise in spending, the abundance of media channels and the good PR around the adoption of AI and Data Analytics techniques in the media industry.
How complex is Marketing Mix Modeling?
Marketing Mix Modeling, as a concept, is relatively easy to understand. It is an analytical solution that help marketers to understand and simulate the effect of advertising (volume decomposition), and to optimize tactics and budget spend.
Even though the concept is easy, modeling and interpretation needs to have advanced analytics skills and the right tools to accomplish insights extraction and strategic path shaping.
Our Udemy Beginner course is the best way to familiarize yourself with the ABC’s of Marketing Mix Modeling.
What is the minimum data required to perform a Marketing Mix Modelling project?
You need to have at least sales data per month and if possible by week. Ideally, 3 years’ worth of data is recommended. If not possible you can do with 2 years. You also need to have data about the main campaigns run and the investments in the different channels.
It is also advised to have Marketing data (price, promotions, distribution).
What is the CRISP-DM methodology?
CRISP-DM stands for Cross-Industry Process for Data Mining. The CRISP-DM methodology provides a structured approach to the planning of a data mining/data science project. Below are the 6 phases of the process:
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Business understanding
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Data understanding
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Data preparation
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Modelling
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Evaluation
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Deployment
