Marketing Mix Modelling - Maximise your return on investment
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    Marketing Mix Modelling – Data at the heart of ROI 

    Learn more about our expertise Tracking 19/02/2025 2 min. reading Leslie

    Traditional marketing is evolving. Between digital tools, the proliferation of available data and the awakening of consumers, it is high time to change strategy. This is precisely the objective of Marketing Mix Modelling. While the fundamentals remain the same (the famous 4Ps – Product, Price, Place and Promotion), the method is changing. Today, data is becoming the most valuable resource for boosting companies’ return on investment. Discover MMM and our tips for implementing it effectively. 

    What is Marketing Mix Modelling? 

    MMM: intelligent models for marketing 

    Marketing Mix Modelling places data at the heart of its strategy. But it is not just a matter of analysing information related to the target audience, budget, competitors, the 4Ps, etc. No, MMM creates models capable of anticipating consumer and market behaviour. 

    These models are based entirely on artificial intelligence and big data. Using linear regression techniques, marketing data teams assess the impact of each action on the company’s sales and brand image. Advertisements on Google Search, partnerships with influencers, organic videos on TikTok, a poster campaign in the Paris metro… Marketing Mix Modelling measures everything, from traditional to digital methods. 

    the 4 Ps, foundations of marketing mix modelling

    The strengths and weaknesses of Marketing Mix Modelling 

    To better understand the MMM, here is a summary table of its advantages and disadvantages. 

    The advantages of MMMThe disadvantages of MMM
    Advertising budget optimisation: you allocate resources where they have the greatest impact.Statistical modelling: far from perfect, the models used do not always take the most recent data into account. 
    Better ROI: by identifying the most effective (or least effective) actions, you maximise your return on investment.Data processing: as the entire strategy is based on data, MMM requires considerable upstream work to ensure data quality.
    Predictive capability: thanks to the trends identified by the models, you can anticipate the future behaviour of your target audience. The proliferation of platforms: new social networks (such as TikTok) make data modelling more difficult. 
    Adaptability: you adjust your marketing strategy as soon as the market shows signs of change. 

    How to succeed with your MMM strategy? 

    While Marketing Mix Modelling enables companies to maximise their ROI, it is not that simple to implement. So how can you guarantee its success? Here are 5 tips: 

    • Data completeness: the entire MMM strategy is based on data. And all information is useful. Not just the latest sales on Instagram. Historical data is also important. Overall, you will need information on investments made, sales volumes and other contextual data. 
    • Choosing KPIs: the data collected is only valuable if it allows you to gain insights. To do this, you need to select the right performance indicators. These could be sales, CAC, CLV, etc. 
    • Collaboration: marketing and data must work hand in hand to design relevant models. The former provide their market expertise, while the latter create tools that can be used by everyone. 
    • Combining analytical methods: although highly effective, Marketing Mix Modelling works best when used in conjunction with other analytical methods, such as multitouch attribution (MTA). 
    • The use of modern solutions: in addition to enabling model creation, artificial intelligence and machine learning tools facilitate the automation of data processing procedures. It would be a shame not to take advantage of these solutions at every stage of the project. 

    Would you like to implement an MMM strategy? Feel free to contact our tracking agency to effectively measure your marketing activities. 

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