Marketing Mix Modelling – Data au cœur de ROI 

Traditional marketing évolue. Between digital tools, the proliferation of available data and the awakening of consumers, it is high time to change stratégie. Il s'agit 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’ retour sur investissement. découvrez MMM and our tips for implementing it effectively. 

Qu'est-ce que Marketing Mix Modelling? 

MMM: intelligent models for marketing 

Marketing Mix Modelling places data au cœur de its stratégie. But it is not just a matter of analysing information related to the audience cible, 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 l'impact de each action on the company’s sales and brand image. publicité on Google Search, partnerships with influencers, organic videos on TikTok, a poster campagne in the Paris metro… Marketing Mix Modelling measures everything, de traditional à digital methods. 

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 MMM	The disadvantages of MMM
publicité budget optimisation: you allocate resources where they have the greatest impact.	Statistical modelling: far de 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 maximiser your retour sur investissement.	Data processing: as the entire stratégie is based on data, MMM requires considerable upstream work à ensure data quality.
Predictive capability: thanks to the trends identified by the models, you can anticipate the future behaviour of your audience cible.	The proliferation of platforms: new social networks (such as TikTok) make data modelling more difficult.
Adaptability: you adjust your marketing stratégie as soon as the market shows signs of change.

comment succeed with your MMM stratégie? 

While Marketing Mix Modelling enables companies to maximiser their ROI, it is not that simple to mettre en œuvre. So how can you guarantee its success? Voici 5 tips: 

• Data completeness: the entire MMM stratégie is based on data. And all information is useful. Not just les dernières 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 vous permet de 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: Bien que 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: en plus to permettant model creation, artificial intelligence and machine learning tools facilitate the automatisation 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 mettre en œuvre an MMM stratégie? Feel free to contact our tracking agency to effectively measure your marketing activities.