Published On: 22 Jan 2024
Marketing Mix Modeling (MMM) and Media Mix Modeling (MxM) are often mistakenly used interchangeably. However, there are distinct differences between the two. If you are here, you likely understand that media mix and marketing mix models deal with different types of marketing data.
Media Mix Modeling analyzes the effectiveness of different media channels within the marketing mix to optimize the advertising spend and maximize ROI. On the other hand, Marketing Mix Modeling measures the impact of various marketing elements, including external factors like political scenarios, inflation, recession, seasonality, and natural disasters, to understand their effect on sales and marketing ROI.
There are both similarities and differences between media mix and marketing modeling. This article is all set to explain to you these key differences (and some similarities) between the two MMMs.
Marketing mix models identify the impact of different marketing initiatives on the overall ROI. It is a holistic approach focusing on external factors (political, environmental, economic, financial) and analyzing the extent to which these factors influence the performance of a marketing campaign.
A marketing mix model applies statistical methods like correlation trend analysis to understand how the internal and external variables are associated with impacting the sales or ROI of a brand.
In the image below, Gabriele Franco, founder of Cassandra, discusses only marketing mix modeling. He explains what problems B2B brands encounter in measuring campaign effectiveness and why MMM is the easiest solution available:
The components of a marketing mix model are as follows:
The data inputs required in marketing mix modeling are segregated into three categories:
Media Mix Modeling is a focused approach that zeroes in on the performance of individual media channels like television, social media, and advertising platforms. It leverages historical data to offer insights into campaign performance and future potential.
Bilal Adham, Group Vice President at DP World, explains why major players like Facebook Amazon are slowly shifting to media mix modeling in the below image:
Brands segregate their media mix modeling initiatives and outcomes depending on the following drivers:
Media Mix Modeling is focused on channel-specific data, including
While both models aim to optimize marketing resource allocation, they differ significantly in approach and data utilization:
But that's not all. The approaches and data types used in media mix modeling and marketing mix modeling are largely different. Here's a comparative analysis of both:
Marketing mix modeling
Media mix modeling
To offer a holistic overview of all factors (internal and external) affecting the marketing performance of a business.
To identify channel-specific factors on a deeper level that optimize the advertising spend of a campaign to achieve desired results.
Focused on category-level performance measurement, MMM helps marketers develop an integrated overview of the market category as a whole and not just a brand-specific overview.
Brand-level overview of the marketing mix. This approach focuses on data-driven insights from one or more media channels to measure the impact of advertising.
KPI-based data, marketing data, and non-marketing external factors.
Sales data, customer data, and campaign spending data.
Which internal and external factors are the key driving factors in the sales revenue generated from advertising campaigns?
How do you achieve the maximum impact from your advertising campaigns?
Ultimately, it all comes down to your goal and requirements when deciding between the marketing and media mix models.
The marketing mix model is beneficial when you want to:
Media mix modeling is best suited when you want to:
Here is the case study of an FMCG brand and its strategic shift to MMM led to a 15% increase in marketing ROI.
Suppose you run an ecommerce store selling luxury bags. Currently, your target marketing channels are:
You have implemented media mix modeling to get data-driven insights into which of these channels contribute the most to your overall sales ROI.
Here are the possible insights a media mix modeling will derive in the case of the ecommerce store:
To get these insights, a media mix modeling will demand the following data inputs from the ecommerce store:
Now that you have a clear idea about marketing mix modeling vs. media mix modeling, it is time to try both approaches.
Starting with marketing mix modeling is a smarter idea, as you need a holistic overview of your marketing initiatives before diving deeper into a specific channel.
The perfect tool to begin your association with marketing mix modeling is Lifesight which helps brands:
Want to cut down unnecessary ad budgets and predict future outcomes accurately?
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