MMM — A deeper dive

Akanksha Anand (Ak)
5 min readJan 24, 2024

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After having covered the basics of MMM, let’s scan how MMM works.

Market Mix Modeling variables

MMM dissects your outcomes based on channels, enabling you to identify the marketing activities that exert the most substantial influence on your desired results.

It incorporates multiple variables to assess the impact and efficacy of your marketing endeavors. These variables commonly encompass:

  • Sales data: Including historical figures like unit sales, revenue, and market share, provides insights into our performance.
  • Marketing Spend: Details on marketing spend are crucial, outlining the allocation of the budget across different activities like advertising, promotions, and sales support.
  • Market and consumer data: They offer a comprehensive view, encompassing consumer demographics, attitudes, and behaviors, along with insights into market trends and conditions.
  • Product data: Our product data, covering features, pricing, and distribution, is essential for understanding our offerings in the market.
  • Economic data: Including indicators like interest rates, inflation, and consumer confidence, aids in gauging the broader economic landscape.
  • Competitor data: It provides valuable information on their marketing activities, including advertising spend and promotions, allowing us to stay competitive and informed.

MMM Technique:

MMM uses Linear Regression Model where the dependent variables are sales data or market share and the independent variables include market data like sample distribution, digital data like impressions, clicks, website visits as well as customer data.

MMM breaks down total sales into two parts:

Sales components
  1. Base sales: Also known as Brand Equity, this represents the inherent demand for the product influenced by economic factors such as pricing, long-term trends, and seasonality. Additionally, qualitative factors like brand awareness and loyalty contribute to this component.
  2. Incremental sales: These are sales generated through marketing and promotional efforts. This segment can be further dissected into sales attributed to specific marketing components, such as television advertising, radio advertising, print advertising (in magazines and newspapers), coupons, direct mail, Internet promotions, feature or display promotions, and temporary price reductions. Some of these activities yield short-term results (coupons, promotions), while others have a longer-term impact (TV, radio, magazine/print).

The other features included are then transformed to ensure that there is a linear relationship between independent variables and dependent variables.

Ad-stocking is one such effect that is frequently considered while implementing linear regression models. It is a marketing concept used to describe the prolonged or lingering effects of advertising on consumer behavior over time.

Sales carryover refers to the continuation of sales momentum from one period to the next.

Control variables are the various factors like seasonality and other economic factors like inflation are also kept in consideration while defining the linear relationship

This gives us the final equation in the below form:

Sales = Base sales + Promotions with Ad stock effect + control variables

MMM Use Case

Marketing mix modeling is a robust tool that can assist you in uncovering incrementality, gauging marketing effectiveness, evaluating ROI, predicting future performance, and achieving various other insights. It's time to look into the kind of analytic insights that we can gain from MMM implementation.

  1. ROI Analysis: ROI Analysis aids in answering which marketing investment is giving the best returns. Analyzing ROI is likely the most prevalent application of marketing mix modeling. It gives business leaders a rapid overview of the most effective allocation of their funds. This enables them to make informed decisions on adjusting marketing investment strategies to ensure optimal returns.
  2. Forecasting: When it comes to forecasting and MMM, the focus shifts from glimpses into future sales and revenue to strategically planning upcoming marketing budgets and overall expenditures. Considering the numerous teams eager to understand the trajectory of marketing spend in the coming months or years, MMM may not provide precise future figures, but it proves valuable in offering rough predictions of budget trends and the potential consequences of any adjustments. Despite the lack of exact numbers, this predictive capability is beneficial for other business units to make well-informed plans.
  3. Pricing: By utilizing the appropriate data and analysis model, you can start forecasting how the market might respond to alterations in your pricing framework. The below questions are extremely challenging and intricate, demanding a similarly complex analysis to reach a dependable conclusion:
  • Lowering your product or service price: Will it attract more customers?
  • Market impact: Can a price drop help you gain market share from competitors?
  • Perceived value: Does reducing the price affect how customers perceive the value of your product or service?

Understanding MMM from a Business Perspective

As we learned, ROI analysis is one of the most popular applications of MMM but reading it right also plays a crucial role. Having said that, a successful marketing mix should consider the response in the days and weeks following exposure, as well as the overall halo effects.

While media exposures can lead to immediate incremental conversion, their influence is frequently misunderstood or misattributed in both the short and long term. Hence, to develop an accurate and effective Marketing Mix Modeling strategy, it’s essential to take a holistic view of media effectiveness, accounting for long-term effects and indirect impacts.

Factors affecting ROI:

  • External Factors: These include weather, competition, etc. It’s essential to grasp how weather and competitive factors come into play and contribute to the overall return on investment (ROI) of the marketing mix for accurate and effective Marketing Mix Modeling. Natural demand is subject to changes over time and varies among different customer types and competitors’ strategies. It’s essential not to underestimate the impact of weather on consumer behavior and demand, particularly in industries such as retail and hospitality.
  • Online and Offline media: Businesses invest in both online and offline media as the customers interact with products and brands through various channels, highlighting the significance of incorporating both offline and online media into their strategy. Every form of media has a comprehensive impact across channels, emphasizing the importance of having a physical store presence and online visibility for a holistic consumer experience.

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Akanksha Anand (Ak)

Data @CIAI, Marketing Media Analytics for Life Science and Healthcare