JS eBusiness

by Joomlashack


Improve marketing effectiveness and increase ROI.

Complex array of marketing drivers contribute to sales. This complexity has led to difficulty in quantifying the contribution of each marketing element to sales leading to inefficient budget allocation. There is always a possibility that hard working element might get under invested.

Marketing Mix Modeling which uses advanced econometric principles can reveal how different elements of the marketing mix are contributing to the sales. It can also quantify the impact of competition, macroeconomic and environment on the sales. Market Mix Modeling provides deep insights, removes guesswork and makes marketing more accountable.

Typical business questions answered by Marketing Mix Model

  • Which element of the marketing mix contributes to sales and profits?
  • How do I allocate resources amongst various marketing heads to maximize sales?
  • What are the advertising threshold and saturation levels for the brand?
  • How would a price increase impact volume and profit?
  • What is the sensitivity of the brand to competitive activity?
  • What is the baseline sales for the brand?

Graphic Equalizer for marketing mix

Marketing mix model converts sales to a mathematical equation. In building the equation, it is possible to mirror realities of marketing like advertising carryover and wear out, diminishing returns and interaction effects (say between ATL investments and increase in distribution.)

From the equation it is possible to compute contribution , elasticity and ROI of each marketing element. The mathematical equation powers simulator and optimizer. Madison Business Analytics provides these tools as part of the engagement. Marketers can use the tools to increase or decrease spend on the marketing lever just as in graphic equalizers and the simulator will project the likely consequence.

Contribution and ROI of each marketing driver:

From the mathematical equation, it is possible to obtain the contribution of each driver in explaining the sales. In the process of development of MMM, various drivers could appear as insignificant in the final model. This in itself is a huge insight to the marketer.

Once the contributions of various drivers are estimated, it is typically exhibited as contribution chart. (shown along side)
In the sample contribution chart, baseline accounts for 71% of the sales while A&P contribute around 32% of the total sales. Contribution by various A&P activities are also shown. In the example, the price differential with the category average price and competitive promotion are taking away likely sales of the brand. It is also possible to identify the key competition that should be tracked by the brand. 

Once it is possible to estimate the impact of each driver, we can compute the RoI for each element in the marketing mix

Optimization and Resource Allocation

In most cases, the key outcome of MMM is to devise the optimal allocation strategy that will maximize the outcome. This is done by running an optimizer setting the minimum and maximum budget constraints based on domain expertise (role and scale of each driver), practicalities and experience.


What are the data requirements?

The following are examples of the types of data that are typically used:

  • Monthly/Weekly sales data of brand and competition both in value and volume terms
  • Monthly/weekly advertising media spend for brand and competition
  • By media (National TV, Regional TV, Print, Online etc)
  • TV GRP data
  • Consumer and trade promotion spend and calendar
  • Weighted and unweighted distribution data
  • Economic indicators, demographic and weather data

At MBA, we use Cloud Computing Infrastructure to ensure that MMM iterations are automated.

Need further information?. Please do contact us and we will get back to you within 2 business days