If there is a talk of Marketing Mix Optimization (MMO), then Marketing Mix Modelling follows suit. As MMO resonates with every marketing department’s need to optimize marketing investments towards generating maximum sales and profits, the case of this apparel retailer is a case in point in reiterating the significance of Marketing Mix Optimization.

An apparel retailer with a physical and a digital empire wants every penny spent from its marketing budget yield incremental sales. With so many hurdles to cross, the retailer sets out to analyse various marketing features attributing to sales performance – Attribute modelling does help the retailer understand how sales and conversions resulted from channels and campaigns – and analyze how marketing strategies, investment and efforts impact marketing performance.

In short, the apparel retailer wants to optimize the marketing mix in enhancing marketing efficiency and ROI, and driving incremental sales from every marketing dollar. Accomplishing the retailer’s objective is better served by creating Marketing Mix Modelling (MMM) models to understand the effect of various marketing variables on sales, create the best marketing mix to achieve the objective.

How Marketing Mix Optimization brings best returns from marketing investments, help drive sales and revenue growth?

Aligning Goals with MMO

Reaping value from Marketing Mix Optimization begins by aligning goals with MMO. In turn, goals are about finding answers to some marketing-related queries like:

  • What is the typical customer journey?
  • What channels form a part of the customer journey?
  • What are the marketing touchpoints across the journey?
  • Where to increase the marketing budget?
  • Are there marketing strongpoints and weak points with respect to channels?
  • What issues bring down marketing performance?
  • What to do if a competitor increases media spend by 10%
  • What if competition reduces price?
  • What’s the optimal touchpoint mix?
  • Where to invest marketing in terms of channels and touchpoints across the customer journey?
  • What are customer sweet spots in the lifecycle, from prospecting to loyalty?

Marketing Mix Optimization also sets the trend to unearth the impact of one channel over others, and impact of campaigns and messages across channels, determine best times to roll out campaigns and messages as well as identify areas deserving optimal marketing spend. Insights into critical marketing elements acquired through Marketing Mix Optimization go a long way in improving marketing effectiveness, sales and revenue growth.

Dependent and Independent variables

The need to find areas of optimal marketing investments to enable sales growth puts Marketing Mix Modelling into perspective. The same can be vouched if we were to find the impact of marketing investments on sales revenue or the market share. In effect, MMM is about determining the influence of various independent marketing variables on dependent variables such as sales growth or profits.

If sales growth is the object of measure (dependent variable), how various independent variables like campaign spend, price, distribution, promotional spend, product features, product performance produce an impact on the outcome, which is sales growth, becomes the core component of the Marketing Mix Modelling exercise. The lens then falls on regression techniques to build MMM in predicting the optimal mix of independent variables that can influence the desired outcome.

Regression technique for MMM

The core of regression deals with analysing the impact produced by independent variables on the outcome related to the dependent variable. Linear regression model becomes a perfect match when there is linearity involved in relationship between dependent variable and that of independent variables. And as we look into the impact of various independent variables on the continuous dependent variable, sales growth for instance, multi-Linear Regression fits in to determine the relationship between dependent and independent variables.

Using regression techniques for building the Marketing Mix Model calls for using relevant data. Data used for Marketing Mix Modelling spreads across promotional, product features as well as performance, industry data, service, sales, price, profit, advertising, revenue and competitor data.

Marketing Mix Modeling Answers

There are critical Marketing Mix Modeling answers lying in the wait. Though the answers tend to hinge on the objective of a company to leverage Marketing Mix Optimization, say to maximize sales or profit or brand interest or new customers, MMM helps make a comparison of marketing efficiency across channels like TV ads, print, websites, Email marketing and social networks and create the optimal marketing mix to determine how incremental sales can be driven from every marketing dollar. In comparing ROI efficiencies across channels, insights can be used to create the best marketing mix to drive better sales and revenue.

Marketing Mix Modeling also provides answers towards decreasing cost of distribution, enhancing returns on advertising and promotions and promoting optimal price strategy to maximize returns on every marketing buck spent.

The key to extracting value from Marketing Mix Optimization lies in building holistic Marketing Mix Models taking traditional and digital media, consumer attitudes, operations and other external factors into account. Granularity of variables depending on an enterprise’s objective can help build robust predictive models to accelerate speed to marketing decisions in terms of using the optimal marketing mix to increase returns on marketing investments, enable sales and profit growth.