Author: Rahul Budhraja- Co-Founder and Managing Partner, Analytic Edge 

It’s budgeting season. And Brian is at work trying to figure out answers to a dozen questions on his mind.

“Has my Out-of-Home advertising really been contributing to sales? Should I turn down Out-of-Home and up my spend on TV ads?  Or is more digital and social the way to go? It’s what everyone is talking about. It must be working… I think. And oh, what about discounts? Sure, they bump up volumes a little, but is that at the cost of my bottom-line?”

As marketing head for a slew of brands at SunFresh, a mid-sized juice and beverage company, Brian owns the marketing and media budget for his brands and must decide on the most optimal way to allocate it across the various options available to him.

If you are or have been a marketer responsible for budgeting and planning for one or more brands, this is a predicament you are probably familiar with.  

Marketing is one of the largest items in most companies’ budgets, and continues to grow as a percentage of the total budget. According to the Deloitte CMO Survey 2019, marketing budgets now comprise 11% of total company budgets on average. In addition, 40% of marketing leaders indicate that driving growth is their number one challenge, while a significant percentage also cite delivering measurable return on investment on their marketing activities as another key challenge.

This means marketing departments are under a lot of pressure to ensure that they maximize the return on marketing investments to drive sales growth and profitability.

And that’s not all. The landscape that marketers operate in has transformed rapidly over the past few years. Today’s marketers must consider not just traditional channels like TV, print, radio, OOH, discounts and POS promotions, but also a multitude of newer options such as social media apps, websites, search engine marketing, event marketing and more when planning their marketing mix. Add to this the impact of external factors such as the economy, seasonality, weather and competitor activity, and it becomes apparent that the biggest challenge marketers face – What is the most effective marketing mix  that will best drive sales and revenue growth? – is more complex than ever before.

This is where Marketing Mix Modeling can help.

Marketing Mix Modeling is an analytical approach that looks at the historical relationship between marketing spending and business performance to determine how each marketing activity has impacted performance.

It defines the effectiveness of each element like TV advertising, digital marketing, pricing discounts etc. in terms of its contribution to sales volume or revenue. The results and learnings are then adopted to adjust marketing tactics and strategies to drive maximum growth.

A quick look at the science (and art!) behind Marketing Mix Modeling. In a nutshell, it is about accurately defining the simultaneous relationship of various marketing activities with sales, using the statistical technique of regression. Getting the ‘model’ right for each brand and business and market is at the heart of the process. This is done by considering sales as the ‘dependent’ variable and various marketing efforts and external factors as ‘independent’ variables and running regression analyses and iterations to arrive at a model that explains the sales trends satisfactorily. The process is as much an art as it is a science. While technology does enable crunching large sets of data and running multiple iterations rapidly, identifying and selecting the right variables from amongst dozens that could impact sales, and teasing out the impact of each individual variable requires not just an intricate appreciation of econometrics, but also a deep understanding of the industry, the brand and the market.

So, how exactly does Marketing Mix Modeling help solve the challenges that marketers face? To understand this, let’s go back to Brian’s dilemma.

With a data-driven tool like Marketing Mix Modeling to help him , Brian would be able to do a number of things easily.

  • He could accurately determine the effectiveness of each marketing element like TV advertising, Out-of-Home advertising, digital marketing, discounts etc. in terms of how much each has contributed to sales. And therefore, identify what’s been working well and what’s not.
  • He could then experiment with simulations or ‘what-if’ scenarios, varying the spend on different high performing marketing elements to evaluate the impact on sales, revenues and profits
  • And finally, he could decide how much to spend on each marketing activity for each brand so that he maximizes sales volumes and achieves his targets for the next quarter.

In other words, he would be able to maximize the overall return on investment of his marketing budget to drive growth. With sharper, data-driven budget allocations based on Marketing Mix Modeling done right, Brian can expect to drive a 5% to 10% improvement in his top-line growth.

The techniques of Marketing Mix Modeling were first adopted by large consumer packaged goods companies such as The Coca Cola Company, P&G, Kraft etc. in the early nineties, but are now used as an integral part of planning by many companies – large, mid-size and small – irrespective of their size and across industries such as retail, pharmaceuticals, telecom and many others. The science of Marketing Mix Modeling itself is evolving and maturing to address the dynamic and fast-changing marketing landscape and the new challenges it throws up to marketers every day.

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Rahul Budhraja is a Co-Founder and Managing Partner, at Analytic Edge, a technology-enabled analytics solution provider for marketing and sales effectiveness. He has extensive experience of over two decades building analytical capabilities for clients in North America, Europe, and Asia.