Democratising marketing mix modelling

1 June 2020

Marketing strategy

Think marketing mix modelling is only for Fortune 500 companies? Think again.

In part 2 of our marketing mix modelling series, in partnership with Analytic Edge, we explain how emerging technologies and business practices have led to drastic improvements in the speed, precision and cost of our powerful prescriptive analytics engine. 


Marketing mix modelling is a technique that was first adopted by large multinational consumer packaged goods companies around the early nineties. It 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 marketing element like TV advertising, digital advertising, print advertising, pricing discounts and trade promotions etc. in terms of its contribution to sales volume or revenue. Companies then use the results and learnings to adjust their marketing tactics and strategies to drive maximum growth.


Want to re-wind back to part 1: why invest in marketing mix modelling?



Early adoption was limited to tier 1 brands


For many years from the time it first came into use, only the largest companies and brands with huge marketing budgets adopted this practice on a wide scale. In recent years, more and more companies - regardless of their size - in marketing-heavy industries such as retail, pharmaceuticals, financial services, telecom, automotive and travel and hospitality have started adopting Marketing Mix Modeling. However, the scale of adoption by medium or small companies still remains extremely low.


Awareness and perception challenges


The reasons for this are two-fold. First, many relatively smaller companies who are now spending more significant amounts on marketing are just not aware of this solution that can help them maximise return on investment on their marketing spends. And second, even among medium and smaller sized companies who know of marketing mix modelling, there is a perception that it is a very expensive proposition and therefore affordable and feasible only for very large companies with marketing budgets in the tens or hundreds of millions of dollars.


Why this lack of awareness about marketing mix modelling among smaller companies? Or why do they perceive it to be expensive and exclusively for the biggest marketing spenders? Let’s look a little closer.


Low awareness


The truth is marketing analytics providers have for years focused their efforts mainly on the low-hanging fruit - the biggest brands and marketing spenders for whom marketing mix modelling has the potential to deliver the maximum impact in terms of ROI. Few providers, if any, have reached out to smaller companies with more modest marketing budgets to educate them about this analytics solution and its benefits. As a result, awareness among smaller companies is abysmally low leading to negligible adoption rates. A sizeable market for marketing analytics including tools such as marketing mix modelling exists among Tier 2 and Tier 3 companies (as categorised by quantum of marketing budgets). The first task analytics providers must initiate is to build awareness and educate this untapped market about the potential of marketing analytics.


(Not unjustified, but) mistaken perceptions


For a long time and to a large extent even today, marketing mix modelling was typically provided by large consulting companies for big-brand clients. The process was time and effort-intensive. It involved collecting, reviewing and ingesting data from numerous sources, employing data scientists and statistical experts to build the right models, and finally running the models to generate insights. This resulted in the process being prohibitively expensive, and contributed to a (not unjustified)  perception that it was feasible and affordable only for Tier 1 or Fortune 500 companies.   




Today's new technology & business models


Fortunately, things are changing. Analytics firms today are harnessing the power of technology and automation to drastically improve the way marketing mix modelling is delivered.


Latest data from numerous sources is collected continuously and data ingestion is being automated


  • Technologies such as artificial intelligence (AI) and machine learning (ML) are being leveraged to ensure data quality control and to identify incorrect data and outliers
  • Technology and computing power are being used to crunch large sets of data, run multiple iterations and build accurate models quickly and efficiently based on the latest data
  • Reporting and insight generation is being automated by harnessing tools like natural language processing (NLP) and natural language generation (NLG)
  • And intuitive interfaces and easy-to-use tools are increasingly bringing marketing mix modelling in-house and making it transparent and “do-it-yourself”


In addition to these improvements in the process itself, analytics firms now offer newer deployment and business models including hosted and “pay-per-use” models which demand minimal upfront investment and very nominal ongoing costs by companies.



Democratising marketing mix modelling


All this has helped truly democratise marketing mix modelling. It is now faster to deploy, easier to use and much more affordable for even Tier 2 or Tier 3 companies. Today, it is entirely conceivable for a brand with, say, a $5 million to $10 million marketing budget to adopt marketing mix modelling and realise a significant ROI benefit on its marketing spends at a feasible cost.   


What’s more, the improvements in marketing mix modelling have also made it ‘always-on’. This means it continuously measures marketing effectiveness and delivers insights that are near real-time more actionable.


So, if you are a company that spends a moderate yet significant amount on marketing but thought marketing mix modelling was not for you, think again! With the solutions available today, you could literally log in to the intuitive interface, evaluate recent marketing campaigns, rapidly update models based on the latest data, and generate real-time insights on demand to optimise your marketing investments on-the-go and maximise return on marketing investment - at a price point that more than pays for itself!


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If you'd like to hear more about our marketing mix modelling offering, subscribe to Frame or live chat to the team right here on this page. Why not say hi to Stuart (our Sydney MD managing our technology partnerships) on LinkedIn too?

Tags: ROI, Analytics, Big data, Marketing mix, Marketing effectiveness, Marketing mix modelling