Today’s marketing managers require all the ammunition they can get to fight fierce competition and harness the proliferation of advanced marketing channels, in an ever more digitalized world.
Consequently, the “Marketing Mix Modeling” (MMM) field of data analytics has become indispensable in helping these managers to adopt the modern paradigm of “data-driven decision making”. MMM aids informed and thus wiser decisions, making possible the optimal spend of often considerable marketing budgets.
However, MMM services remain expensive and only afforded by big advertisers with large marketing budgets. As a result, despite the ever-growing business opportunity, Marketing Mix Modeling nonetheless struggles to become a real industry; capable of scaling to reach a wider range of clients.


Of course, every Marketing Mix Modeling practitioner aims to get the best value for their company. He or she would not then be doing their job properly if they did not consider using open source solutions such as R, after all, it is “free”, right? Some would say; “Wrong!”
The truth is this: Such “freeware” solutions are a bit like an iceberg; their true cost is largely hidden. Furthermore, the missed business opportunities may be colossal.
While R is free, it is no different than other open-source alternatives like Python or even Java in the sense that a minimum amount of coding is necessary to build tools that can do the job. Additionally, maintenance, upgrades and various subsequent modifications to meet the expectations of ever-demanding clients will always be needed. Building these tools in-house necessitates hiring developers and data scientists often at a high cost, even if the underlying technology used is freeware.
Rather than being free, such home-built systems can work out to be expensive. They are often unstable, error-prone, and present newly hired data analysts with a steep learning curve. For this reason, Marketing Mix Modeling projects usually consume a considerable amount of resources and time; hence the lack of affordability to anyone other than the largest advertisers. A much larger pool of potential customers is left out in the cold; a much broader market is just around the corner.


What is needed today to turn MMM (and other data analytics applications) into a real profitable industry, with a much larger customer pool, is to adopt a new approach. Perhaps one based on dedicated third-party software which could increase efficiency, accuracy and considerably reduce cost and complexity. Over the years, the “Marketing Mix Modeling process” has matured and has been mastered by existing practitioners. Thus begging the question: How far does it make sense for each newly created team to reinvent the wheel and build their MMM systems in-house and risk ending up with a rambling set of often inefficient and unreliable scripts?
In answer to this, many agencies have already detected the opportunity and decided to switch to third-party dedicated MMM software offering a robust and efficient process, and have readily managed to widen their customer base and increase their profits.

By Dr. Firas Jabloun

Chief Technology Officer at MASS Analytics – Creator of MassTer the Marketing Effectiveness software, that’s saving companies like yours considerable sums!