In today's workplace, marketers are forced to come up with new and improved ways of gaining product revenues. Understanding how much media to use and which mediums are most effective lead to discussions on how to efficiently promote sales. How is this process done? Simple, through a method called marketing mix modeling.
As defined by Google: "Marketing Mix Modeling (MMM) is a way for marketers to gain visibility into the extent to which business results, such as sales, are driven through marketing initiatives... In layman's terms, MMM seeks to demonstrate how much business success was generated by controllable marketing variables, otherwise known as the four Ps of marketing: Price, Product, Place and Promotions."
This model for statistical analysis allows marketers to use regressions and time series data to estimate how impactful future marketing tactics will be on potential sales possibilities. Sounds like a whole bunch of fancy words put together, right? Well, the idea behind this strategy is actually quite simple. It's pretty much correlating data on previous marketing spending with business performance, and using that information to make data-backed decisions on where to spend future budgets. A few data component points which are measured could be:
- Base and incremental sales/volume
- Media and advertising
- Sales promotions offered
- Distribution costs
- Competition costs
When these statistics are presented in user-friendly visualizations, they can be incredibly helpful for marketers to use to their advantage. When the gathered data is presented accordingly, it allows anyone from an individual analyst to an entire marketing agency to decide where to allocate marketing budgets efficiently for future spending quarters.
Let's paint a scenario. The sales report finally came in for the new quarter and it's sub-par to say the least. Management is going to wonder why this number is lacking, and, unfortunately for us marketers, it's our responsibility and we'll be the ones to blame. Instead of guessing what the issue is, we look at different factual variables in order to connect the dots and come up with a solution. This is exactly what Marketing Mix Modeling allows us to do. It gives marketers the opportunity to understand how business results are directly related to advertising behavior. Once correlations are observed, companies can understand where exact budget and money allocations are going and what the results are.
The biggest advantage of this approach is that it alleviates spending confusion. This basically means that money won't be randomly poured into channels that are inherently cost-exhausting with no immediate benefits. On the flip side, some of the more common critiques of this practice are the infrequency of reports and the detail level of the actual research. The real issue is that valuable data points aren't being discovered. Take a look at these two statistics from this report by HubSpot:
- Twenty-eight percent of marketers say securing enough budget is their top marketing challenge
- Marketers that calculate ROI are 1.6 times more likely to receive higher budgets
From a data perspective, proving how certain social channels can offer considerable returns is one of the biggest steps into swaying your higher-ups to approve budgets. For example, if social media paid advertisements work well, it becomes your job to prove how they can have a positive impact for prospective future planning.
Nostradamus looked at the stars to see his prophecies unfold; we marketers look at something else...data.
Numbers confirm decision-making and ensure that the right channels are being funded. Without hard facts, budget arrangements would have a sense of uncertainty and outcomes would have no backing. As much as opinionated thoughts come into question when deciding what works and what doesn't, there's much more to brand building than picking numbers out of a hat.
Data comes in many shapes and sizes, so fully understanding how to harness it is arguably the most important element of marketing mix modeling. Raw numbers don't resonate well without being affiliated to something of substance, so relevancy is key in coordinating your organization with the data you present. Showing changes over time is also a great way to visually represent whatever you're trying to confirm. Using business intelligence and data analysis programs that are available on the Web like Tableau, Qlik Sense or Microsoft Power BI can translate your data into a language that management understands. Pie charts, line graphs, scattered plots, etc., can visually depict correlations of what actions have positive and negative impacts on the company as a whole.
The other part of this is to set and align results with the business goals your team wants to produce. Having a set target will guide the focus for data requirements that are addressed during this course, and in the end will prevent any uncertainty of what's being put on display. Establish goals and achieve brand prosperity.
Marketing mix modeling should be your company's go-to source for time, money and energy allotment into different advertising tunnels. This process provides marketers with reassurance that their campaign plans are profitable, and will accelerate brand awareness, thus making everyone happy. Use it and you'll see just how beneficial it can be.
Jacob Smart is a creative content writer and marketing expert for the SEO agency Aumcore. He loves writing blogs and learning about the industry, relevant to creative development and advancements in technology.