In this era of multimedia, many companies have manipulated their traditional methods of business reviews to advance skills and analytics to get a comprehensive insight into sales and outcomes. Media Mixed Modeling is one of those statistical methods that make it incredibly easier to evaluate the impact of marketing efforts on your return on investments (ROI).
Let’s deeply discuss the Media Mixed Modeling to get the highest potential profits.
What Is Media Mixed Modeling (MMM)
Media Mixed is a cluster of all communication channels and campaigns a company deploys to gain market content across targeted customers. These MMM may consist of traditional advertising modes like TV, broadcast channels, social media, newspapers, or other online advertising. These communication channels assist the companies in gaining insight into what they require to target their customers potentially.
The organization takes Media Mixed Modeling as an effective step while planning its campaign’s goals and outcomes.
However, not all companies can use media Mixed effectively as it is more profitable for online markets. It helps inspect the analytics and Return of Investment of various marketing strategies, and at this step, MMM proves most effective.
How To Measure MMM
Media Mixed Modeling is a hierarchical approach that deploys all advanced tools and analytics to assess how marketing and media activities, trends, seasonality, strategies, campaigns, and various factors influence sales and potential profits. Also, it shows how these strategies contribute to the company’s ROI.
It is a marketing analysis technique that evaluates the effect of a specific strategy or marketing campaign that contributes to the company’s success. Ultimately, MMM gives you the idea of how to manipulate or improve your strategy.
Marketing analysts are using these scientific techniques to identify each marketing input’s effect on the ROI. All in all, the only goal is to determine which marketing input has potentially higher ROI and which has the least ROI.
How Does MMM Work
The objective of the MMM study is to offer the measurable result of each marketing campaign in terms of sales. And it can only achieve by quantifying the impact of pricing, advertising sponsorship, and more. Here is a guide to know how MMM works.
- Media Mixed Modeling evaluates collected and processed data across communication channels like social media, print, TV, broadcast, and other advertising modes.
- Then it applies various tools and advanced statistical analysis to understand how these campaigns prove effective for the company’s success. MMM’s metrics and variables, such as online analytics and rating sales, let the analyst get an extensive and measurable outlook of the outcome of a certain campaign.
- MMM measure two types of variables: linear and non-linear variables. It indicates that these variables are directly proportional to the sales. As much as you increase the input, the sales grow.
However, some variables are complex to evaluate, like broadcasting. If marketer analysts try to track them manually, it becomes intensely difficult. MMM, like advanced technologies, make it convenient to track the measurable impact of every marketing effort by using Artificial intelligence and advanced analytics tools regardless of channels.
Key Drivers Affect Marketing Mixed Modeling
The key drivers that may affect the MMM are categorized as
|Base Drivers||Incremental Drivers||Other Drivers|
|These may include the company’s revenue, expenses, capital costs, growth, and more.||Incremental drivers come with marketing activities such as digital spending, print advertisements, social outreach, price discounts, and so on.||Other drivers are related to other baseline factors that measure over a long time.|
Why Was MMM Developed
MMM became tremendously popular in the 1970s; Kraft was an early consumer of these models. By the launch of Jell-O, marketers were allowed to select almost all television networks and other traditional advertisement modes to promote their services and products.
Then this convention MMM approach let them inspect how it would impact sales if they were promoted at various levels across different areas of the country at different times of the year. For instance, they can promote Jell-O only in ten locations to track sales. And MMM is its simplest derivative to get a broad insight into campaign effectiveness.
What Are Media Mixed Modeling Ratios
Here are the following three components of the MMM ratio
- Marketing channels that you are using
- The price you invest in each channel
- Insights and outcomes you achieved from the last campaign
Media Mixed Modeling VS. Data-Driven Attribution
Comparing Media Mixed Modeling and Data-Driven Attribution is more likely an apple and orange discussion since both models track the impact of marketing inputs on a business goal.
But the most highlighted difference is MMM is not used for inspecting user-level insight like clicks and impressions. Therefore, Data-Driven Attribution is widespread as it tracks customer engagement. Let’s know the difference more clearly.
Data-Driven Attribution is a set of Attribution models that refers to a top-down approach for evaluating marketing potency. It tracks the engagement throughout the user journey. Also, it provides the marketer’s insight into which strategy is more effective as customers move down to the sales funnel. Moreover, it also measures the performance of certain outcomes at the end of a campaign after a brief time.
This model is more about evaluating market efforts in terms of consumer action.
Media Mixed Modeling
While on the other hand, MMM offers comprehensive insight to understand variables like equity, seasons, trends, etc. As mentioned above, it evaluates the marketing tactics in terms of ROI over a long time.
However, both models have tremendous uses in modern digital marketing, but they also have some limitations.
How To Know Media Mixed Modeling Is Best For Your Campaign
Media Mixed Modeling doesn’t work the same for all companies as it is more effective for online markets. But how could you know that MMM best fits your brand?
Some factors like understanding the target audience and then collecting data accordingly. There are unlimited communication channels in the market to reach a targeted audience. But randomly choosing these channels is not a wise decision. It not only causes a loss of your money but also impacts ROI. Therefore, opting for the best MMM is necessary to get the highest outcomes.
Understand Your Targeted Audience
Well! Firstly, developing a demographic sheet would help if you started by knowing your audience. So, you can know their income, age, gender, marital status, and educational level.However, there are many other ways to inspect them more deeply like.
Track Your Competitors
By tracking your competitors, you will get more about your potential customer’s finding interests and the platforms they used to visit more often. So, keep your eye on competitors’ activities and campaigns.
Visit Social Media Sites Of Interest
Your customers must talk about the services and products related to yours on many reviews and social media platforms. Visit these sites to know what they are talking about and their relevant product reviews.
Use Authentic Data
Now you have collected data to know your targeted customer. Then use this data to get insight into which MMM you need to use that will work best with your campaign.
Limitations Of MMM
MMM is more effective as it accounts for the drivers and variables that may impact the company’s success. However, marketers should track some challenges and limitations across their ecosystem. That is following
- It doesn’t track the relationship between various communication channels
- Offers no insight into the company’s message
- Doesn’t consider the user experience
- Comes with only a few reports
Media Mixed Modeling is a bottom-up approach to offering extensive insight into how the market’s strategy impacts the company’s goal and ROI.
So, for using an effective MMM to evaluate the market performance, you need to balance short and long-term growth, organic research of the targeted audience, assess external variables and track the customer journey.