Improving your ROI with Market Mix Modeling

Posted on July 13, 2019 by 3 Comments

Improving your ROI with Market Mix Modeling
Blog / Marketing / Improving your ROI with Market Mix Modeling

These days, it’s rare to see websites that don’t promote themselves using multiple channels. You can use social media, traditional online ads, email marketing, and much more. The more channels you implement, the better returns you’re likely to see – but measuring the impact of each of them becomes complicated.

That’s where Market Mix Modeling (MMM) comes in. This type of statistical analysis can help you measure the impact of all your marketing channels. In this article, we’ll break down how MMM works, explore some basic terminology, and discuss how you can implement it for your own business.

Let’s get to it!

What Market Mix Modeling Is

Let’s say you run an ecommerce store, and you put a lot of money into marketing using different channels, such as:

Ideally, you’ll monitor each channel closely to see how well your efforts are doing. The more data you have, the easier it becomes to determine which channels will have a greater impact on your overall Return on Investment (ROI).

If you’ve ever done that type of analysis, then you’re already familiar with MMM. At its core, MMM is a statistical analysis that you apply when you use several marketing channels at the same time. Its goal is to help you optimize how much you spend on each channel, in order to improve your returns.

Online businesses have a massive advantage over traditional brick-and-mortar companies. That’s because you get access to a lot of marketing tools that can help you keep close tabs on performance. Let’s say, for example, that you use Google AdWords to promote your WordPress business. With AdWords, you know exactly how much you’re paying for each click, and you can easily measure your spend for each sale you get.

However, imagine that you spend $10 on PPC ads, and you see a direct return of a $100. On another channel, you also pay $50 for video advertising and get a return of $70. You don’t need to be a data scientist to figure out that you’re better off increasing your PPC budget, but keep in mind that this is a highly simplified example using only two channels.

In practice, MMM not only measures ROI, but also effectiveness, efficiency, and plenty of other key elements. If you’re the kind of person who likes charts and numbers, and you’re interested in optimizing your ROI, then MMM is a great fit.

5 Market Mix Modeling Terms You Need to Understand

As you might imagine, there are a lot of terms to unpack when you start learning about market analysis. Once you get a grasp on the basics, however, the whole process becomes much less intimidating. With that in mind, let’s discuss some key terminology before moving on to applied MMM.

1. Multi-Linear Regression

Linear regression‘ is a type of analysis that establishes a relationship between dependent and independent variables. For example, you might use overall sales as your dependent variable. Then you might have multiple independent variables, such as social media and video ads, as well as PPC spends. When you start dealing with multiple independent variables, you’re talking about multi-linear regression, which is at the core of MMM.

2. Base and Incremental Sales

‘Base sales’ refers to the natural demand for your products, once you take advertising away. Once people know you and your brand, you could theoretically reduce your ad spend to zero and still get some sales. ‘Incremental sales’, on the other hand, are those you get as a direct result of your marketing activities. With MMM, these are the sales you’re going to focus your analysis on.

3. Distribution

When we talk about ‘distribution’ in MMM, we’re referring to how many of your resources you’re allocating to each marketing channel. MMM’s ultimate goal is maximizing the effectiveness of your ad spend. To achieve that, you’ll need to constantly optimize your distribution.

4. Diminishing Returns and Decay Effect

You’re probably already familiar with the term ‘diminishing returns’. In advertising, it refers to how much you can push ads until they reach the point where their effects start to regress.

To give you an idea of what that means, let’s return to our earlier example of getting $100 in sales for each $10 you spend on PPC ads. Ideally, you could scale that number infinitely just by increasing your spend. However, in practice, there’s only so much you can scale up a campaign before the numbers start to decline. That, in a nutshell, is what makes optimal resource distribution in MMM such a complex task.

On a related note, there’s also the ‘decay effect’ to consider. In most cases, every single marketing campaign you launch will start to see decreasing returns over time. That’s par for the course, because people’s interests shift and wane. You’ll need to adapt with those changes if you want to remain at the top of your game.

5. Deep Dive Analysis

Finally, a ‘deep dive analysis’ involves taking a close look at your marketing campaigns to assess which ones are most effective. In practice, that means analyzing their copy, designs, distribution channels, and pretty much every other component you can imagine. When you get to the budget optimization or distribution segment of MMM, the insights you get from your deep dive analyses will be one of your most valuable assets.

How You Can Implement Market Mix Modeling in Your Business (2 Methods)

By now, you should have a good grasp on what MMM is and its basic terminology. Now let’s move on to a few actionable ways you can implement it for your business.

1. Measure Your Marketing Channel Distribution

Tracking your marketing spending is at the core of MMM. That means the first thing you’ll need to do is put all that data together, using charts, tables, or whatever your favorite tracking methodology is. Personally, we’re big fans of charts and spreadsheets for market analysis.

Whichever approach you take, remember that you’ll need to update this information often as you shift your distribution. The goal here is for you to be able to get a quick overview of the areas you’re focusing on and what their returns are looking like, so you can make adjustments as needed.

2. Use Experiments to Validate Your Distribution Adjustments

It’s easy enough to say: “Let’s shift X number of dollars from email to video marketing, because the latter is giving us better results”. In real life, there are a hundred factors that can impact the effectiveness of your ads, which is why deep dives are so important.

When you shift marketing resources from one channel to another, you need to get into the mindset of thinking about the change as an experiment. Consider A/B testing, for example – you start with a hypothesis, you test it, and if the results are good, you make the change.

The same goes for resource distribution. Ideally, it should be a gradual change, so you can measure its impact and see if it translates to an increase in your ROI. If not, at least you’ll know that as soon as possible.


Measuring the impact each marketing channel has on your sales and conversions can be tricky. However, the great thing about marketing online is that you get a lot of tools to keep track of all your data. That means you should have an easier time determining where it makes more sense to allocate marketing resources.

When it comes to MMM, the first you need to do is collate all the data you have from diverse channels. Once you look at it all together, you can start to consider where to shift your resources, and test your changes gradually. Over time, this will provide you with an informed way to boost your campaigns’ effectiveness.

Do you have any questions about market mix modeling and how to apply it? Ask away in the comments section below!

Article thumbnail image by Visual Generation /


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  1. Before I heard about Market Mix Modeling, what I was using is social media and I don’t know any other one. I just wish to try Market Mix Modeling as well and see how my marketing grows. I thank you for this useful enlightenment.

  2. A very good eye opener

    • Glad it was helpful Sarah 🙂

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