Too often, companies are swimming in sales and marketing data but unsure how to use it to create better active prospects and achieve business goals. Marketing mix modeling (MMM) can help turn that data into actionable insights and results.
Marketing mix modeling (MMM) is a data analysis technique that allows marketers to understand the impact each marketing effort has on a bottom-line goal. A bottom-line can include conversion actions, lead submissions, or revenue generation. Not only can MMM show you the results of current efforts, but it can also forecast the impact of those marketing efforts. This predictive model can aid in effectively choosing the best marketing channels for your business and the resources needed for those channels.
Here are a few tips and tricks to help you start building and using the marketing mix model.
When building any type of data analysis model it’s important to have clean and accurate historical data. Once you know your data has a solid foundation, you can start constructing your MMM. Typically these models contain three key elements: external factors, ad stock, and the bottom-line goal. Let’s take a look at each one of these critical model components.
The first step to gathering the information for your marketing mix model is to review any external factors in your data. These factors typically include marketing spend by channel or campaign. That marketing data is then usually further broken down into time increments, generally by week and year or month and year. Depending on the type of business it can be important to include any data from marketing promotions or sales to ensure any anomalies in the data are accounted for.
Ad stock rate
The next step is to calculate the ad stock rate. The idea behind it is that advertising plays a role beyond the initial touchpoint of an ad and that you still see benefits from an ad after it’s viewed. The most common use of ad stock in the digital age is that each week has a 50% rate. This typically means that 50% of a week’s spend will carry over to the next week when building a model. The goal of using ad stock is that it gives proper credit to each channel or campaign even if you decrease spend in certain weeks. This can be especially helpful if your business has a long research phase before a conversion.
Bottom line goal
The last part of an MMM is establishing a bottom-line goal or conversion action. Similar to external factors, this goal will be broken down by the same time period as the other factors. However, unlike the external factors, you don’t want to break the goal down by channel.
Building the marketing mix model
Now that all the data is gathered, there are numerous different strategies you can use to build your marketing mix model. Your approach can be as simple as constructing a linear model. Or you can use more complex machine learning models to calculate seasonality, trends, and determine points of diminishing returns.
There’s no right answer when choosing your strategy for building your MMM. Every business and its data are different. The most important part of this step is to find the most accurate model for your business and bottom-line goal. When trying to find the most accurate model you will most likely go through several iterations. Each company must decide which tests and metrics they want to use.
However, if DIY is not your style, hiring a performance-based digital marketing agency can help you build your model. These experts can help determine effective metrics, create an accurate model for your businesses, and develop insights from your marketing data.
Using the marketing mix model
The data team at our digital marketing agency has found the two most effective ways to use a client’s MMM to help with their digital marketing efforts. They are:
The first way a model can aid your marketing efforts is through budget allocation. It’s not uncommon for clients to come to us with an ad budget and ask how best to allocate the dollars. Our digital marketing agency is able to use an MMM to identify seasonality and trends to appropriately allocate the budget in months with high demand. The model can also help allocate budget by channel to further optimize the number of conversions.
MMM can also boost your digital marketing through predictive forecasting. It’s always nice to have general marketing predictions, but a marketing mix model adds an extra layer of accuracy. If a company can accurately predict the highs and lows of a year they can allocate their internal budgets more effectively. The team can also better know when to increase the supply of a product or when to add sales reps in specific areas to keep up with the demand.
In the end, building and implementing a marketing mix model can help elevate the success of your digital campaigns. It can also help your business make better use of your marketing data. From better marketing campaign optimizations to insights to move you ahead of your competitions, having an MMM is a key component for any data-driven company or B2B business.
Want to get started with a marketing mix model of your own? Reach out to the data experts at our digital marketing agency to get started.