3 Minute Primer: Why Marketing Mix Modeling Matters for B2B Brands

The four Ps of the marketing mix modeling as we know it – Product, Price, Place, and Promotion are the driving forces behind every marketing strategy. Today it has been extended to include people, processes, and physical environment as well. Identifying the right marketing mix is quite a challenge and many B2B marketers face several challenges when it comes to justifying their marketing investments. Though several factors contribute to this challenge it mainly arises due to long sales cycles, ineffective media spend, and marketing strategy.

However, things have started to change, with marketing and sales teams working in tandem to achieve their organization’s targets. Today, B2B marketing teams play a significant role in increasing ROI, driving down the cost of high-quality leads by optimizing their media spend.

Marketing Mix Modeling: Four steps to Maximize Marketing Success

Marketing mix modeling helps businesses to gauge past performance so that they can use it to improve their future MROI. By doing so businesses can gain a better understanding of their marketing effectiveness and take corrective actions to realign their marketing budget across tactics, products, segments, time, and markets for a better future return. Every marketing mix modeling project must incorporate all the marketing tactics, assuming there is high-quality data with enough time, product, demographic, and/or market variability.

Each marketing mix modeling project has four distinct phases, lets take a look at each phase in depth:

Step 1: Data Collection and Integration

The initial phase of any marketing mix modeling project revolves around collecting and aggregating data from diverse sources. Marketers must ensure they collect relevant data as this would be used to develop statistical models. To do so, it’s essential to first determine the categories to be analyzed, the timeframe, and the granularity at which data would be scrutinized.

Talk to our analytics experts for more insights on marketing mix modeling and its use cases.

Step 2: Data Modeling

This phase focuses on leveraging advanced analytical methodologies to address common queries and skilfully tackle challenges. Partnering with the in-house team or third-party analytics service providers will help brand managers to leverage marketing mix modeling to addresses their challenges. Also, they need to conduct a deep dive analysis of business needs to determine their statistical needs and specifications.

Step 3: Model-Based Measures

This is the most crucial step in marketing mix modeling as it helps assess how each marketing tactic affects sales. Also, the data that comes out of your model must align with the requirements and answer the questions that are crucial to decision making. A fundamental output of every marketing mix modeling project revolves around the decomposition of sales, often represented using graphs to analyze sales volume by each modeled tactic. The output can beused to bifurcatecore and incremental marketing tactics, including tactics that are not controlled by marketing teams.

Step 4: Simulation and Optimization of Business Models

The final phase of any marketing mix modeling assessment focuses on turning the insights into inputs for effective planning of marketing activities. After the completion of data modeling, brand managers can perform data simulations to gain valuable information that may be useful when planning their future marketing activities. Through such simulations, they can also gain valuable insights on how each marketing tactic might impact sales. This also hints at the fact that each mathematical model can provide insights that can help improve the way you approach marketing.

Though there is a growing need for businesses to revamp their marketing strategies using advanced marketing mix modeling solutions, its crucial to note that before one makes any change to the marketing plan, its a good idea to gauge the quality of the model. However, this requires brand managers to have a basic understanding of how to gauge the quality of a marketing mix model. Since most of them might not be good at data modeling, it might be challenging to assess the quality of the model. Our comprehensive suite of marketing mix modeling solutions enable businesses to drive MROI by helping them tackle all their marketing challenges.

Would you like to learn more about marketing mix modeling? Request a free proposal today.