Market Mix Modelling: The Science of Predicting Sales from Marketing

In the days of traditional marketing, the marketers knew how their efforts accounted for sales. But this is not the case anymore. With so many digital channels it is becoming more and more difficult to measure the efficiency and impact of marketing initiatives. Now, the marketing activities are spread across traditional and new age channels. With the increase in the number of channels, there is a resultant increase in the number of possibilities and accordingly an increase in the number of challenges. How to know which campaigns & activities are working and which are not? For this, you can always use the evergreen method of calculating ROI:

If you think that this should be suffice, then there are just three questions you need to ask yourself:

• Is this method fruitful in the digital era?
• How will you find the gain from investment from every single marketing campaign?
• Can you predict the outcome of marketing activities on sales and their ROI in future?

This is where Market Mix Modelling (MMM) comes into the picture. MMM is a technique to answer all these three questions with the power of Big Data analytics.

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What is Market Mix Modelling?

Marketing mix modeling is a data analysis technique in which past company data is analyzed to quantify the impact of various marketing activities on sales. This data includes information from Google Analytics, point-of-sale systems and company’ internal reports. A statistical technique called regression analysis is used identify linear and nonlinear relations between the marketing activities and direct sales. MMM measures the efficiency of all the marketing elements in following terms:

• Contribution to sales-volume
• Volume of sales generated by each unit of effort
• Sales volume generated divided by cost
• Return on Investment (ROI)

These insights are then leveraged to adjust marketing activities to maximize revenues and profit and predict sales while simulating various scenarios. Advanced Market Mix Models may also include multiple products or brands competing against each other to analyze the cross-price relationships and advertising share of voice. The insights can be used to identify their impact on the market as a whole and individual companies in it.

Read More: How to identify the right pricing for your products using Big Data?

5 Steps to Implement Market Mix Models:

Market Mix Modelling divides the sales into two parts - base sale and incremental sale. The base sales is the natural demand for a product which is built due to prior market reputation, pricing, product quality etc. Incremental sales are the sales generated due to marketing activities. The MMM model is created to analyze the impact of four main marketing channels - media and advertising, trade promotions, pricing and distribution activities. These categories can be further silted into more minute segments based on the business needs and activities.

To create a successful model for analyzing marketing activities, various hypothetical models are created and then validated. Here are the exact steps that are followed to create market mix models:

1. Hypothetical models are created with sales as the dependent and marketing efforts as independent variables.
2. Once the variables are created, multiple iterations are carried out to identify the model which explains the best relationship between the variables.
3. Now the tests are validated either by using validation data or by checking the consistency of the business results.
4. The contribution of various marketing channels as a percentage of revenue can be plotted year after year to ascertain the trends relating to one medium.
5. The final model can be used to simulate different marketing scenarios for a ‘What-if’ analysis. The marketing manager can ascertain the impact on sales and ROI by changing budget allocations to different channels. Using this they can arrive at the best possible marketing strategy for their business.

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The Complications Involved in MMM:

• There are usually inconsistencies between the data received from marketing agencies and the internal documents of the company. While analyzing data from both ends it is required to combine the two which becomes a very complicated process.
• Marketing is a very dynamic activity. Results from one channel can vary based on many factors apart from the money invested in it. A single viral post can change the entire picture of social media ROI. In such a dynamic scenario, it is very difficult to predict the future growth based on past trends.

Even after these complications market mix modelling is a very effective technique. If used properly, it can be very fruitful for business. Not only this model gives insights into current operations but it also guides the decision making in future. If you are looking for a company to help you use business analytics at scale then feel free to contact us.