Marketing Mix Modelling: A Complete Guide

Marketing Mix Modelling (MMM) is an approach to understand how different marketing activities like advertising and promotions affect sales. It uses math and statistics methods like regression analysis to study past data on sales and marketing which helps businesses analyse what is working and what is not.

Implementing marketing mix modelling

Step 1: Set Clear Goals

• To effectively use MMM make better use of the marketing budget
• These techniques help to predict future sales and understand how customers behave
• Measure the return on investment (ROI) from marketing

Step 2: Collect Data

• MMM is an approach which depends on collection of all the important information from both inside the company (like sales and ads) and outside sources (like market trends).
• The data should cover the time and place you want to study through MMM techniques.

Step 3: Prepare the Data

• Next step involves cleaning the data by fixing any errors, fill in missing values, and making sure that everything is in the right format.
• Sometimes the numbers are normalized so they can be compared more easily.

Step 4: Choose the Right Model

• Now in this step we choose the right method to analyze the data.
• Some commonly used models are: Regression analysis, Time series analysis and various machine learning techniques

Step 5: Select Variables

• This is where you decide which marketing activities and other important factors should be included in your model.
• You choose the ones that matter most for your business results.

Step 6: Building the Model

• Now the actual model is created using data and statistics and the model tries to understand how different marketing actions affect sales or other business goals.
• This technique involves teaching the computer to spot patterns.

Step 7: Checking the Model

• Now we will test how well the model is performing.
• Does it predict real results well? If yes then great and if not some tweaks may be needed.

Step 8: Finding Useful Insights

• Once the model is ready you analyze it to find what’s working and what’s not.
• For example you might discover that social media ads are giving a better return than print ads which could help improve your marketing strategy.

Step 9: Making Changes

• Based on what the model shows, you make desired changes to your marketing plans.
• This could mean spending more on what’s working and less on what’s not or trying new tactics to improve results.

Step 10: Watching and Improving

• After you make the desired changes you keep an eye on the results like are things getting better? If not then you adjust again.
• This step is ongoing because markets and customer behavior can change over time.

Impact of variables on MMM

1. Base variables

• The baseline is any impact achieved independent of marketing mix variables. Base variables are influenced by various factors like brand value, seasonality and other non-marketing factors like GDP, growth rate etc.
• They include: Price, Seasonality, distribution and macro economic variables.

2. Incremental variables

• ATL (Above the Line) marketing: This type of marketing reaches a large, general audience. The goal is to build the brand and make more people aware of it and it’s not focused on specific customers. For example: Radios ads, TV ads etc.
• BTL (Below the Line) marketing: This is more targeted and direct marketing as it focuses on specific groups of customers and aims to get them to buy and often called direct marketing. For example: sales promotions, discounts, social media marketing etc
•  TTL (Through the Line) marketing: This type of marketing combines both ATL and BTL methods.It uses broad brand building and targeted sales techniques together for best results. For example: digital ads and videos.

3. Other variables

3.1 Competition

• Direct competitors: These are companies that sell the same kind of product as you. For example: Apple iPhone vs. Samsung Galaxy both sell smartphones.
• Indirect competitors: These companies sell different products but meet the same customer need in another way. For example: Amazon kindle and paperback books both satisfy the need for reading.

3.2 Halo and Cannibalization Impact: The halo effect happens when customers like a product because they had good experiences with other products from the same brand. It shows how strong a brand is and how loyal customers are. For example: People buy Apple iPads because they liked Apple iPhones before.

Challenges in marketing mix modelling

1. Getting good data: It can be hard to collect clean and accurate data. Sometimes the data is missing pieces, not recorded properly or doesn’t match up. Also, pulling in data from different places can be tricky and time consuming.
2. Detail and timing of data: if the data is too general then you might miss important patterns and if the data comes in late you can’t use it to make quick decisions. Both issues make the model less useful.
3. Complex models are hard to understand: the models that used in MMM can be very technical and complex. They often require experts to build and explain them which makes it hard for people without a data background to understand or use the results easily.
4. Privacy and legal rules: using customer data must be done carefully as there are privacy laws that protect people’s information. You need to keep data secure, remove personal details when needed and follow all legal rules to avoid problems.

Applications

1. Retail: Stores use MMM to improve their sales and promotions which helps them to decide the best prices which products to focus on and what promotions attract more shoppers. This way they can bring more people into the store and boost overall sales.
2. Financial Services: banks and insurance companies use MMM to see which marketing efforts bring in new customers, keep current ones and increase customer value over time. They look at things like ads, email, and online campaigns to see what works best and then use that info to spend their marketing budget wisely.
3. Telecommunications: phone and internet companies use MMM to figure out what helps them get new customers, keep current ones, and grow revenue by analyzing how marketing spend connects with things so they can choose the best ways to increase sales.
4. Automotive: car companies and dealerships use MMM to check how their marketing affects their sales.