Attribution Modeling Vs Marketing Mix Modeling - Which One Is Right For You?
Today, the world has turned more analytics-driven, and assigning credits to marketing channels is what every digital marketing firm is doing. So much that around 30% of the whole marketing budget is kept solely for analytics. Everyone wants to know whether their marketing efforts are generating any value or not, and this is where digital attribution models act as a helping hand.
In fact, with the booming digital marketing industry, developing technology, and increasing competition, whether what you are doing is working is not the only answer you need. But, when is it working, where is it working, how well is it working, and with whom is it working are important things to know as well.
attribution modeling
But this can only be done if you choose the right measurement approach, and where most companies get stuck is making a choice between Attribution modeling and Marketing Mix Modeling. To make the right decision marketers need to understand the difference between the two, and fit them in their needs frame.
Let’s start by understanding the difference between the two on the basis of various parameters. The following parameters will help you in making your mind up for which one to opt for your organization:
Media Type: Marketing mix model works primarily offline and is more suitable for traditional media, such as radio, print, and television. Attribution modeling, on the other hand, is primarily online based and focuses on social media and digital marketing tools such as AdSense, AdWords, etc. With world interest changing to digital platforms, Marketing mix model fails here due to its restrictions to media types.
Approach: Marketing mix model is based on econometric models and has a macro-level or top-down approach. Whereas attribution modeling is based on data-science models and has a micro-level or bottom-up approach. Marketing mix model measures the overall value of the marketing tasks by analyzing the historical data. Attribution model, on the other hand, constructs and measure the path to conversion from various channels to individual creative.
Time Period: Marketing mix model is performed just once or twice a year as it is based on aggregated historical data. Attribution model needs more real-time and accounts specific data and hence the results are updated daily. For a better and critical understanding of marketing function’s performance, attribute modeling is much recommended.
Data: Integration of sales and marketing data based on external factors such as marketing cost and the benchmark is done in Marketing mix modeling. Seasonality, recent news events, market movements could act as variables in this case. In Attribution modeling, sales and granular marketing data is considered base to understand how each media asset is performing. It integrates with demand-side platforms and data management platforms using advanced algorithms.
Strengths: The biggest strength of the marketing mix model is that it has the ability to evaluate offline variables and is also a competent tool for “push” marketing strategies. It also acts as a good tool in the quantification of brand ads. Attribution modeling‘s key strength lies in “pull” marketing and is a much more quick tool with which you can update your campaigns in a go. The granular view and daily based analysis allow the marketer to allocate budget in proportion to the revenue being generated by each channel.
Now you know how marketing mix modeling can and attribution modeling can add value to your organization. Both the approaches could be of great advantage for proficient micro and macro optimization. They can improve an organization’s holistic marketing strategy by providing insights into customer behavior and aiding in the allocation of the marketing budget.