 By Carolina Pelegrin Data Scientist at joint systems  In today's data-driven marketing landscape, understanding the effectiveness of marketing activities is crucial for optimizing marketing strategies and maximizing return on investments. Two powerful methodologies that can decision-makers achieve this are Marketing Attribution and Marketing Mix Modelling. These state-of-the-art approaches are versatile and complement each other to a large extent - this is why we decided to delve into them in this blog post. Marketing Attribution methods are used to determine how each marketing interaction (touchpoint) contributes towards reaching a desired output (like a donation). It aims to determine which channels, campaigns or interactions are most effective in driving donations and therefore, what revenue is expected to come from all different channels. This can help us allocate resources more efficiently, prioritizing those channels and campaigns that are expected to return the highest revenues. In 2022, our data science team applied marketing attribution methods to a dataset of website visits and donations. We were able to conclude that different online marketing channels did have different effects on donations and donation revenues, with the best results obtained for branded paid search and organic search. You can find an introduction to the topic and the main results we obtained in our previous post on the topic, just follow this link if you are interested. Marketing Mix Modelling (MMM) on the other hand are methods that assess the impact of various marketing activities on overall business performance. This technique tries to identify the relationship between donations and different marketing elements like media campaigns, external variables like macroeconomic factors, internal variables like new products or new pricing, seasonal trends, etc. In general, MMM involves collecting and analyzing historical data to identify patterns and relationships between marketing activities and business outcomes. This analysis typically employs regression techniques and other statistical methods to isolate the effects of individual marketing components, allowing us to forecast the impact of different strategies and make informed decisions about resource allocation. The main characteristics and differences between MA and MMM methods can be found on the following table:  Marketing Mix Modelling – data requirements and techniques
From our previous blogpost on attribution modelling, we know that marketing attribution traditionally focuses on the analysis of online data during a specific, short period of time. Also, results from marketing attribution are based solely on the touchpoints or channels that a donor has used to “land” on conversion sites. No other information is needed to build the models, although total budget/investment per channel is an interesting feature, since we can reallocate that budget depending on the results obtained. Also, attribution models are not limited to only channels an can be applied across all communication channels On the other hand, Marketing Mix Modelling tends to use a a wider variety of variables. Data requirements include historical donation data, marketing costs across different channels, data on media metrics (if available) including reach, frequency and engagement levels, as well as data on external factors, including economic indicators, seasonality data or any other relevant and available external factors. Other kind of data, like promotions and competitor pricing are typically included in MMM. As for the techniques widely used in MMM to uncover data insights, they will mostly depend on the goal of the specific analysis, although regression analysis, machine learning algorithms and time series analysis are the ones most widely used.
To give you an idea of example deliverables MMM may provide, the web holds a plethora of interesting resources such as this well-summarized article on LinkedIn. Conclusion In summary, understanding the effectiveness of marketing activities is essential for optimizing strategies and maximizing ROI. While both Marketing Attribution and Marketing Mix Modelling methods have their own unique strengths, by leveraging the insights from both methodologies, we can optimize our marketing performance, enable more informed and strategic resource allocation and achieve better overall results. Are you also interested in Marketing Attribution and Marketing Mix Modelling? Let’s stay in touch! 😊
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