Marketing mix modeling is a statistical analysis method that determines the effectiveness of marketing efforts and helps to optimize the allocation of resources across channels, tactics and/or campaigns. It quantifies the return on investment (ROI) and gives recommendations on how to increase it.
Self-service marketing mix modeling goes one step further. With the help of intuitive Software-as-a-Service (SaaS) solutions, marketers can independently carry out analyses, evaluate and compare the effectiveness of individual marketing activities. This allows them to develop their own understanding of what drives marketing performance.
The need to control the flood of data: Marketers are inundated with data. There are a number of analysis tools available to them that can help them evaluate their data and improve their marketing performance. However, this overwhelming availability of data and tools can be difficult for marketers to master and use effectively. Self-service marketing mix modeling enables marketers to focus on the relevant data, train precise statistical models, find out the important patterns and derive results such as impact contributions, return on investment, ad-stock effects and saturation curves.
The demand for more accountability and transparency: In today’s data-driven marketing world, stakeholders expect marketers to be able to measure and report on the impact of their actions with accuracy and transparency. Self-service marketing mix modeling enables marketers to validate their own data and more effectively measure the impact of their marketing efforts, which helps build trust and credibility with stakeholders.
The need for quick insights and flexibility: Traditional full-service marketing mix modeling can be time-consuming, expensive, and may not provide the flexibility and agility marketers need to operate in a rapidly changing environment. Self-service marketing mix modeling empowers them to perform on-demand marketing mix modeling with efficiency, as everything needed can be bundled in the marketing department with no external dependencies.
Once marketers have decided to use marketing mix modelling, they are faced with the next decision: Who should build, implement and interpret the model? There are basically three options:
Marketers who have all the crucial skills in-house, for example for data set creation, model building and analysis, can build and run an MMM themselves. The advantage is obvious: A model can be set up entirely according to the needs of the company. However, the experts required for this must also be kept in the company so that the knowledge does not flow away again. This is not always an easy task. Building a model from scratch is also time-consuming.
A full-service MMM, whether purchased from the agency or from another external service provider, offers the advantage that no expertise is required in the company. Flexibility is the lowest here, since there is a complete dependency on the service provider and there must be great trust in the correctness of the results. It is often not possible to understand in detail how the results of the model come about.
A self-service MMM is a middle ground. Here a system is bought, but it is operated by oneself. Self-service marketing mix modeling platforms are designed to be easy to use and intuitive for non-technical users, with drag-and-drop interfaces, understandable data visualization, and built-in guidance and support. They enable marketers to do their own marketing mix modeling without having to rely on outsiders. In this way, an understanding of the causes of marketing performance can be built up in the company.
All three options have advantages and disadvantages. Which way makes the most sense depends primarily on the resources available in the company.
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