Data marketing has evolved considerably over the last few decades and has become a backbone for business strategies in an increasingly digitalized landscape. His trajectory has gone from traditional approaches to increasingly advanced and personalized methods. Among the innovations that have gained prominence in the sector, incrementality emerges, bringing a more precise and effective perspective for companies to shape their strategies.

The concept of incrementality in data marketing can be translated into strategic actions that allow us to measure and structure the true impact of a campaign or action. Unlike correlation and attribution, incrementality seeks to understand how a specific change affects desired results in different scenarios. Its application is vast in the area of ​​marketing: it ranges from advertising campaigns to customer retention strategies, as its ability to isolate and measure the real impact of an action is fundamental for today’s data-based decision making.

For example, imagine a company is running an advertising campaign on social media. Through an A/B test, in which one group of users is exposed to the campaign (A), while another similar group is not exposed (B, control group), it is possible to compare the purchasing or conversion behavior between the two. This is where incrementality comes in, which will be calculated to determine the real impact of the campaign.

Another practical situation: a financial institution can use behavioral data for purchasing past services to offer personalized discount offers to certain customer segments. Incrementality would be measured by comparing the acquisitions of these segments with those of a control group that did not receive the personalized offers. Or, when implementing an email marketing strategy, the institution can segment its customers differently, sending specific campaigns to each segment. Incrementality would be assessed by comparing the performance of segmented campaigns with that of generic campaigns, for example.

Adopting incrementality offers substantial benefits for those looking to maximize their return on investment (ROI). By understanding the true impact of each action, organizations can allocate resources more efficiently, adapt strategies in real time, and build more meaningful customer relationships.

Furthermore, the advancement of technologies, such as artificial intelligence and machine learning, has provided new tools and approaches for implementing incrementality. The ability to analyze large data sets in real time and automatically adapt strategies represents a significant evolution in the field of data marketing.

Therefore, incrementality in data marketing is not just a passing trend: it is a fundamental shift in the way companies approach their marketing strategies. As the business environment continues to evolve, the ability to measure and understand the true impact of actions becomes a crucial competitive advantage. Those who embrace incrementality are positioned to not just survive, but to thrive in the information age, where precision and effectiveness are the keys to business success. And those who arrive first win.

*Marcel Ghiraldini is co-founder and Chief Growth Officer of MATH Group, a holding company for B2B companies that apply exact sciences to improve relationships between brands and people. He is also co-author of the book “Marketing Code: The practical guide to generating performance in digital channels” and postgraduate professor in the area of ​​marketing at ESPM and FIA. He served for more than 15 years as commercial director and maintained contact with the world’s main technology companies. The executive was also a mentor for startups in the Google Launchpad Accelerator, ACE Startups and Inovativa programs. Ghiraldini has a Bachelor’s degree in Information Systems from the Municipal University of São Caetano do Sul and an MBA in Strategy from Fundação Getúlio Vargas.


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