Rethinking Data: The Parallels between Retail Media and Choice-Driven Advertising

The good performance of retail media campaigns is currently the focus of the online marketing industry. The positive results are not due to their mere data-driven nature, but rather to the quality of the data used. Retail media providers benefit from meaningful data directly from consumers and in close proximity to key touchpoints in the middle and lower funnel.

The effectiveness of campaigns depends heavily on the quality of the data used. Outdated, inaccurate and unusable data can significantly hinder marketing efforts and lead to misguided strategies, wasted resources and a lower return on investment. It is therefore time that we build a new, more dynamic understanding of how and where to get the best information from data.

Marketing has always been data-driven, even if we have only added this term to our industry vocabulary in recent years. That is, marketing decisions have always been made based on insights into the needs and interests of the respective target groups and the chosen media.

However, the real change in recent years would be better described as “big-data-driven” marketing. Technological advances in this period have enabled the industry to create and purchase immense collections of data about its target groups. And no longer just on a collective level, but through targeted behavioral tracking on the internet, on an individual level as well. The supposed promise: Now each person could be addressed individually with the right message on the internet.

True to the motto “bigger is better", the industry strived for more and more data, regardless of its quality. Databases filled up more and more and took on dimensions that were almost impossible for campaign planners to manage. New digital helpers in the form of artificial intelligence were supposed to provide a remedy. However, the actual reality is far more sobering. And there is a simple reason for this.

The problems with our current understanding of data

The masses of data collected are supposed to provide insights into people's needs and interests. But does it actually do that? In reality, our needs and interests not only change from day to day, but often several times a day. Many of these changes cannot be reflected by user tracking and collected data in a database, as they often only take place in people's heads. The large amount of data collected is not able to capture the actual and constantly changing consumer preferences at the correct time.

Furthermore, the data collected often does not correspond to the truth. Especially in a professional context, many employees research various topics, for example to gather background information about their customers or business partners. As a result, users are assigned fields of interest that are irrelevant to them as consumers. The same phenomenon also occurs with students and pupils who look online for information on their fields of study and research.

In addition, the internet landscape itself is currently undergoing a major transformation. More and more users are protecting their privacy online by using privacy-enhanced browsers, browser extensions and settings. At the same time, the refusal of consent, which is essential for permission to track users on the internet in order to show them personalized advertising, is on the rise. Last but not least, marketers are losing access to the previous tracking technology due to the long-delayed “death” of third-party cookies. As a result, the majority of people are already invisible to programmatic advertising.

From computer-driven data to human-driven data

Where do we go from here? What can the future of data-driven marketing look like if the quality of the data has so far led to rather mediocre targeting quality? The answer is simple, but it challenges us as an industry to rethink our current understanding of data as static cornerstones in databases and lists. The most valuable data is provided by people themselves, especially when they provide it voluntarily.

People are the data sources we need to draw on - and can, thanks to the advances of the internet. The digital space gives us the opportunity to interact directly with them and make them part of the advertising playout process. Instead of making predictions and probabilities about people based on outdated or low-quality data, people themselves provide the information about which campaign is most relevant to them in each session. Similar to how real buying behavior works as a data point in retail media. Because this information comes directly from consumers, it is more up-to-date and personalized than information in a traditional database could ever be. Advertising is aimed at people. The best data on which to base advertising is therefore dynamic and human-driven rather than static and computer-driven.

To maximize the effectiveness of marketing efforts in the upper funnel, we need to prioritize data quality. In this way, we can better manage the complexity of target groups caused by the individuality of people and implement targeted, effective and appealing campaigns that achieve the desired goals.