Data Science at the service of advertising performance

Optimizing advertising targeting thanks to Data ScienceWhile the disappearance of third-party cookies does not necessarily mean the extinction of data and performance, these upheavals in the digital advertising ecosystem mean that a change in targeting strategy is necessary. It's about understanding, understanding, and using data wisely so that are powerful drivers of performance and innovation. At the crossroads of computer science, customer service and mathematical modeling, data science is a discipline that aims to build statistical and machine learning models. It thus makes it possible to explore and analyze raw data in order to transform them into relevant information responding to a business problem, such as advertising targeting. Data Science therefore provides a concrete solution that perfectly meets the current challenges of optimizing advertising targeting.A model based on artificial intelligence and machine learningFor several years now, advertising has been transformed thanks to artificial intelligence. This provides a subtlety of analysis that makes it possible to readjust targeting and to offer a more detailed understanding of the contexts of distribution. Thanks to the enormous progress of cloud computing offers, it is possible to train machine learning algorithms on ever larger volumes of data to make them extremely efficient. These models can then be used to automatically classify millions of rows of data in record time and make decisions in real time. A technology that, combined with NLP (Natural Language Processing) algorithms, greatly benefits the digital advertising market. These self-learning systems make it possible to optimize advertising performance and investments while guaranteeing the advertiser a display context in perfect harmony with his image and his universe. AI is propelling ad targeting into a new era and this trend is only going to increase as the cookieless world emerges in the future.The era of semantic targetingToday, AI makes it possible to enrich so-called “contextual” or even “semantic” data by combining it with the analysis of the meaning and brand suitability of the editorial content analyzed. This approach makes it possible to change perspective and to move from targeting based on personal data to targeting based on semantic data. Concretely, the user is no longer targeted via their personal data or browsing history, but according to their immediate reading context. This type of targeting offers better performance because the message is personalized and is displayed when the user's attention is maximized on a specific subject. In addition, it makes it possible to reach the user without device or browser restrictions and only requires attention data. Semantic targeting also has the advantage of making advertising meaningful again. By linking the advertising offer to the content of the website, the product or service offered by the advertiser makes perfect sense, and the editorial content gains value.Made possible by Data Science, cookieless and consenless targeting offers new perspectives of performance and makes it possible to maintain a data-driven approach while avoiding the use of third-party cookies. Thus, “zero user data” will no longer be an alternative, but a recognized digital lever or the question of “who” will be addressed through a global and contextual vision.