Performance marketing : the AI revolution in action

Digital marketing is constantly evolving. At the heart of this transformation, Artificial Intelligence (AI) and Generative AI (GenAI) are emerging as driving forces. They are transforming strategies and redefining the customer experience, acting as real levers for growth and performance. Their ability to bring greater precision to data analysis and large-scale personalization is becoming crucial. GenAI, in particular, is multiplying our capabilities for content creation and, more broadly, task automation, from targeted campaign management to visual production.

The emergence of GenAI marks a real paradigm shift. While Artificial Intelligence, with its foundations in Machine Learning and Deep Learning, has been around for decades, the arrival of models such as ChatGPT, Mistral, and Gemini has democratized the ability of machines to create text, images, or video by understanding natural language. Tools are now adapting to humans, transforming marketing perspectives.

To grasp the full scope of these transformations, let’s look at how AI structures our marketing actions: it enhances our ability to understand customers, predict their behavior, measure the impact of our campaigns, and orchestrate all of these processes in an omnichannel and automated manner.

A detailed understanding of customer behavior is the cornerstone of any successful marketing strategy.

However, for AI to truly transform raw data into actionable customer knowledge and operate as an insight engine, data quality and governance are fundamental, with a collection strategy aligned with the company’s strategic objectives.

It is on this solid foundation that AI excels at analyzing complex data and identifying precise insights. It processes large volumes of information—browsing behavior, purchase history, interactions across different channels—to extract correlations and trends that would otherwise be imperceptible.

Beyond simple dashboards, AI can help build a predictive understanding of the customer journey, anticipating needs and intentions. This intelligence allows marketers to create more accurate segments, anticipate attrition, or detect cross-sell/up-sell opportunities.

Customer insights obtained through AI become the foundation of a solid predictive capability. This ability allows marketers to deliver the right message to the right person at the optimal time, moving from a mass approach to a personalized relationship.

AI enables intelligent and comprehensive targeting. It detects complex patterns in data, revealing new opportunities and high-potential segments, even outside of traditional targeting.

The result: more relevant messages, stronger engagement, and more conversions. CRM automation tools now natively integrate algorithms that further refine this targeting by predicting engagement or optimizing sales pressure on an individual basis.

When it comes to content, GenAI is a powerful tool for creativity, working closely with humans.

For text, it facilitates brainstorming ideas, exploring semantic fields, and generating first drafts. Its strength lies in its ability to integrate tone of voice and brand identity for relevant content. However, human intervention remains crucial for reworking the content to avoid overly smooth writing and add nuance.

GenAI makes it possible to quickly create images and adapt them to multiple formats. It leverages existing brand visual assets by animating them, extending their lifespan. It leverages existing brand visual assets by animating them, extending their lifespan and reducing the need for costly new productions. Brands such as Bollinger and Transavia, for example, are already using it to create immersive and interactive experiences using generative AI.

Content personalization is not limited to generation. Traditional AI (machine learning) adapts each message to the individual through behavioral and predictive analysis: choosing the right visual, the right offer, or the right block of text.

This includes product recommendations and the creation of entire versions of messages based on each consumer’s preferences. GenAI creates the building blocks, and algorithmic AI intelligently assembles them for each target.

At the heart of the marketing journey, AI-enhanced performance measurement acts as a continuous feedback loop. It allows you to evaluate the impact of actions and refine strategies in real time.

It is not limited to aggregating figures: it analyzes campaign effectiveness in real time, identifies factors of success or failure, and adjusts budgets accordingly. AI can detect anomalies or emerging trends, quickly flagging opportunities or challenges.

From multichannel attribution analysis to the identification of key conversion paths, AI provides accurate and actionable insights. This continuously generated information feeds into and refines the marketing strategy, enabling agile adjustments and increased performance. Thanks to this ability to continuously learn and adapt, it becomes possible to achieve a comprehensive orchestration of the customer experience.

With a better understanding of customers, targeted predictions, and real-time measurement, marketing can now function as a seamless, automated omnichannel orchestration. This is where the true potential of AI lies: connecting these three steps in a virtuous loop, with AI Decisioning at its core.

AI Decisioning goes beyond simple prediction: it makes strategic and operational decisions in real time, based on customer insights, behavioral predictions, and performance feedback. This self-optimizing capability paves the way for agentic AI: systems capable not only of deciding, but also of proactively executing complex tasks, interacting with other agents to drive entire marketing workflows.

AI and GenAI are profoundly transforming marketing by offering increased performance, advanced personalization, and immersive experiences that enhance customer centricity.

However, this revolution also has its limitations and challenges: environmental impact, intellectual property, algorithmic bias, and data privacy. Regulatory developments, such as the European AI Act, will guide responsible use. Despite these challenges, we are the agents of major change. AI Decisioning, already discussed, is just one step toward increasingly autonomous systems. Agentic AI paves the way for potential “agent centricity,” where AI agents could profoundly reinvent e-commerce and many other facets of marketing, as some experts suggest.

The marketing of tomorrow needs to be reinvented, and AI is the catalyst.