IA pour les professionnels du marketing

Aperçu

In an era where "AI-powered" is the new standard, marketers must move beyond basic chatbots to strategic implementation. This course provides a comprehensive roadmap for integrating Generative AI into the modern marketing lifecycle, focusing on both creative output and operational efficiency.

We begin by building a technical foundation, ensuring you understand the strengths and limitations of AI while navigating the critical boundaries of privacy, compliance, and brand safety. You won't just learn to "prompt"; you'll learn to translate complex marketing briefs into structured AI task descriptions that respect audience insights and brand guidelines.

Throughout the modules, you will gain hands-on experience in:

Creative Execution:

Generating and refining high-converting copy for emails, social media, and ads. Strategic Workflows:

Designing end-to-end campaign plans that bridge the gap between a brief and a multi-channel launch.

Data Intelligence:

Leveraging AI to analyze performance data, build detailed personas, and identify high-value audience segments. Optimization:

Repurposing existing assets and using AI-generated variations to scale your A/B testing efforts.

The course concludes with a focus on quality control and professional growth. You will learn to rigorously evaluate AI outputs against brand voice and performance goals.

Finally, you will move from theory to practice by developing a series of assignments that provide hands-on practice at the skills and thought processes needed to make AI a permanent, productive part of your professional toolkit.

Programme

• Définir les concepts d'IA générative, ses forces et ses limites en marketing.
• Identifier les applications éthiques, privées et sûres pour la marque de l'IA.
• Convertir des briefs marketing en descriptions de tâches structurées pour l'IA.
• Stimuler et affiner le texte marketing multicanal généré par l'IA.
• Concevoir des flux de travail automatisés par l'IA pour des campagnes multicanales.
• Analyser les données pour générer des segments d'audience pilotés par l'IA.
• Réutiliser les actifs existants en utilisant l'optimisation assistée par l'IA.
• Générer des variantes d'IA pour soutenir les décisions de test A/B.
• Auditer les productions de l'IA pour conformité à la marque et qualité.
• Créer un plan personnel pour l'intégration quotidienne de l'IA.

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Matières

Business