When a marketing team has been relaunching the same email campaign for three years with a declining open rate, the cause often lies in a marketing strategy that is poorly adapted to the constraints that have shaken the landscape in 2024: the scheduled end of third-party cookies, the European regulatory framework on AI, and the rise of advertising channels where measurement remains unclear.
Adapting corporate marketing to these realities requires fewer buzzwords and more method.
Proprietary data and the end of third-party cookies: the foundation to build before anything else
The gradual disappearance of third-party cookies in browsers has rendered most targeting mechanisms that fueled traditional display campaigns obsolete. This is not a minor technical adjustment: it is the acquisition model for many companies that is losing its fuel.
The operational response lies in proprietary data collected through CRM, customer accounts, and newsletters. A well-structured loyalty program or a sign-up form for a segmented newsletter generates directly usable information without relying on a third party. Market analyses for 2024 recommend complementing this data with privacy-enhancing technologies, rather than replicating old individual targeting models.
In practical terms, we start by auditing what we are already collecting and what we are underutilizing. Many companies have purchase data, browsing data on their site, or responses to satisfaction surveys, without ever cross-referencing them. This is where the room for improvement lies, well before investing in a new tool. To delve deeper into these levers, marketing on Business Club details several approaches suitable for SMEs as well as larger structures.
Marketing AI and the European AI Act: the concrete obligations to integrate
The majority of articles on marketing strategies in 2024 present artificial intelligence as a productivity accelerator, period. They talk about content generation, email personalization, chatbots. But the framework in which these tools operate has changed.
The European AI Act now imposes obligations based on the risk level of the AI system used. A customer scoring tool that influences access to a service is not deployed like an Instagram caption generator. The CNIL has published its first recommendations on the development of artificial intelligence systems, and the interplay between the AI Act and GDPR conditions the legal deployment of any marketing AI in Europe.
On the ground, this means two things. First, document every use of AI in the marketing chain: what tool, what input data, what impact on the final decision. Second, ensure that the legal basis for processing personal data remains valid when adding an algorithmic layer. Ignoring this point exposes one to penalties, but also to a loss of trust from customers who are becoming more attentive to the use of their data.
Three checks before deploying a marketing AI tool
- Identify the risk category of the tool under the AI Act (minimal, limited, high, or unacceptable risk) and adapt the documentation accordingly
- Ensure that the personal data injected into the tool complies with the legal basis defined in the company’s GDPR register
- Plan for a human oversight mechanism on automated decisions that directly affect the customer (scoring, price recommendation, access denial)
Retail media: a powerful advertising lever but difficult to compare
Retail media networks have established themselves as a standalone channel for brands selling online or in large retail. Their main advantage: they have proprietary purchase data and offer a measurement linking advertising exposure to actual sales.
The problem is that each network uses its own definitions. What Amazon considers a sale attributed to advertising does not correspond to what Carrefour Links or Criteo Retail Media measure. Attribution windows (the time between the click and the purchase taken into account) vary, as do reporting methods.
For a company that allocates its marketing budget among several brands, directly comparing performance between retail media networks remains very complicated today. Feedback on this point varies by sector and investment volumes. Our recommendation: demand raw data access from each network and define an internal unique attribution method, even if simplified, to arbitrate budgets.
Content strategy for social networks: produce less, target better
Publishing daily on three platforms without a clear content strategy generates neither engagement nor customers. We observe that companies achieving concrete results concentrate their efforts on one or two social networks where their audience is truly active, rather than spreading their resources thin.
The question to ask is not “what format is trending” but “what content answers a question that our customers have before buying.” A LinkedIn carousel detailing a product use case with real data performs better than a generic video about the company’s values.
Criteria for deciding between content formats
- The format corresponds to a real consumption behavior of your audience (not a global TikTok trend if your customers are on LinkedIn)
- The content can be reused or adapted on another channel (newsletter, blog article, sales support) without starting from scratch
- Production is sustainable with the available internal resources, for at least three months without interruption
- A converting piece of content is worth ten pieces that generate likes: measure leads or incoming requests, not just engagement
Adapting corporate marketing strategy in 2024 relies on two or three well-mastered levers, measured rigorously, and compliant with a regulatory framework that continues to clarify. The best-spent marketing budget is the one for which we can prove the return.
