Digital marketing in companies is no longer driven by the same levers as it was two years ago. Attribution models are fragmenting, European regulations are reshaping advertising targeting, and the rise of nano-creators is redistributing influence budgets. Three transformations that call for structurally different digital marketing strategies.
Post-DSA advertising targeting: what compliance changes for digital campaigns
The Digital Services Act imposes transparency obligations on platforms with more than 45 million active users in the EU regarding recommendation algorithms and advertising targeting. For advertisers, the direct consequence is the restriction of targeting based on sensitive data (political opinions, sexual orientation, health data) and the prohibition of advertising targeting minors.
We observe that many marketing teams have not yet adapted their workflows. Custom audiences built on fine behavioral segments lose granularity as the platform limits access to third-party signals. The technical workaround involves strengthening first-party data collected with explicit consent: enriched forms, loyalty programs, post-purchase interactions.
In this area, marketing at CGI Network illustrates how a structured approach to proprietary data supports compliant campaigns without sacrificing performance. The issue is not only regulatory: companies that build their own data foundation gain autonomy in the face of algorithmic changes on platforms.
The DSA also requires the public disclosure of ad libraries. Your competitors can now analyze your creatives, your formats, and your frequencies. Creative strategy becomes a visible competitive advantage, not just an internal conversion lever.
Nano-influencers and data-driven influence strategy
The barometer conducted at the end of 2025 by Reech with ARPP, the Union of Brands, and Snapchat confirms a structural shift. 83% of brands had conducted at least one influence campaign in the last two years. More significantly: 44% of brands now favor nano-influencers with fewer than 5,000 followers, and 69% of companies planned to increase their influence budget in 2026.
This shift is not just a cosmetic trend. Nano-creators generate higher engagement rates than mass accounts, and their cost per collaboration remains compatible with SME budgets. The real challenge is operational: managing twenty simultaneous partnerships with niche creators requires tooling that most teams do not have.
Industrializing without dehumanizing
We recommend structuring the process in three layers:
- A sourcing tool that filters creators by theme, actual engagement rate (not just the number of followers), and geographical area relevant to the company.
- A standardized but modular brief that allows the creator editorial freedom over the format while imposing legal mentions and key messages.
- A tracking table that aggregates the metrics of each collaboration (clicks, conversions, cost per acquisition) to arbitrate partnership renewals.
52% of brands want to intensify their partnerships with micro-creators and 50% with UGC creators. The challenge for companies is to transform UGC into a reusable asset in paid campaigns, product sheets, and email sequences.
Multi-touch attribution and optimization of cross-channel journeys
Last-click attribution models are still predominant in SMEs. They systematically undervalue discovery channels (social networks, organic content, influence) in favor of final conversion channels (SEA, retargeting). The result: poorly allocated budgets that reinforce the most expensive levers.
Shifting to a data-based multi-touch attribution requires two technical prerequisites. The first is server-side tracking that withstands the gradual disappearance of third-party cookies. The second is a modeling that weighs each touchpoint according to its actual contribution to the journey, not according to its chronological position.
Connecting CRM to campaigns in real-time
Cross-channel optimization is not limited to measurement. It involves adapting messages based on the prospect’s position in the buying cycle. A visitor who has viewed three product pages and opened two emails does not receive the same ad as a first-time visitor from a Google search.
Marketing automation platforms allow for this granularity, but most companies only exploit a fraction of their functionalities. The barrier is rarely budgetary: it is related to the quality of CRM data. Incomplete contact records or unmerged duplicates render any advanced segmentation ineffective.
Generative content and editorial oversight in companies
The adoption of generative AI for marketing content production is massive. The question is no longer whether teams use it, but how they oversee what the AI produces. Content generated without professional proofreading degrades brand credibility faster than it fills an editorial calendar.
The main risk is not linguistic quality. It is factual hallucination: an invented figure, a poorly cited regulation, a misnamed competitor. In B2B, a single technical error in a white paper is enough to disqualify the issuer in the eyes of informed decision-makers.
We recommend a three-step workflow: AI-assisted generation, proofreading by a subject matter expert, SEO validation by the acquisition team. This process adds time, but it protects two assets that AI alone cannot guarantee: reliability and editorial differentiation.
- Define structured prompts that include the regulatory constraints of the sector and brand guidelines.
- Maintain a base of verified facts (internal figures, sourced studies) that the human writer injects after generation.
- Measure the post-AI modification rate to gradually adjust the quality of automated briefs.
The French digital advertising market continues to accelerate, and companies that master both regulatory compliance, activation of niche creators, and reliability of their content have an advantage that their competitors will take time to replicate. Technical sophistication matters, but it is operational rigor that makes the difference over time.
