An SME launching an advertising campaign across three platforms at once, without aligning its messaging or checking its consent obligations, wastes budget and takes on legal risk. In 2025, effective marketing strategies start with a practical reality: the growing number of channels and AI tools does not replace operational discipline. Aligning actions with real-world constraints (regulations, usable data, internal resources) remains the foundation of sustainable growth.
Advertising consent and the AI Act: two constraints reshaping campaigns
Before discussing personalization or automation, businesses must contend with a tightening regulatory framework. Service-Public’s guidance states that advertising trackers require prior consent, that refusing must be as easy as accepting, and that users can change or withdraw their choice at any time.
In practice, this means that every digital campaign journey must incorporate consent management from the outset. A poorly configured banner or a form that makes refusal difficult can expose a company to penalties. Marketing teams should work with developers to audit user journeys before launch, not afterward.
When it comes to artificial intelligence, the European AI Act’s implementation timeline is already underway. February 2, 2025 marked the start of the application of certain prohibitions. In practical terms, if you use an AI tool to score leads or segment audiences, first check which risk category it falls into. Marketing strategies for success in 2025 now include this compliance step, or you may have to pull a tool in the middle of a campaign.
Marketing personalization: start with real data, not technology promises
Personalization is often described as the key to success. In practice, most companies use only a fraction of their customer data. The problem isn’t the tool—it’s the quality of the database.
Cleaning and structuring your database before investing in a personalization tool is still the most cost-effective first step. A CRM full of duplicates, inactive contacts, and empty fields won’t deliver anything useful, no matter what software you connect to it.
Once the database is clean, personalization takes three practical forms that should be prioritized:
- Behavioral segmentation, grouping customers based on their actual actions (purchases, clicks, abandoned carts) rather than on self-reported criteria that are often outdated
- Dynamic content in emails and on your website, tailored to each segment without manual intervention for every send
- Predictive analytics, identifying purchase or churn signals to trigger actions at the right time, provided there is enough data for the model to be reliable
Predictive capabilities vary depending on database size and interaction frequency. A B2B company with a few hundred active customers won’t get the same results as an e-commerce business processing thousands of transactions a week.
Retail media and performance measurement: a promising but fragmented channel
Retail media is attracting an increasing share of advertising budgets. According to the Attitudes to Retail Media 2025 report, published on July 30, 2025, by IAB Europe, fragmented networks and a lack of standardization are creating challenges for buyers.
For a company considering allocating budget to retail media, comparing performance across platforms remains difficult as long as metrics aren’t standardized. One network may calculate its click-through rate differently from another. Commerce media measurement standards are being developed, but they have not yet been widely adopted.
A pragmatic approach is to test a single retail media network with a limited budget, measure results using your own attribution tools, and then expand. Jumping straight into three networks at once without being able to compare their metrics is like navigating without a compass.
Content and generative AI: produce less, but make it more targeted
Generative AI tools can produce articles, visuals, and scripts at scale. The temptation to publish more is strong. In practice, brands that churn out content without an editorial strategy see engagement decline.
AI works well for low-value tasks: rewriting product descriptions, generating headline variations for A/B tests, and summarizing customer feedback. Its limitations become clear when you need an editorial position, a point of view on an industry topic, or a story that reflects the company’s real-world experience.
A practical division of responsibilities:
- Use AI to produce drafts, find additional keywords, and structure raw data
- Keep editorial approval, brand voice, and high-engagement content (testimonials, customer stories, opinion pieces) in human hands
- Systematically measure engagement rates by content type to adjust how much work is delegated to AI
Content that generates no clicks, shares, or conversions is just taking up space. It’s better to publish two well-targeted articles a week than a daily stream that nobody reads.
2025 marketing budget: prioritize channels instead of piling them on
The most common mistake is still trying to be everywhere. Every new channel (social network, retail media platform, automation tool) takes time, money, and attention. Focusing resources on two or three channels you know well delivers better results than spreading yourself thin across eight.
When deciding where to invest, go back to basics: where are our customers, which channel delivers the lowest acquisition cost, and how much content can we realistically produce? A company with a two-person marketing team doesn’t have the same options as one with a department of twenty.
Omnichannel marketing doesn’t mean being on every channel. It means the channels you choose work together: the same message, synchronized customer data, and the same level of quality. This operational consistency matters more than the number of touchpoints.
