Many SMEs launch campaigns across three channels simultaneously without having defined a precise target. The budget dwindles, leads do not convert, and the sales team loses confidence in marketing. This scenario repeats itself regardless of the sector. Successfully implementing a marketing strategy relies less on multiplying actions and more on the rigor of choices made in advance.
First-party data and the end of third-party cookies: the real starting point of a marketing strategy in 2025
Since the gradual rollout of the removal of third-party cookies on Chrome and iOS restrictions on tracking, it is no longer possible to build a targeting strategy on the same foundations as before. Purchased audience segments from third parties are losing precision, and traditional retargeting campaigns are seeing their performance decline.
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The operational response lies in the structured collection of first-party data: forms on the website, loyalty programs, in-store interactions, or through a CRM. We are talking about data that the customer has voluntarily shared, making it both more reliable and compliant with regulatory frameworks.
The Digital Services Act (DSA), fully applicable since February 2024 for large platforms, imposes greater transparency on recommendation systems and limits the use of sensitive data for advertising targeting. In practice, marketing teams need to reassess their segments and messages because some data used yesterday is no longer legally usable today. To delve deeper into the fundamentals that frame these changes, marketing on Marketingrama details the pillars to master before taking action.
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A well-designed loyalty program (even a simple one, with a segmented newsletter and a points system) generates valuable behavioral data. We know what the customer buys, how often, and what triggers a repeat purchase. This raw material then fuels the personalization of campaigns.
Marketing objectives aligned with the customer cycle: attract, convert, retain
Setting objectives without linking them to the actual customer journey is like steering blindfolded. We still see marketing plans where the main objective is “increase awareness,” without specifying at which stage of the cycle this awareness should translate into measurable action.
A more operational framework involves breaking down objectives according to three phases of the customer cycle:
- Attraction: generate qualified traffic through content, organic search, or targeted campaigns. The key indicator is not the volume of visits, but the percentage of visitors matching the target profile.
- Conversion: turn interest into purchase action. We measure acquisition cost, conversion rate by channel, and sales cycle duration.
- Retention: encourage repeat purchases and recommendations. The retention rate and customer lifetime value (LTV) are the metrics that matter here, not the number of newsletter subscribers.
Each phase requires different channels and content. An SEO-optimized blog post works on attraction. A well-calibrated email sequence drives conversion. A relationship program fosters retention. Mixing objectives on the same channel dilutes results.
Generative AI in the marketing plan: what works and what remains unclear
The adoption of generative AI is rapidly progressing within marketing teams. The most common uses include content production (posts, emails, product sheets), creative brainstorming, and customer data summarization.
However, most SMEs remain at the stage of opportunistic experimentation. ChatGPT is used to write a LinkedIn post, but without a governance framework, without systematic human validation, and without integration into existing processes. AI produces volume, not strategy.
What makes a difference on the ground:
- Define a clear workflow: AI generates a first draft, a human validates the content, tone, and legal compliance (especially regarding product claims).
- Integrate AI into existing tools (CRM, email platform) rather than multiplying isolated applications.
- Measure the real gain: time saved per content piece, impact on open rates or cost per lead, not just the volume produced.
Concrete benefits depend on the level of oversight. Companies that gain a tangible advantage from AI in marketing are those that have framed it as a tool serving defined objectives, not as a creative shortcut.
Marketing channels: choose less to execute better
The temptation to cover all channels (SEO, social media, email, paid advertising, events) is the most common trap. We spread the budget, produce mediocre content on each platform, and do not master the indicators of any.
Two or three well-executed channels consistently outperform five poorly managed channels. The choice depends on the target and the buying cycle. For a B2B product with a long cycle, the duo of SEO content + email nurturing yields solid results. For B2C with impulse purchases, social commerce and targeted advertising are more suitable.
Criteria for arbitrating between channels
The first filter is the actual presence of the target. Posting on TikTok when the decision-making customer is fifty years old and uses LinkedIn is a waste of time. The second filter is internal capacity: it is better to manage a channel in-house with consistency than to outsource a channel without follow-up.
The third filter, often overlooked, is measurability. If we cannot attribute a commercial result to a channel within a reasonable timeframe, we risk maintaining an investment out of habit rather than performance. A simple dashboard with three indicators per channel is enough to make informed monthly decisions.
The most robust marketing strategy is not the one that covers the most ground, but the one where each action is linked to a measurable objective, supported by reliable data, and executed consistently.