Trends in digital marketing

Successful brands will master both worlds: the scalability of AI and the credibility of humans. Marketing teams will not have to choose between them. They will combine the possibilities of AI with the relevance of and trust in human insights. Those who use attribution, authenticity, and intent-driven strategies will lead the next era of performance marketing. The new premium will be characterized by authenticity, proximity, and verified content. This is the view of marketing analytics company Nexoya, which has identified three major trends.

Trend 1 – Hybrid advertising world: AI-generated networks are spreading, but human interaction creates more trust

Today, all social media platforms use artificial intelligence. What is new is that more and more AI-generated social platforms are coming onto the market. AI is no longer an add-on feature as it is on conventional platforms. Networks use AI for everything—from content creation to feed personalization and moderation. Now, even micro-communities can be generated entirely by AI. Here, the entire environment can potentially be created automatically. This opens up scalable opportunities for engagement and storytelling.

However, the steadily growing share of AI raises new questions regarding authenticity, trust, and brand risk. AI-generated content such as texts, images, and videos are inexpensive to produce and sound plausible. However, they often contain false facts and information. And AI can be used to deliberately manipulate people on a large scale. Misinformation and a general loss of trust in the media remain problematic if sources cannot be verified or if content is not curated. Users are therefore beginning to question AI-generated platforms. This development is already having an impact on consumer behavior and is thus also influencing performance marketing strategy. Marco Hochstrasser, CEO of Nexoya, says: «It remains to be seen how strongly the new AI platforms can influence purchasing decisions in the long term. Their rise will definitely change the advertising landscape. In addition, their widespread use could lead to stricter standards in terms of verification, identity, and brand safety.»

As AI-generated content floods social media feeds, a clear countertrend is emerging: in a world full of synthetic content, trust is becoming a distinguishing feature. Brands that can demonstrate verifiable data, credible attributions, and verified campaign results will stand out from the crowd. Social feeds with exclusively human-generated content, content prioritization based on friendships, and curated offline experiences are becoming more popular.

Marketers will not abandon AI automation as a result of this development. But they will combine it with the creation of communities that put people first, hybrid events, and exclusive formats. Advertisers will prefer to invest their budgets in platforms that reveal the reasoning behind every change, recommendation, or forecast. Marco Hochstrasser emphasizes: «Transparency is no longer just a compliance requirement, but is becoming a performance advantage for advertisers.»

Trend 2 – Multi-layered search: AI-based results are moving away from keywords and toward conversation-based queries

Searches are no longer limited to text queries in traditional search engines and are shifting toward conversation-oriented AI assistants. As a result, pure keyword strategies are losing influence. The results have also changed fundamentally: search engines are increasingly displaying AI-generated answers to users. Consumers now discover products and brands via voice assistants, visual search, and generative AI interfaces. Search tools provide answers instead of the long lists of web links that were previously common. At the same time, social platforms such as TikTok and Instagram are developing into independent search destinations that strongly influence the visibility and perception of products and services.

Platforms such as ChatGPT, Gemini, and Perplexity are developing «geo-related insights.» Here, search results reflect a mixture of search intent, location, context, and user scenario. In the future, advertisers will optimize their campaigns for moments, location-based intentions, and conversation-oriented responses. We will soon be using geo-based systems that show how search queries differ depending on the city, market maturity, or competitive environment.

In addition, the regional inaccuracies in GEO, SEA, and SEO that models and advertising platforms have struggled with in the past will be eliminated. Marco Hochstrasser expects significant improvements in this area by 2026: «Search and advertising platforms will gradually provide region-specific insights into user intent, localized attribution results, and location-based data on advertising performance. Performance teams will finally be able to align spending with actual local impact rather than just aggregated averages. Combined with platforms that enable ad delivery—one example being ads in the free version of Perplexity—this opens up new opportunities for performance marketing.»

This shift is forcing advertisers to fundamentally rethink their strategies. They need to understand the contexts in which their target groups search: from spoken search queries on smart devices to image-driven moments of inspiration to AI-generated summaries of the best products or services. To succeed in this environment, they must adapt content and creative formats, optimize for new search interfaces, and monitor the initial impact of generative search on traffic and conversion paths. 

Trend 3 – Cross-channel attribution: In the cookie-free era, multi-touch attribution has reached its limits

Traditional attribution models are under pressure as data protection regulations and changes to platforms limit data transparency: usable cookies are becoming increasingly scarce and publisher data is distorted. Static triangulation—the systematic combination of multiple analysis methods and data sources for a holistic evaluation of campaigns—tends to cause confusion rather than clarity, especially for larger advertisers. The new standard is regression-based cross-channel attribution, enabled by data protection-compliant CRM/shop and ERP integrations, aggregated data, and statistical modeling. These systems continuously measure the actual contribution by channel, campaign type, and even creative concept, based on real budget shifts and incremental effects. Marco Hochstrasser says: «Advertisers are becoming increasingly skeptical of the platforms» measurement tools, citing conflicts of interest and a lack of transparency as reasons."

Nexoya solves the long-standing attribution dilemma by implementing regression-based attribution methods in daily practice. Monthly statistical modeling uses weekly budget adjustments as ongoing micro-experiments, allowing the model to continuously learn and improve its accuracy week after week. This provides marketing teams with both rigorous measurements and actionable campaign-level budget recommendations that can be reviewed by teams and implemented with a single click.

Source: Nexoya