Viele Marketingverantwortliche stehen vor demselben Paradoxon: Trotz erheblicher Investitionen in generative KI stellen sich die erwarteten Auswirkungen auf Kosten, Geschwindigkeit und Leistung nicht ein. Warum? Weil die meisten KI-Systeme nur “denken”, aber nicht handeln. Agente-basierte KI ändert das.
In today’s data driven marketing landscape, Customer Data Platforms (CDPs) have become an essential component of a successful strategy. A CDP is a centralised system that collects, cleanses, and unifies customer data from various sources to build comprehensive customer profiles.
In this article, we explore why marketers – despite having more data than ever – struggle to turn it into actionable insights, and how AI Agents promise to deliver autonomous, high-value recommendations. Yet there’s a hidden barrier few talk about: inconsistent naming conventions. Without a standardized structure, AI Agents can’t reliably read, unify, or optimize your campaign data.Daniel shows why grounding your AI Agents in clean, enforceable data is critical for cross-channel analysis, faster insights, and confident budget decisions.
AI is transforming search, shifting it from ranking and retrieval towards reasoning and synthesis. This whitepaper charts this evolution, explains the mechanics of large language models (LLMs), and sets out the implications for marketers and brands. At the center of the new measurement landscape is the golden triangle of MROI: Marketing mix modeling (MMM) provides the strategic view, quantifying the impact of marketing on sales and offering optimizers and simulators to guide budget allocation.Incrementality testing validates whether campaigns truly drive additional outcomes, using test-versus-control experiments to establish causality. It also calibrates both MMM and attribution models.Attribution informs in-flight optimization by assigning credit across customer journeys. In 2025, advanced models use deep learning and attention mechanisms to capture channel interactions more effectively.These methodologies are most powerful when used together: MMM for long-term planning, incrementality for ground truth, and attribution for real-time agility. Companies also face the decision of in-housing vs. SaaS solutions. In-housing brings customization and control but requires talent and investment, while SaaS offers speed and expertise. The right choice depends on resources and data maturity. Real-world examples highlight best practices: Google’s Meridian introduces an open-source MMM toolkit to improve calibration, upper-funnel measurement, and bias correction.Accor uses incrementality testing to question assumptions and optimize budget allocation.Nike demonstrates the power of persistence and cultural change, embedding measurement into processes and democratizing insights.Artefact stresses the 95-5 rule, showing how brand equity measurement links long-term growth with short-term performance efficiency.Looking forward, five trends will shape measurement: improved data quality, new frameworks for retail media and connected TV, in-housed MMM with testing, privacy-first approaches, and attention-based metrics. The conclusion is clear: marketing measurement is now a strategic enabler. By integrating methodologies, embedding them in culture, and focusing on both performance and brand, CMOs can defend their budgets and unlock sustainable growth.
In 2025, marketing measurement has become a top priority for the C-suite. While generative AI is transforming campaign execution, measurement is what proves value and secures budgets. Yet maturity remains low: most CMOs still struggle to dynamically adjust spend based on performance. The challenge lies in balancing brand and performance marketing, coping with fragmented data, and aligning decisions across strategic and operational levels. At the center of the new measurement landscape is the golden triangle of MROI: Marketing mix modeling (MMM) provides the strategic view, quantifying the impact of marketing on sales and offering optimizers and simulators to guide budget allocation.Incrementality testing validates whether campaigns truly drive additional outcomes, using test-versus-control experiments to establish causality. It also calibrates both MMM and attribution models.Attribution informs in-flight optimization by assigning credit across customer journeys. In 2025, advanced models use deep learning and attention mechanisms to capture channel interactions more effectively.These methodologies are most powerful when used together: MMM for long-term planning, incrementality for ground truth, and attribution for real-time agility. Companies also face the decision of in-housing vs. SaaS solutions. In-housing brings customization and control but requires talent and investment, while SaaS offers speed and expertise. The right choice depends on resources and data maturity. Real-world examples highlight best practices: Google’s Meridian introduces an open-source MMM toolkit to improve calibration, upper-funnel measurement, and bias correction.Accor uses incrementality testing to question assumptions and optimize budget allocation.Nike demonstrates the power of persistence and cultural change, embedding measurement into processes and democratizing insights.Artefact stresses the 95-5 rule, showing how brand equity measurement links long-term growth with short-term performance efficiency.Looking forward, five trends will shape measurement: improved data quality, new frameworks for retail media and connected TV, in-housed MMM with testing, privacy-first approaches, and attention-based metrics. The conclusion is clear: marketing measurement is now a strategic enabler. By integrating methodologies, embedding them in culture, and focusing on both performance and brand, CMOs can defend their budgets and unlock sustainable growth.
Margin leakage often hides in complex pricing, promotions, and multi-channel strategies, where list prices rarely match the final pocket price. Promotions can cannibalize sales, and inconsistent channel discounts create arbitrage risks, silently eroding margins. Companies that define clear pricing architectures, analyze demand deeply, and govern execution with real-time monitoring turn pricing into a strategic lever. The result: higher profitability, smarter commercial decisions, and sustainable value capture.
AI Agents are revolutionizing commercial operations by automating tasks, enhancing customer relationships, and providing actionable insights. From boosting salesforce efficiency to optimizing pricing strategies, these intelligent systems help businesses achieve measurable growth and competitive advantage.
Artefact, in partnership with Societe Generale and Sorbonne University, presents a new AI approach to identify atypical customer profiles. Tested on real banking data, this open-source algorithm improves scoring accuracy while ensuring interpretability and practical applicability.
Google’s new AI Overviews are changing how users find information online. In a practical case from the Dutch sustainability sector, we explore how this shift is affecting SEO and SEA for a client active in boilers, hybrid systems, and heat pumps—and what it means for the future of digital marketing in the sector.
