Artefact Value By Data

Enriching the DIY experience: How ADEO uses AI to connect content and knowledge

Assortment optimization is a critical process in retail that involves curating the ideal mix of products to meet consumer demand while taking into account the many logistics constraints involved. The retailers need to make sure that they offer the right products, in the right quantities, at the right time. By leveraging data and consumer insights, retailers can make informed decisions on which items to stock, how to manage inventory, and what products to prioritize based on customer preferences, seasonal trends, and sales patterns.

MotherDuck Explained: How the Next-Gen AI & Analytics Solution Fits Into Your Data Stack

MotherDuck extends DuckDB's analytical performance to the cloud with collaborative features, delivering 4x faster performance than BigQuery and cost savings over traditional data warehouses through serverless, pay-per-use pricing. Following the announcement of MotherDuck’s new European cloud region, we were impressed by its performance and attractive pricing. MotherDuck can already be integrated into your gold layers in order to accelerate the serving of data use cases while saving costs at the same time. See performance benchmark.

How AI is changing search and what it means for customers, marketers and brands

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.

A C-Suite Guide to Marketing Measurement in 2025

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.

The Execution Problem: Why Even Flawless Pricing Strategies Fail Between the C-Suite and the Shelf

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.

Unlocking Commercial Efficiency: The Transformative Power of AI Agents

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 Survey “The future of Agentic Supervision” – Key Insights

In the evolving landscape of enterprise AI, the rise of agentic systems marks a pivotal shift. AI agents are autonomous applications powered by large language models (LLMs) capable of reasoning, memory, and action. They are no longer passive responders to user input; they are active decision-makers influencing business processes in real time. But with autonomy comes risk, and with risk comes the need for structured supervision. In this new paradigm, supervision of tech systems is no longer optional, it is foundational.

How conversational engines redefine visibility, transactions, and trust

As search progressively shifts toward conversational engines such as ChatGPT, Gemini, Le Chat, Claude or Perplexity, brands must fundamentally rethink how they exist online. Visibility becomes central: it is no longer about pleasing Google’s algorithms but about appearing within generated, synthesized, and contextualized answers.

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