Originally coined by Philadelphia police in the 1950s to describe chaotic post-Thanksgiving crowds, “Black Friday” later gained a positive spin as the day stores turned “in the black” financially. Today, it marks the start of the holiday shopping season, both in stores and online.
In our previous articles, we challenged conventional ROI models for AI and introduced a multi-layered, context-driven framework for measuring AI’s unique value.
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.
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.
Real estate in the Gulf is moving faster and at a larger scale than at any point in the last decade. In Dubai, more than 43,000 property deals worth AED 115 billion were recorded in Q1 2025, with nearly 70% off-plan — evidence of liquidity but also exposure to delivery and handover risks.
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.
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.
The travel retail sector is at a fascinating crossroads. Passenger numbers across air and rail have rebounded to pre-COVID levels and are set to grow steadily in the years ahead - in stark contrast to declining footfall on the high street. Yet beneath this apparent recovery lies a challenge: spend per passenger remains 15% lower than before the pandemic, squeezed by rising costs and increasingly value-conscious travellers.
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.
