Artefact Value By Data

ESG em ação: Transformando a sustentabilidade data em inteligência de negócios

Na última década, a sustentabilidade passou da periferia da reputação corporativa para o centro do desempenho dos negócios. O novo e-book do Artefact, ESG in Action, How to convert Environmental, Social, and Governance (ESG) data into business intelligence, documenta essa transição por meio de entrevistas semiestruturadas com líderes de C-suite de empresas globais como Accor, Legrand, Tarkett, Ardian, Heineken, Siplec e Schenker, além de insights da OECD e dos especialistas em sustentabilidade e data do Artefact.

O futuro do AI autêntico dependerá de gráficos de conhecimento?

À medida que as empresas se apressam para operacionalizar o AI, a maioria descobre que sua infraestrutura de data nunca foi projetada para raciocínio autônomo. Hoje, até 80% do tempo de implementação do AI é gasto em disputas e alinhamento de esquemas do data, um sintoma de infraestruturas criadas para armazenamento, não para compreensão. Sem uma base que capture relacionamentos e significados, os agentes continuarão poderosos, mas cegos. Com os agentes AI se tornando participantes ativos nos fluxos de trabalho corporativos, a natureza e a escala das consultas data estão evoluindo.

Moldando a estratégia AI em Energia e Indústria

Nos últimos 18 meses, o 'Generative AI' dominou todas as sessões de estratégia de nível C. Mas e se essa já for a conversa antiga? Nos setores industrial e de energia, a discussão está mudando rapidamente de GenAI para Agentic AI. Não se trata apenas de uma atualização incremental, mas de um novo paradigma, que vai do simples aumento de tarefas à reinvenção completa dos principais processos industriais.

Anúncios controlados pelo AI: O futuro da publicidade

Quando a OpenAI anunciou o Atlas, seu novo navegador com tecnologia ChatGPT, ela não lançou apenas mais um produto. Ele abriu uma porta que leva à próxima era da interação humano-computador e, inevitavelmente, a uma nova fronteira para a publicidade.

Data Plataformas para a Era Agêntica

A maioria das empresas não está pronta para substituir uma pilha de data da era do painel por uma pilha de AI. O último State of Data & Analytics da Salesforce indica que 84% dos líderes de data e analytics afirmam que suas estratégias precisam de uma revisão completa antes que as ambições de AI sejam bem-sucedidas. Os líderes estimam que 26% de seu data não é confiável, apenas 43% relatam estruturas formais de data governance e cerca de 50% não estão confiantes em sua capacidade de gerar e fornecer percepções oportunas. Ao mesmo tempo, 70% acreditam que os insights mais valiosos estão presos no data não estruturado. A conclusão é direta: o obstáculo não é o entusiasmo, mas a base, e essa base precisa mudar antes que os sistemas agênticos possam ser ampliados.

Enriquecendo a experiência DIY: Como a ADEO usa o AI para conectar conteúdo e conhecimento

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.

Explicação sobre o MotherDuck: Como a solução AI & Analytics de última geração se encaixa em sua pilha Data

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.

Como o AI está mudando a pesquisa e o que isso significa para clientes, profissionais de marketing e marcas

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.

Um guia para a diretoria para a medição de marketing em 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.

Ir para o topo