Data Valorization & Category Management
Unlock hidden business value in your data through structured data valorization and category management strategies.
As businesses accumulate vast amounts of data, the challenge lies in transforming it into actionable insights that generate tangible business outcomes.
Artefact’s Data Valorization and Category Management services help enterprises identify, manage, and extract value from their data assets.
By combining best-in-class data management practices with advanced analytics, we enable organizations to unlock new revenue streams, improve operational efficiencies, and make more informed strategic decisions.
Transforming data into business value
At Artefact, we take a systematic approach to data valorization, identifying opportunities to maximize the impact of your data across different categories and functions.
Our expertise in data category management ensures that data is categorized, governed, and utilized effectively, providing the foundation for informed decision-making and innovation.
- Data Inventory & Audits: We conduct a comprehensive audit of your existing data assets to identify opportunities for value creation.
- Data Categorization & Management: We implement frameworks for organizing and managing data by category, ensuring data integrity, accessibility, and compliance.
- Monetization Opportunities: We identify and develop data monetization strategies by leveraging insights to open new revenue streams and partnerships.
- Data-Driven Decision Making: We empower teams to make data-backed decisions through effective visualization and reporting tools.
- Advanced Analytics & AI Integration: We leverage AI and machine learning to extract deeper insights, improve forecasting, and drive innovation from categorized data sets.
Data monetization opportunities for retailers: Retail Media within the CPG/Retailer data ecosystem
Data monetization: retailers are monetizing existing consumer data across CPG brands to support their customer centricity. 1P data shared by retailers originates from their loyalty program. The cardholder data they share can be socio-demographic (e.g. the age of their consumers), transactional (e.g. what did they buy), behavioral (e.g. what did they look at), loyalty data (e.g. did they buy again), etc. This data is shared “as-a-service” in a data clean room where brands can access the retailer’s data in a secure environment to carry out specific use cases defined by the two partners.
Carrefour, for example, has created a consumer intelligence service called Carrefour Links, based on the LiveRamp clean room, where partners can access their cardholder data. This is a self-service platform that allows users to perform basic activities such as reconciling retailer and brand databases on individual customers to build a more complete view of the consumer and thus improve their experience. It also provides analytics and measurement capabilities that Carrefour can bill to its partners.
Our expert content about Data Marketing
AI Agents Are Changing How People Shop. Here’s What That Means for Brands.
The rapid adoption of AI agents has major implications for who captures value in consumer transactions—particularly who owns the end customer. In the pre-internet era,...
Céline Bracq and Florence Bénézit discuss the survey "Future of work with AI."
Florence and Céline talk about how AI is revolutionizing the workplace, improving productivity, creating new opportunities, and transforming the way employees collaborate.
Privacy, Data, and Effectiveness: The State of Digital Advertising in 2025
Digital advertising and measurement are evolving fast, driven by privacy centric measures. These driving forces consist of changing legislation, growing awareness for data ethics, privacy...
Vincent Luciani, CEO and co-founder of Artefact, presented the main insights of The Future of Work with AI survey
Vincent shared positive outcomes on the benefits of generative AI boosting employee productivity and enhancing collaboration, with 92% of users reporting satisfaction.
MMM Requirements and when to look for other options?
Bayesian MMM can transform your company's marketing results, but not all organizations are ready. Understand the criteria for deciding.
Transforming Customer Relationships with CEPs: A Game Changer for Businesses
Today’s businesses face the challenge of building personalised connections with customers across multiple channels. A Customer Engagement Platform (CEP) is designed to simplify this by...
Marketing Mix Modeling in Pharmaceuticals: challenges and solutions
Marketing Mix Modeling (MMM) has long been a valuable tool across industries for data-driven decision-making. Recently, it has gained renewed attention in healthcare and pharmaceuticals...
Demystifying brand and long term effect measurement in Marketing Mix Modelling
Did you recently make a significant purchase, like a new phone, car, furniture or even jewellery? If yes, then you are probably not buying them...
The holistic measurement puzzle: Navigating the complex landscape of Marketing ROI
Measuring and optimizing marketing ROI is a challenge for many companies, with 70% of marketing executives struggling to do so effectively.
How does generative AI create more personalized marketing?
Generative AI personalizes and optimizes marketing strategies, signifying a decisive turning point in customer engagement and campaign performance. Here's a look back at what Hanan...
Think with Google – How the Egyptian tourism authority used AI to measure the real impact of their ad campaigns
One of the biggest challenges travel marketers face today is measuring the real impact of their ad campaigns. That’s because most travellers book their holidays...
Unlocking growth and efficiency: Leveraging Customer Data Platforms in financial organizations
Customer Data Platforms (CDPs) are one of the key technological enablers for staying competitive in a rapidly evolving industry landscape. CDPs aggregate, segment, and leverage...
