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Case Study


WPP paired with AI to fuel creative data uses in the hotly competitive global advertising market.

The Challenge

WPP is the largest advertising firm on the planet, a tough title to hold in a world that spends more than $800 billion annually on ads.

Innovation is essential to retaining the “world’s biggest” distinction and is an approach WPP embraces wholeheartedly. The global firm, which has more than 100,000 employees in 3,000 offices across 100+ countries, sees generative AI as a key part of future growth, and it’s aggressively pursuing imaginative ways to power growth.

In the second quarter of 2023, WPP announced a partnership with chipmaker Nvidia to use AI in advertising. And consumers could soon see AI-generated cars traversing mountains, cities or deserts depending on the ad market.


But AI is fueling WPP behind the scenes in equally important ways.

With, WPP has developed a connected knowledge platform powered by AI that fuels data-driven creativity. Broad user adoption fueled by ease-of-use with robust data discovery and context has yielded clear benefits:

  • 1,500+ users are consistently active on the platform

  • 70% of WPP agencies actively use

“You show people what they can do, and they want more of it,” said Vip Parmar, WPP’s global head of data. “It’s like getting to a destination – I want to get there in a more efficient way in terms of time and cost.

“Getting our data out of silos and shared across teams is how we grow.”

WPP at a glance

HQ: London, UK
Industry: Advertising & Media
Ticker: WPP (NYSE)
Data catalog users: Approximately 1400
Countries: 152
Companies: 500+
Use Cases: Data Discovery, Data Integration
Challenge: How to find, curate and inventory data
Solution: offers both data virtualization and data management

Top priorities 

1. Find the data
2. Understand its meaning
3. Use it effectively to grow the business

“If you don’t choose a data catalog platform on a knowledge-graph architecture, and bring in all data and knowledge, governed in one platform, then you are setting yourself up for failure in an AI future.”
Vip Parmar Global Head of Data at WPP


WPP’s goal is to develop itself into the world’s most advanced and respected creative tech company. The aim is to harness all of the company’s assets in a connected way, build stronger collaboration across the enterprise, and help clients win with data. 

Through this approach, WPP can strongly differentiate itself from its competitors in the ad space. To accomplish this goal, WPP customers required a solution that could overcome data silos and foster a genuine data-led culture.

Finding, sharing, and using data was a persistent challenge

Given its global presence, WPP faces significant data silos within its organization, making it difficult to identify relevant expertise and collateral for client projects.

  • Digital Transformation: WPP is going through a digital transformation process that requires adopting modern technology. 

  • Diversity of sources: Cloud data sources such as Snowflake and Google Big Query, but also semi-structured such as Google Sheets, CSV files, and even unstructured data in files, images, etc.  

  • Distribution: With over 100,000 employees in 100+ countries and a diverse range of data resources, it became increasingly challenging to efficiently utilize available data.

  • Data Value: For data to be meaningful, it has to be discoverable. If a data chef doesn’t know what’s in the pantry, how are they going to know what they can cook?

The lack of knowledge about available resources results in duplicate work across different departments, wasting time and resources and most importantly restrains creativity and innovation. As a result, WPP was not clearly able to get ahead of its competition. 


In order to develop a connected knowledge platform that fuels data driven creativity, WPP required a solution that addressed three key requirements.

Requirement 1: Knowledge-Graph Architecture

WPP needed to have a guarantee that it could bring in any type of enterprise resource, without exception. To build a knowledge platform, WPP needed to connect data assets with application code that is using those assets, the people who have created the assets, and client case studies that illustrate the value derived from the data.’s knowledge-graph architecture provided the flexibility to support all kinds of diverse resources.

“Without a knowledge graph, it would just be a catalog that would not scale,” Parmar said.

Requirement 2: Platform

A data catalog platform provides a strong foundation in order to build any type of applications. WPP needed a guarantee that it could build any application required to support yet-unknown use cases that could arise in the future. For instance, if WPP wants the capability to build recommendation systems using all the connected data in the data catalog. This is not a capability that traditional data catalogs offer.

Requirement 3: User Adoption

WPP needed the ability to unlock widespread user adoption. Marketplace alternatives were too focused on technical users and wouldn’t empower the wide expanse of global business users WPP wanted to benefit from better data access. 

A flexible, federated solution paired with AI

At WPP, creativity lies at the core of its operations. Employees continuously strive to leverage data and assets in pioneering and unique ways. With, WPP is able to push the boundaries of what's possible by leveraging the knowledge-graph architecture and generative AI in order to increase productivity, efficiency and ultimately creativity. 

Knowledge Graph

By integrating traditional data assets with additional resources — like code repositories, people, case studies and additional knowledge assets — when users find data, they can find code that has used the data, the people who have used it before, case studies that describe customer challenges solved with the data and much more. provides WPP a holistic solution, facilitating informed decision-making and fostering collaboration.

The knowledge-graph architecture provides the ability to offer applications that go beyond traditional data catalog features. For instance, WPP is leveraging the platform to create an application that provides recommendations on which code base to use or suggests individuals to consult based on their expertise. By seamlessly integrating data assets with these additional resources, users can easily discover code that has utilized a particular dataset, identify the individuals who have previously interacted with it, and access case studies illustrating customer challenges resolved using the data.

The implementation of a knowledge-graph architecture empowers WPP in several ways. For one, it enables the support of existing client use cases while also catering to future, yet unknown, use cases. By accommodating evolving requirements via, WPP maximizes and future-proofs its investment in data. This versatility translates into substantial gains in productivity and efficiency, ultimately fueling creativity throughout the organization.

“If you don't choose a data catalog platform on a knowledge-graph architecture, and bring in all data and knowledge, governed in one platform,” Parmar said, “then you are setting yourself up for failure in an AI future.”

Generative AI

Building upon’s platform, WPP pioneered integration of generative AI with by expanding capabilities for metadata enrichment, data discovery, and idea generation.

Metadata Enrichment

A significant challenge faced by WPP is the slow process to enrich the cataloged resources. By transferring to AI the manual curation tasks that humans typically perform — generating tags, descriptions, and summaries — WPP is empowered to streamline data ingestion and enhance the quality of its catalog. This feature has reduced the time to enrich resources in the catalog and has improved data discoverability. 

Augmented Natural Language Search

Another pain point was the difficulty in finding the right data within the catalog. Moreover, the catalog alone didn't always have the data WPP employees needed, necessitating searching external resources. Now, with an augmented natural language (NL) search feature, users have a unified platform where they can search for specific data, seamlessly across internal and external sources in natural language. This streamlined approach enables efficient data discovery, saving valuable time for users.

Driving Creative Ideation with Data

WPP's goal is to best leverage data to solve client challenges creatively. This AI feature enables users to input a client challenge into the catalog. AI analysis generates creative approaches to and suggests ideal data sets to tackle the challenges. Additionally, the AI assistant connects to the data catalog knowledge graph and external repositories to provide users with the relevant datasets required for projects. This innovative approach not only stimulated creative thinking but also facilitated data-driven decision-making.

WPP’s AI foundation led to the company co-innovating with to bring generative AI-powered features to market. Archie Bots launched in March 2023. 

Evolution of Data Catalog growth powers WPP Open, a platform that allows users to unlock and share data resources across the WPP network – deliver engaging pitches, client work, and research. Users can now share data and knowledge – find data, documents, images, videos, and analysis that you can adapt for your own collaborative projects. WPP Open delivers valuable insight from one location — centralize and manage project datasets in one simple user interface

Initial Phase

The implementation of began with cataloging WPP’s existing content, which included produced and procured data. This formed the foundation of the data catalog, similar to the original ingredients in a pantry. With the data catalog initially populated, WPP could now ask what data don’t they have that they should? 

Adoption and Collaboration

To encourage adoption, the customer demonstrated the platform's capabilities to users, showcasing how it could help them find relevant APIs and resources efficiently. As users began to explore and utilize the catalog, they created new data solutions (following the analogy, now there is a chocolate cake that has been baked). This work was then added back to the catalog, allowing others to find and reuse it for related projects (like a vanilla cake). This fostered collaboration and innovation across the organization.

Outcomes and ROI

Increase Deal Wins

WPP's strategic utilization of data has revolutionized its approach to pitching to clients, resulting in a significant increase in deals won. At the heart of this transformation is through its search and discovery capabilities.

By incorporating data-driven insights into its pitch preparation, WPP not only showcases its creative solutions but also demonstrates its ability to effectively address clients' challenges. These valuable insights are derived from the data that users discover in 

Moreover, WPP leverages data to identify untapped opportunities and proactively offer tailored solutions, setting them apart from its competitors. 

Culture of Collaboration and  Innovation serves as a central hub that drives a culture of innovation within WPP's distributed and federated organization. Today, has grown, encompassing 10 subject domains and boasting an adoption of thousands of users and growing. Six in 10 users consistently re-engage with each month, as do a significant 70% of WPP's agencies.

“AI is changing the way we work, but its outcomes are only as good as the data that’s put into it,” Parmar said. “That’s why it’s key to have a foundation of diverse, connected data that’s contextual and relevant and works in conjunction with AI. 

"That’s what sets us up for."

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