Brandtech Group Launches Unified Data and AI Unit
The new unit helps companies unify fragmented datasets to scale AI-driven marketing strategies and improve search profits.
Updated on Oct. 26, 2026 in Advertising
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The Brandtech Group has consolidated its data and AI capabilities into a new unit, Brandtech Data, which operates across 22 countries. This integration combines specialist teams from fifty-five, DP6, and Jellyfish to serve clients with over 500 total specialists.
Why it matters
Companies are increasingly creating centralized data hubs to resolve fragmentation across platforms and prepare existing datasets for AI integration. This move allows The Brandtech Group to scale its data and technology offerings under a single, unified operational framework.
Brandtech Data launches with over USD $100 million in annual revenue generated by 500 specialists across 22 countries. Case results include an 83% increase in eCommerce revenue for Salomon and USD $4.5 million in savings for TotalEnergies using the firm's AI-led models.
The players
The Brandtech Group
A global marketing and technology firm that provides data, AI, and digital advertising services.
Will Heins
The Chief Executive Officer of Brandtech Data who leads the newly integrated practice.
Pierre Harand
The President of Brandtech Data responsible for the firm's global operational strategy.
The details
The new unit integrates data, creative, media, and technology services into a single operational framework. By grouping specialists who previously worked across shared client accounts, the company aims to eliminate the friction caused by fragmented data silos. This approach forces a consistent standard for data and technology foundations, which the company claims is essential for optimizing AI-led marketing campaigns.
Timeline
October 26, 2026: The Brandtech Group officially launches Brandtech Data.
Market Landscape
Brandtech Data's formation aligns with the industry-wide trend of adopting AI-based marketing mix modelling to manage complex datasets. The consolidation marks a departure from fragmented service models in favor of unified AI transformation strategies.
Operators should evaluate whether their own data teams are sufficiently integrated or if internal silos are inhibiting AI readiness. The results seen at firms like John Lewis and Salomon suggest that real-time data collection remains a primary lever for profit improvement.
The takeaway
Centralizing data operations is a critical step for companies attempting to turn raw customer information into automated AI-led marketing results. Managers should audit their current data technology foundations to identify if current silos prevent the deployment of AI-based predictive models.
Further reading
For more insight into how agencies manage global digital portfolios, visit the Advertising section.
Source note: This article includes information reported by eCommerceNews Australia.
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