Case Study: How Kantar Transforms Marketing Insights with AI

Kantar, one of the world’s leading marketing data and analytics companies, is revolutionizing how brands interact with data through artificial intelligence. With a legacy of over 40 years in AI, Kantar has recently introduced a suite of generative AI-powered tools to enhance marketing insights, accelerate decision-making, and improve innovation outcomes. Central to this transformation is KaiA – the Kantar AI Assistant – developed under the company’s newly launched AI Lab.

Key Takeaways

• AI powers the entire marketing lifecycle, from innovation testing (ConceptEvaluate AI) to ad effectiveness (LINK AI).
• KaiA, Kantar’s generative AI assistant, delivers conversational insights from brand tracking data.
• Tools like Text AI and Lift ROI integration illustrate AI’s role in streamlining analysis and campaign performance.
• The AI Lab consolidates Kantar’s strategy, embedding AI across products and value chains.
• Partnerships, like the one with AnswerRocket, further enhance AI capabilities with advanced analytics.

Approach

Kantar’s approach to AI adoption is grounded in integrating generative AI into its core products, data infrastructure, and client workflows. The company’s AI Lab was established as a center of excellence to unify strategy, engineering, and deployment. This lab is responsible for developing AI tools that merge proprietary datasets, validated brand growth frameworks, and expert analysis. A key tenet of Kantar’s strategy is to augment—not replace—human expertise, empowering users to extract value from data more quickly and confidently. By embedding AI across its full portfolio, from innovation to media and creative effectiveness, Kantar enables clients to scale insights, reduce time-to-market, and increase return on investment.

Implementation

Implementation of Kantar’s AI strategy centers on several key solutions. The flagship product, KaiA, is a conversational AI assistant that allows users to interact with brand tracking data using natural language queries. It leverages large language models (LLMs) and analytics to deliver relevant, actionable answers in seconds. KaiA is supported by ConceptEvaluate AI, an early-stage innovation screening tool that can test 10 to 100 product or service concepts in less than 24 hours. This model is trained on nearly 40,000 historical innovation tests and over six million consumer evaluations.

Another major innovation is LINK AI, which allows for the testing of digital and TV ads in as little as 15 minutes. It benchmarks performance against one of the world’s largest ad testing databases and uses predictive metrics such as brand lift, engagement, and behavior indicators. Text AI complements these tools by analyzing open-ended survey responses at scale, identifying sentiment and recurring themes while preserving privacy. Through its partnership with AnswerRocket, Kantar has added narrative-driven analytics and visualization capabilities, enabling clients to explore complex datasets through simple queries.

Results

The deployment of AI tools has produced significant results for Kantar and its clients. With KaiA, users can bypass traditional analytics bottlenecks and receive insight in real time, accelerating business decision-making. ConceptEvaluate AI has dramatically reduced the time and cost required for product concept testing while increasing the reliability of early innovation assessments. Clients benefit from its high predictive accuracy—up to 90% compared to past survey-based benchmarks. LINK AI enables rapid testing of ad creatives, allowing marketers to confidently allocate media spend based on performance forecasts.

These solutions are not only fast but also cost-effective, allowing organizations to scale insights across more campaigns, concepts, and use cases than previously feasible. Most importantly, Kantar’s AI tools provide decision-quality outputs that drive meaningful business outcomes while empowering users at all levels to interact with data directly.

Challenges and Barriers

Despite the clear advantages, Kantar has encountered several challenges in implementing its AI initiatives. One major hurdle has been fostering AI fluency among marketers and research professionals, many of whom are unfamiliar or cautious about using AI-driven tools. Building trust in the models—especially for high-stakes innovation or brand decisions—has required rigorous validation and ongoing education.

Integrating diverse and complex datasets into a unified platform has also posed technical challenges, particularly in maintaining data consistency, quality, and security. Furthermore, while generative AI excels in conversational interfaces, ensuring it consistently delivers accurate, brand-specific insights remains a key area of ongoing improvement. Kantar continues to address these challenges through robust training, secure infrastructure, and continuous model refinement.

Future Outlook

Looking ahead, Kantar plans to extend the capabilities of its AI portfolio and deepen integration across its full range of services. KaiA will expand beyond brand tracking to include other proprietary data sources, making insights even more accessible. The AI Lab will continue to innovate, introducing enhancements such as automated creative tagging, hybrid performance metrics, and integrated campaign optimization tools. ConceptEvaluate AI will evolve to cover broader categories and additional predictive features, while Text AI will be applied to new types of qualitative data.

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Sources:
Kantar.com
Kantar to Work with AI Analysis Firm AnswerRocket
Kantar announces launch of AI-driven, automated service for early-stage product development, evaluation
KANTAR LAUNCHES AI TOOLS TO ‘DISRUPT INDUSTRY’
Kantar launches AI Lab to enhance industry insights through integrated AI capabilities and extensive data
Kantar unveils AI-driven tool for early-stage product evaluation

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