“For more than 50 years, our unrivalled brand expertise, deep understanding of people, and track record in innovation, have made us the indispensable brand partner for the world’s most valuable companies. 

Today, AI enables us to go further and faster for our clients, making strides that are redefining the relationship between business and consumers. 

Thoughtfully and responsibly, we are now infusing GenAI into our core to reimagine the future better than anyone in the industry. Together, we’ll write the next chapter of brand history.” 
 
Chris Jansen 
CEO, Kantar 

Our AI manifesto

 

Kantar is your indispensable brand partner in a world being reimagined by AI

Innovation in AI is opening new frontiers in the collection, interpretation and application of human data. It enables even deeper understanding of how people everywhere think and act - and allows us to generate brand-defining insights at ever greater speed and scale.

Kantar's application of the most meaningful data, validated brand growth frameworks, and longstanding AI models, enable our AI portfolio to unlock profound new possibilities to shape your brand's future.

Real answers from people, at scale, are the fuel of our AI capabilities. Through our comprehensive data ecosystem, we are the global authority for sourcing the most trusted, highly-permissioned, and meaningful data from the highest quality panels and other sources of proprietary research.

This fundamental ingredient, with our expertise and technology, makes Kantar's AI one-of-a-kind. 

 

35 million human responses from 250,000 ad tests over 30 years powering Link AI
11,000 ads tested in less than a month by Google
1.3 billion data points from real people processed through Trend AI annually
30 billion authentic digital media impressions measured monthly


AI has been around in various forms for 50+ years, however Generative AI models such as ChatGPT have captured popular imagination in a way that previous technologies did not, and businesses all over the world are scrambling to create AI roadmaps and AI strategies that match the new pace of advances.

At Kantar, we have a rich history of innovation in this space, with AI and machine learning deeply embedded across our entire product suite and ways of working

How we help you 

  • How can marketers leverage AI to test more of their advertising faster and drive stronger marketing impact?

    Using AI and machine learning, Kantar continues to forge new innovative paths helping advertisers drive stronger marketing impact through creative.
    It tests creative assets quickly, iteratively and at scale, decreasing time to market and increasing ROI for our clients. Link AI on Kantar Marketplace is the fastest, fully automated, AI-powered solution to guide creative and media optimisation available today.  It is built on a database of over 250,000 ads and 35 million human interactions.

    Find out more with LinkAI

  • How can AI help marketers be in control of their marketing budget and enable tactical decisions? 

    Get highly scalable AI-powered cookie-less unified measurement and understand the relative contribution of all marketing mix elements. UMMO (Unified Marketing Measurement and Optimisation) puts you in control of your marketing budget and calculate your unified marketing (ROI) and their short and long-term impact on sales and brand equity. 

    Find out more with UMMO

  • How can marketers use AI to ensure that all brand assets deliver a consistent message across touch points and build competitive advantage?

    NeedScope has helped drive brand growth in more than 15,000 studies across 115 markets.

    Understand the functional, identity and emotional needs in your market and how best to access them, using Kantar's validated psychological framework and AI capability. Analyse a brand’s imagery and video to understand the degree to which they are in alignment with the brand’s targeted emotive positioning across touchpoints.

    Find out more with NeedscopeAI

  • How can AI-driven technology help marketers build brand equity and predict future performance? 

    Kantar BrandNow embeds Kantar’s proprietary AI technology Trend AI, to removes noise from survey data, making data lag-free and truly real-time. Understand the key drivers propelling your brand growth, so you can invest your resources in the right place at the right time, with the confidence of Kantar's globally accredited brand equity framework.  

    Find out more with Kantar BrandNow

Our guiding principles for ethical and responsible, Indispensable AI

 

  • Transparent and clear

  • Interpretable and trustworthy 

  • Human oversight

  • Data management protocols

  • Full impact assessments

  • Close collaboration

  • Embedded accountability

  • People training and awareness

Our data responsibility pledge


Privacy
Apply our rigorous user permissions standards and ensure compliance with global data protection and privacy laws where PII/personal data is utilised or generated.

Quality 
Ensure the data used for AI models is reliable, complete and relevant to research purposes. 

Ownership and Use
Define and communicate the intellectual property rights involving the ownership of data, the AI Model, technologies, outcomes and other materials generated. 

Lineage
Track the provenance of data and its transformation throughout the lifecycle. 

Clients and 3rd parties
Assess whether our use impacts intellectual property rights belonging to clients or others. 

AI is transforming how we deliver brand success, every step of the way

"Our world-class behavioural and attitudinal data and data-engineering expertise are the bedrock on which we're building our next generation of AI-powered products.

Katalyst, our unique product development process, is how we're making these possibilities a reality today, accelerating our time to market and allowing us to stay ahead in a field that's constantly changing. 

Katalyst applies 40 years of industry leadership into state-of-the-art product methodology, ensuring brand success is repeatable, scalable and efficiently achieved. "

Ted Prince
Chief Product Officer, Kantar

Kantar's AI solution suite

BrandDynamics is a daily brand performance tracker to help you monitor your brand and competitors in real-time. 

Supercharged with Kantar’s proprietary Trend AI technology to cancel the ‘noise’ in the data that distorts short-term metric movements and lets customers see category trends without time lag. 

BrandHealth is a continuous brand health intelligence system that acts and reacts to threats and opportunities. Leveraging Kantar’s Trend AI and MDS framework supercharged with ML.

BrandStructures uses advanced analytics and ML to identify associations and help you focus on those that are likely to help grow your brand. 

BrandDigital uses AI to analyse millions of search data points to anticipate trends in your category and predict who or what will likely cause disruption. 

Needscope AI decodes images, music, and videos based on their symbolic meaning, using a validated psychology-based framework. We help you differentiate your brand positioning and deliver a consistent experience across touchpoints. 

GrowthFinder uses Kantar’s AI technology to segment by needs, attitudes, and behaviours to build a demand framework to tell the market's story. With GrowthFinder, you can put a value on each Demand Space segment in the framework to inform your portfolio strategy and investments. is a daily brand performance tracker to help you monitor your brand and competitors in real-time. 

TrendEvaluate – Coming soon.

ConceptEvaluate AI – Coming soon.

AI

LINK AI reliably predicts an ad's in-market success in under 15 minutes without a consumer sample. Our advanced AI video processors extract every detail, from eye-catching visuals (pictures, objects, colours) to engaging audio (speech, sound effects) and even on-screen text. Then, state-of-the-art machine learning models analyse it all to predict your ad's effectiveness in record time.

LINK+ delivers razor-sharp insights tailored to your campaigns, whether you need a fast go/no-go call or in-depth guidance for early development— our powerful AI is behind our predictive key metrics for stronger ads that boost sales and brand value. Measure only what matters, optimise like a pro, and get results fast – all thanks to LINK+ unmatched flexibility.

AI

LIFT ROI leverages Hamilton.AI to provide sound, unified metrics for marketing measurement and optimization. With intelligent automation, target a 10x-20x return on investment, guiding both strategic and tactical in-flight decisions across channels. 

LIFT+ coming soon. 

AI

Worldpanel Simulators use AI and ML to model and evaluate a range of 'what-if' scenarios to take the guesswork out of your major decisions. 

By harnessing Kantar's unique behavioural data – from real shoppers over many years – we can help you identify which strategy is most likely to win.

Worldpanel Plus uses Shoppix, a proprietary smartphone app, where panellists can record their purchases and the motivations behind them in real-time. We use image processing and receipt decoding to join the dots on shopper behaviour across all trips, channels and industries - online and offline. 

AI



Kantar’s AI Lab

Explore how Kantar innovates with AI in collaboration with clients and partners.

Click here

Client results 
Explore AI implications and find more opportunities through our articles
Inspiration
insights
Insights must stir things up. Not to be disruptive, but to kindle better conversations leading to smarter outcomes. AI will enable insights teams to do this at speed and at scale.
Fusing survey data and synthetic sample
Investigations into using off-the-shelf Large Language Models to generate data. New Kantar analysis tests synthetic sample vs human survey data to uncover the truth behind artificially created qualitative and quantitative market research data.
AI
With AI now in the mix, insights organisations must ask themselves whether research skills are still relevant; what will AI do better and how AI will enable insights professionals to do better as a result. Read the first article in a series about the impact of AI on key areas of Insights, along with implications for the commercial and business role of insights leaders.
FTF
Finding the Future: Global Emerging Trends Report 
Download the report

FAQs

  • What is Generative AI? What are Large Language Models (LLM)?

    Generative AI is a new and exciting type of artificial intelligence system capable of generating new content such as text, images or videos. Generative AI systems are based on "foundation models", that are capable of ingesting text, images, audio or videos and generating data of any or all of these types, in response to human prompting. Large Language Models (LLMs) are a special class of foundation models that work with text data.

    What makes foundation models very powerful is that they are "task agnostic", i.e., they can be highly proficient on seemingly unrelated tasks that they were not explicitly trained for. For example, LLMs are typically only trained to predict the next word in a sequence of words. However, this training when done at a massive scale, apparently allows the models to write poetry, do math, write code, solve puzzles, excel in exams and much much more.

    Experts agree that we are far from arriving at Artificial General Intelligence – the time when a machine will be able to understand or learn intellectual tasks as a human would. However, foundation models could be a possible first step.

  • How is Generative AI different from Traditional AI?

    Both Traditional AI and Generative AI are based on Machine Learning - algorithms that enable machines to learn from data without being explicitly programmed. However they differ in important ways.

    Traditional AI models are mostly focused on advanced analytic tasks such as prediction or clustering. They typically work with just one form of data and typically are trained for one specific task that they become very proficient at. They need to be trained from scratch or "fine-tuned" to perform well on a different task. Generative AI models on the other hand are based on foundation models that can ingest data of various types (text, image, video) and output any/all of these types. Generative AI models require orders of magnitude more data than traditional AI models but when provided with such data are more versatile - they can be good at activities they were not explicitly trained for.

    Neither form of AI is necessarily "better" or "worse" than the other. Each has its own benefits depending on the intended use case and in fact in many practical situations, the best solution involves a combination of both. For example, Link AI uses both Generative AI and Traditional AI as part of the same overall framework to issue its predictions.

  • What are the known limitations of Large Language Models?

    There are quite a few known risks that we see in the market research industry. One is that the model starts making things up that are factually incorrect or fantastical - a phenomenon referred to as "model hallucination". A second is that the models might not be entirely up to date - we’ve seen this with time series examples where the previous version of ChatGPT gave wrong answers because it was only updated to 2021. More fundamentally, LLMs have no ‘knowledge of knowledge’, so there’s no such thing as a confidence level. And LLMs have no notion of time or temporality, or maths, which is rule-based, so they are currently limited in their interpretation of data to what they can discern through generic associations.

    Aside from technical issues, there are also potential legal and ethical issues that arise. Intellectual property, for example: is this a creative act by the LLM, or is it re-hashing someone else’s IP? Does sharing your own data on the open web mean you give permission for it to be used by LLMs? And finally, the quality of the datasets the models use could easily reinforce biases and stereotypes without ‘knowing’.

  • What are some example use cases for Generative AI techniques in market research?

    Use cases for Generative AI fall into 3 broad categories:

    1. Making things more efficient: Foundation models can free up a researcher to focus on what is important.

    - Summarisation: market research collects a lot of data in the form of words – survey verbatims, qualitative interviews, and focus groups. LLMs could summarise, order and prioritise responses expediting the work of the researcher when creating a narrative for the client. LLMs and foundation models can even summarize videos and images!

    - Automated reporting: market research also produces large volumes of quantitative data that need sorting, summarising, and presenting. LLMs could quickly organise and create draft headlines based on charts, tables, models, as well as executive summaries.

    2. Doing things at higher quality: Foundation models can do what earlier AI models did at much higher quality, sometimes surpassing a human

    - "Attribute" identification: LLMs can identify themes, assess sentiment, brand affinity, brand perceptions, identify emotions, fix for the researcher to refine.

    - Prediction: Foundation models allow us to extract embeddings (mathematical representations) that other machine learning models can use to predict some outcome of interest. For instance, does the dialogue in a TV ad help predict its performance? How can we relate people’s qualitative experience interacting with a service representative to their brand loyalty or churn? The quality of such embeddings is often significantly superior to the previous generation of AI models

    3. Doing entirely new things: Generative AI opens the door to many new applications

    - Intelligent interviewing: already in use by the industry, conversational AI will come on in leaps and bounds, responding to previous answers and routing questions accordingly. And designing quant questionnaires will never be the same again, the machine can help with automating and standardising the process!

    - Creative Writing: this could be anything from creating discussion guides, initial drafts of presentations, marketing copy, concept statements to video ads

    - Conversational search queries: think of ’an intelligent agent’ that sits on top of data platforms you can query in natural human language. The agent then analyses potentially massive databases ’underneath’ and fetches back the results in natural language.