Written by Julian Highley, SVP Data Science
With all the buzz surrounding Generative AI, the true transformation in marketing research is being overlooked. Don’t get me wrong, the AI advancements are impressive, but it’s the data that ultimately drives the revolution.
Generative AI has captured the imagination of marketers and researchers with its ability to produce human-like text, images, and code. However, the real power of AI lies in its ability to analyze vast datasets, uncovering patterns invisible to human eyes. Connecting the right data to the right algorithm is the critical component for unlocking AI’s full potential for marketers and researchers.
Generative AI is set to revolutionize marketing research, but it won’t completely replace the human insights captured by traditional surveys just yet. Why? AI-generated research relies on behavioral data and foundational research featuring real human behaviors and opinions. If this foundational data is outdated or flawed, or the AI model is bad – your research fails.
In the age of AI, research companies must be able to create AI models that extract data from traditional surveys and real-time datasets, including transactional, web browsing, and social media data. These datasets offer a window into human behavior, revealing patterns that surveys and focus groups alone can’t capture. For example, a marketer who adds purchase data to a traditional conjoint study about sneaker buying, might be surprised by the additional context they glean.
Transactional and web behavioral datasets have been around for a while, but the ability to combine multiple data sources into an AI model is more advanced than ever. MarketCast now leverages over 40 different types of data, beyond traditional surveys, to deliver cutting-edge insights. These models, once requiring full-time attention and manual processing, are now fully automated using AI and advanced algorithms.
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Today, our research experts at MarketCast often look to more obscure datasets when tackling client challenges. For one media brand, we recently combined publicly available FCC, SEC, Smart TV, search trends, survey, and credit card spending data to provide a detailed view of competitor subscriptions and consumer flows across its product sectors. For another brand, we integrated our advertising measurement data, with the company’s brand equity insights and first-party sales and promotions information to identify how their marketing drove long-term brand health and lower funnel conversions.
In retail, where competitor point-of-sale data is often restricted, companies are using AI to analyze satellite images of store parking lots to track customer traffic and predict sales trends. Retailers can also merge their own sales data with competitor location data to see how competition affects their performance at a granular level.
Generative AI is a powerful tool, but the real revolution in market research is the smart integration of diverse data sources into a broad set of AI models. Surveys will be enhanced, not replaced, and human voices amplified, not silenced. This approach ensures market researchers can deliver accurate, reliable, and ethical insights in a complex, AI-powered world.
Embrace the future of marketing research: let your data drive your AI.