How AI is leading ‘Digital Transformation’ in Market Research

Satyakam Mohanty
Digital Transformation

Insights professionals have spent decades perfecting quantitative methods to analyze data – think survey methodologies; from clustering and factor models to predictive Bayesian analysis.

Perhaps one of the biggest impact AI has on these time-tested research methods is enabling its usage on data that is qualitative – like videos, text, audio etc.

While there have been attempts at quantifying such data in the past, the new generation of AI systems – powered by deep learning algorithms are capable of doing it at remarkably increased accuracy and speed.

Here are a few ways in which AI is revolutionizing market research:

By providing real-time analysis of opinion through social listening: Anyone who watched ITV’s live coverage on US Presidential election in 2016 might recall that the broadcaster’s AI; EagleAi, was able to predict Trump’s victory.

The telecaster’s AI tool dredged through a mountain of social media posts, photos, videos, comments, searches and press coverage in search of patterns and connections, and seemed never to harbour any serious doubts about the outcome.

AI market research tools, once set up, enrich insights by continuously aggregating data which can be accessed in real time.

Fast analysis of video, audio and text from samples: Deep Learning (DL) algorithm has emerged as the predominant method in AI today. It is used to detect objects in images, analyze sound waves to convert spoken speech to text, or process natural human language into a structured format for analysis.

Using AI tools, researchers can quickly extract and analyze information even from unstructured data.

Save time and lower cost: AI performs repetitive and manual tasks quicker than humans. By implementing an AI program, companies can cut costs by cutting the time it takes to conduct these manual research processes.

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This gives researchers the time and freedom to be more creative and thoughtful, and enables them to focus on crucial aspects such as analyzing consumer behavior and enhancing their experience.

Greater recruitment capabilities: Researchers often work with consumer panels which are typically effective at targeting consumers with general or common needs. The moment the mandate narrows to specific needs and attributes, these panels quickly show their limitations.

Accomplishing research work with a narrower criteria is often difficult or needs large amounts of additional time and budget to reach a small set of audience. AI, however can help the researcher overcome this limitation; with its ability to build rich profiles.

AI powered tools can aggregate a panel of consumers almost instantaneously and with very little time or money spent on human effort.

Guide R&D: AI-driven listening offers companies a window onto trends that indicate their customers’ real opinions and hint at their future behaviour. A great example for this would be Colgate-Palmolive in the US. The company has spoken greatly of its use of AI to guide its R&D efforts.

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Colgate used machines that helped to gather detailed consumer behaviour data that traditional research methods couldn’t find.

AI has the potential to add newer layers of insights, which will enable deep quantification of qualitative data. With AI, researchers can bring methodological rigor of quantitative methods into the world of qualitative research. The future is bright for those who can learn how to harness it.

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