Alex Sunnerstam, SVP, Data Partnerships attended the Stockholm Data Innovation Summit in May.

Below, Alex shares how AI can impact market research and data collection.

Alex partners with our clients on finding the best ways to integrate passive metering and behavioural data within their products and research projects. She has over 20 years’ experience in the industry including with market intelligence and data analysis business.

Attending the Stockholm Data Summit, what struck me was the range of use cases for AI and the potential business impact from agriculture to pharmaceuticals to logistics, and as someone who usually attends market research and consumer insights, it was enlightening to get out of one’s echo chamber.

I couldn’t help but think about the potential for AI, and what that means to market research? Like many industries we’re all no doubt looking at the potential threats and opportunities that such as massive, generationally-defining development could mean – is this evolution or revolution? Something to fear or embrace?

Thinking negatively, AI could allow many businesses to think that they can completely bypass traditional market research. Why ask consumers their opinion or worse, build any predictions if consumers, put it simplistically, a. are not sure of their answers or b. change their mind anyway.

It is very tempting for a corporation to think that AI might just be capable of knowing and anticipating what consumers think, want and need before the consumers do. This might be possible for some consumer-centric organisations that have a wealth of consumer data; customer data- bases, access to sales data or direct customer data to mine and work. AI will enable them to create high touch personalisation and predictions on consumer preferences and demand without having to ask the consumer. In such a scenario, traditional consumer surveys and a range of market research techniques may look outdated.

However, most organisations do not have a direct-to-consumer relationships and sophisticated data to access. The majority of corporations, especially corporations with new brands and services will still need to understand competitor, and market landscape and how consumers engage, purchase and consumer competitor products.

And while it’s true that AI will be able to do some of the very heavy lifting in the research space – processing data and archives with speed and accuracy which will outperform current processing abilities – can it really offer the evidence and predictability of consumer behaviour? That seems unlikely at this stage.

If we look back at the evolution of market research we see an industry that has developed and iterated to reflect technological advances – moving from clip-boards to online surveys, to mining whole new data-sources provided through an increasingly online world. So perhaps we can look at AI as a tool that will continue to help us in this journey of understanding and predicting consumer needs.

Like other industries, perhaps the true strength of AI will be where machine meets human – with one not replacing the other, but rather how it helps us work better, with more insight and accuracy than has been possible before.