How AI and Big Qual can drive real human consumer insight

Published 10 Aug 2021 2 minute read

Market Research
Technology

If some of the news and opinion coming out of the Big Qual summit is to be believed, the gap between qualitative and quantitative research is becoming as thin as Kate Moss circa 1995. However, the real question is; when it comes to distinguishing between the two – do those who commission research projects actually care?

The answer is – probably not!

What all brands really want and need right now are contextual insights into their chosen audience. Without sounding too Hannibal Lector about it – they want to feel what it's like to be in their customer's skin and experience the highs and lows of everyday life and the multitude of decisions they need to make. The name of the game here, though, is real human insight; the kind that comes from truly understanding what people think, feel and do, but at a scale much greater than traditional qual can support.

And with the world and his wife now as keen as mustard to share their opinions in public – on social media, surveys and online groups and communities, brands need to be on board with what every potential customer is thinking and feeling, not just the few.

Big Qual drives consumer insight at scale

While qual research has always been the heartland of deep consumer understanding, Big Qual - as it has been temporarily labelled - allows organisations to get far more wide-reaching human insight by blending machine learning and AI-powered analytics of large datasets with research design and interpretation done by humans.

Where traditionally, these vast data sets were too big for the human eye to process and spot patterns in, thanks to the introduction of AI, machines can now help researchers determine signals from noise and sift through huge amounts of textual data.

And that, in turn, drives the quantifiable human insight and answers the challenging ‘Why?’ question with more confidence than just a sample of 6 or 8 people can ever do.

The rise of the machines

While robots and emotion are not traditionally two comfortable bedfellows, AI's introduction into qual research allows projects that were previously at a small size to now be driven by big data.

A question that’s pondered not only in sci-fi blockbusters, but also by big brands is: “how much can we rely on artificial intelligence when it comes to interpreting human feelings?” And the truth is that there are pros and con's on each side.

On the side of AI, things like group bias that can come from small face to face panels are removed, the statistical significance of the large sample sizes it can reach are more reliable, and patterns are easily picked up.

However, when emotions are boiled down to pure data, interpretation can be lost. The research still requires a narrative frame through which to view the results, which is why Big Qual is still entirely distinct from traditional quantitative analysis.

The reality is that banding around terms such as AI and Big Qual may, to some degree, be the emperor donning his new wardrobe. The truth is that as one of our customers, you want results and the ability to convince a Board who are more comfortable with numbers than feelings, not the buzzwords. 

Why not take a moment to browse our new site or if you have a project you wish to discuss, then drop us a line or book a discovery call, we'd love to share our insight and showcase how we've helped other clients unlock more from their big data.

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