Never the twain shall meet?

It’s a topic that keeps rearing its head, witness Riki Neill’s piece in the last In Depth, in which described how he used Chaos Theory and mathematics to make sense of Big Data and predict shopper behaviour.

Freeze frame

So since In Brief’s brief is to monitor trends, and change, we decided to ask a selection of researchers where they stood on convergence. The answers make for a fascinating snapshot of an industry in flux. Digital is, it seems, blurring the lines — at least superficially — when it comes to client interface, with quant debriefs peppered with verbatim quotes, videos and pictures. Use of the net for data collection means they are getting closer together in the online space, too. But what does this mean in real terms?

“In some ways, the pressure is on for qualitative research as an industry,” says Chris Barnham. “I can’t see qual becoming more like quant, but I can see quant becoming more like qual — without the analysis. The way forward is for qual to up its game, and re-establish its credentials.”

It’s easy to forget, though, that ‘qual’ and ‘quant’ have always been part of a spectrum of research information. Consider grounded theory, where experiments demonstrated that talking to 30 or so people will identify most of the main issues, and that thereafter researchers are in the business of attempting to measure those issues. Consider, too, the fact that 20 years ago or so quant — like qual — was carried out face to face, by interviewers in the street or going door to door.

“Personally,” says Andy Dexter, “I’ve always been of the view that all data is qualitative, and that we’re in the business of pattern recognition, not absolute accuracy (particularly true now). The difference today is that with tools such as easyaccess multivariate data reduction techniques, coupled with methods of analysing unstructured data via, for example, text analytics, ‘quant’ can genuinely be treated as ‘qual at scale’.”

At AQR’s recent conference, his session on Brexit won the award for best contribution. He had asked people to tell him in their own words what Brexit meant to them. In the safe space of an anonymous online survey, some of the responses were, in his words, ‘astonishing’. “When subjected to text analytics, we were then able to form vocabulary clusters that said more about the participants’ value systems than any attitude scale,” he says. “Admittedly, much of this convergence happens, or is facilitated, online — it’s a natural platform for this kind of convergence.”