2023 - Research needs innovation....
...that works for research practitioners, not just client and IT companies.
What will be the key trends in market research for 2023?
Often one reads agility, the use of artificial intelligence, automation - but also staffing issues. Or in the words of a report flashed in a recent Greenbook article: “tighter labor market” (Market Research Top Issues and Trends).
So: tech leading the charge for quicker, easier research in 2023 - but with a nod to the human aspect of finding and retaining researchers.
Greenbook also published a 2023 trends piece on emerging qual trends. Tech again emerged as a key driver.
UK MR agency FlexMR highlighted “video” as a great way to capture qual feedback. Clientside researcher Gary Stow from Reckitt Benckiser is quoted as saying he sees video as easier for participants than texting a response. Video also carries emotions more easily - through tone of voice, body language for example. You can read the full piece here: 3 Emerging Qualitative Trends to Watch.
No doubt true - video can be powerful.
But a couple of things aren’t mentioned in either of the above predictive snippets:
Just having lots more data means you have to find a way to turn all that data into insights. That address a business problem. Fast.
New tools (OK, video isn’t new) have to work for agencies and the people working with those innovations as well as fulfilling an (unmet) need for clients. Unless clients engage in Video DIY insight analysis, of course - likely unrealistic.
Why raise these questions? Well, staffing is a problem for many in MR. And humans matter. As the author of the first report states “what we do as market researchers is hard”.
But hopefully also fun - discovering about how people think about a category of brand can be mind-expanding, and is invariably fascinating in a way that for many staring at a spread sheet isn’t.
2023 - A CALL FOR HUMAN-CENTRED INNOVATION
Making a plea for a 2023 trend sounds weak - a bit like King Canute trying to send back incoming waves.
But the application of MR innovation is the area where real value is identified: in helping surface and tease out insights better. Not just finding new ways of generating more, mainly unstructured data. Yes, quicker if possible - but in a way that isn’t superficial or that encourages corner cutting.
Let’s imagine a project with that video output of say 30 hours of participants talking.
Perhaps in 3 markets.
Do the labour and time-saving AI tools promised by the likes of Voxpopme really deliver ? Carl Wong first came up with the approach I think a decade or so ago, so it’s hardly new - certainly time enough for it to be honed into a powerful tool.
The promise? Tagging, highlighting, instant-translations, text-underlays…..if anyone has a credible study that evaluates the total efficiency of this kind of AI supported video analysis versus a human-only or a machine-only approach, do share.
And video is just an example of tech-innovation in MR - “instant insights on tap” is often the glib promise, accompanied by a long list of blue-chip companies using the approach.
But what about agencies? We all need to be mindful of one of the trends mentioned, “the tight labour market”.
My take: in the case of video, reserachers still have to look and listen to everything to make sense of it. No short-cuts are available.
KEEP IT REAL, KEEP IT HUMAN
Take Facial recogntion software as an example. It’s controversial. There’s plenty of academic doubt on linking facial expression accurately to emotions both within and across cultures.
There are added societal concerns. You can read more here on the issues perceived as expressed by Meta (Meta/Update on Facial Recognition Software) and Microsoft. (Microsoft's Framework for Buildling AI Systems Responsibly).
Add to this: as data-capturing becomes easier, it’s tempting just to increase sample sizes so that the word “robust” can be used appropriately. But so what?
Is it really necessary to generate so much data? A lot of key insights often emerge quite quickly, and arguably from relatively small data sets - depending on challenge and category. Are we really living in an age where capturing say 98% of the insights is needed - outliers included? Or more where a pragmatic “good enough” approach delivers for a given brief? I’d say the latter.
In summary - definitely, MR needs to innovate to thrive. But with humans at the centre of NPD endeavours, throughout the insights chain or eco-system.
Research is a strenuous business - or it can be. But it’s also fun. A great career choice - for the curious amongst us.
We need to keep it that way, and ensure that not just client and tech voices are heard, but authentic practitioner experiences including honest accounts of the good and the bad, if not the ugly. After all, MR is a social science, not just the sub-segment of an IT operation with attractive financial multiples.
So my plea for 2023: let’s innovate with practitioners’ human needs in mind.
Curious, as ever, as to other’s thoughts.
(Photo by Cristian Escobar on Unsplash)