In the seventh episode of Perspectives, we talk about how automation will impact the market research industry and its members.
Annie Pettit – Market Research Methodologist, AnniePettit@gmail.com, read more on her blog.
I’m not concerned with the next 12 months whatsoever. If we aren’t planning for the next five and ten years, we’re going to be in a lot of trouble. With that in mind, I’d like to consider how automation and artificial intelligence will impact me over that time frame.
The reality is that my job will change a lot. No longer will I receive a dataset, clean out poor quality data, run statistics, write a report, and prepare a presentation. Every aspect of that will be handled automatically and with artificial intelligence. I will receive a report at my desk that is perfectly written, with the perfect charts, and perfectly aligned with my clients’ needs.
So why will I still be there? I’ll be the person who points out the illogical outcomes of the data. How errors enter during the data collection process via human cognitive biases. I’ll be the person who interprets the data in an odd way that wasn’t predicted by the data but is still a plausible outcome. I’ll help clients read between the lines and use the results wisely rather than by the book – or rather, by the AI.
So how will automation and artificial intelligence impact our industry? If your business sells repetitive tasks, from survey programming to data cleaning to statistics to chart preparation and report writing, you’d better have a long-term plan. Figure out your unique method of selling WISE applications. Not just data, but wiser data and wiser charts and wiser reports. There are already hundreds of companies innovating in these areas right now and they are waiting to find their customers. I expect you don’t want to hand over your customers to them.
Excerpts from the vlog
How can we create some of the real time response time that many automated platforms promise but keep the humanity? @dbrowell
For the first time next year we’ll be looking to invest in the automation of analysis, particularly in our online communities, and over the last year we’ve been investing in Microsoft Azure technology, and we’re hoping this is gonna help us analyse vast quantities of data, not just the primary research that we collect, but also the behavioural data that our clients give to us. @andybuckers
Most of the innovations I’m finding helpful are coming from outside of the “research industry” and are coming from people who haven’t built them for research context. These advancements have caused me to lean into the strategic and frankly common sense part of my research brain. @reneemmurphy
Automation is allowing us to go through this sort of unstructured data scale, that’s just one example, but I think it’s helping us to blend quant and qual in interesting ways. @RoddyKnowles
The qualitative space doesn’t have as many automated solutions presently as the quant space does. I think part of that is because the qualitative world still wants to focus on maintaining that human connection. So you’ve got that back and forth and the relationship aspect of it. I think that carries over into the way that reporting is done in qualitative. While you can use automated tools to pull out themes you still need to have the storytelling component wove in. And you can’t get that’s not an automated things. That’s a human that needs to do that. @kerryhecht
I read a few months ago about IBM Watson. And Watson has so comprehensively mastered bankruptcy law that a major New York law firm last year laid off 50 top bankruptcy lawyers. And I think that you can, you can also see that the evidence of the impact of automation in AI in the automotive industry, which is booming but with far fewer workers than when it was on the verge of collapse back in 2009. I think, as much as we wish it weren’t so, automation and AI decreases the demand for labour. And there have been a few folks in this industry that are, have, or are arguing that automation in the M/R space will actually free up more time for researchers to be more creative and intellectually productive. I think that the likely result actually is that it will diminish the need for researchers overall. @kristinluck
My worry is that automation will form a barrier between the researcher and the data because automation is great, but is it as good as an experienced researcher extracting meaning and understanding through data. Plus I’ve yet to see a fully functioning artificial on any platform that I’ve been presented in the last few months. Sure there are platforms that can code and what-have-you, but I’m yet to see something really good that excites me enough and again I’m just worried about this barrier between the researcher and the data. @SiamackSalari
That’s where I see automation fitting in the research process, it’s ubiquitous, it’s going to be throughout, it’s already in many places. It’s going to be more and more in qualitative, it’s going to be more in video analytics, and the future is pretty bright. @winifredatwell
The more exciting area is the transformative nature that we can actually see with data automation, for example we can now put cameras onto display material and they can pick up data which then we can start to interpret through algorithms and display in real time to understand people’s emotions in relation to these. @FionaMESH
Without embracing automation, our industry is really going to decline. It is the root for us as researchers to have the room and the space to add value, and be the consultants that we want with clients. @earle_babita
We continue to be amazed at the quality of information we can get from our over one million agents as it relates to capturing data at that point of influence of using a product or a service @rickwest01
I think we’ll be seeing AI taking a much bigger role in sampling. There is a massive amount of work afoot, on being able to predict certain low responsive sectors within the sampling quotas, like young men, that type of thing. Equally, AI can then force through extra sample for those type of people. What we have to watch out for though, is in terms of river sampling, where that might actually end up skewing data quite substantially, so AI is great, but we have to judge it in market research terms. @JohnnyAlucard01
Machine learning is going to be the one that we as an industry will benefit most from @Finn01