Market Research Automation: Our Greatest Fear or Innovation?

By Adriana Rocha

Let’s face the reality: in a very likely future, many of the things we do today will be automated. People, from many areas and industries, are becoming very concerned about advancing automation. And indeed we should be, especially that automation, in the form of artificial intelligence, is invading many work areas, even those more intellectual than manual, and those involving decision making.

In the context of market research, increased automation is focused on operational efficiency, gaining speed and costs savings, but it limits us to thinking within the parameters of work that is being accomplished today. When we consider the quality issues the industry faces with poor online data collection, professional respondents, frauds, etc. my main concern is that speeding data collection automation will just scale the size of the problem. That could be our greatest fear!

However, if we look into advances in automation from a different perspective: what new accomplishments may market researchers reach if they had better-thinking machines to assist them? As David Autor, an economist at MIT, says: there is an immense challenge of applying machines to any tasks that call for flexibility, judgment, or common sense. Also, he states: “tasks that cannot be substituted by computerization are generally complemented by it”. Fortunately, computers aren’t very good at many sorts of things, and here are some examples where market researchers can win upon machines:

1)  Analysts – bring strengths to the table that are not about purely rational, codifiable cognition, with more big-picture thinking and a higher level of abstraction than computers can provide. Let the machine do the things that are beneath you, and take the opportunity to engage with higher-order concerns;

2)  Data Scientists –understand how software makes routine decisions so you monitor and modify its function and output. You can interfere as necessary in special cases or experiments, as well as to improve the algorithms;

3)  Story Tellers – you are better at considering the big-picture than any software. Use your intuition and creativity to tell the story behind the data;

4)  Specialists – specialize in something for which no computer program has yet been developed. People who can go deep in their particular area of expertise have more chance to win: an anthropologist, for example, has deep expertise in observing and interpreting human behavior than any computer; a good moderator will be in need to lead a group conversation, even that is held on a computer platform;

5)  Innovators – build the next generation of market research applications or smart machines. A digital innovator takes hold of new ways to use data and optimize its usage for key decision-making.

So, my conclusion is that a lot of focus on market research automation nowadays has been dedicated to data collection, and it will continue growing and improving. However, the industry should put more focus on fixing the problems with poor online data quality, before investing much in automating such processes.  On the other hand, we can see rising possibilities as we reframe the threat of data collection automation as an opportunity for expansion of the industry into the new data avenues, innovation in artificial intelligence, advanced analytics and reporting.

Hence, smart machines can be our partners and collaborators in creative problem solving. Let’s take advantage of that! 

References:

Our Automated Future (The New Yorker): http://www.newyorker.com/magazine/2016/12/19/our-automated-future

Beyond Automation (HBR):

https://hbr.org/2015/06/beyond-automation

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6 responses to “Market Research Automation: Our Greatest Fear or Innovation?

  1. Wonderful article, Adriana! I think what ties all these together is critical thinking and context thinking – about data and data collection, about insights, about implications, etc.

  2. Automation obviously allows market researchers to do more, faster and with less. However, it might get faster results and be more cost effective, but it does have its downsides….

  3. Excellent article, Adriana. The services that our company offer are highly dependent on quality data. So many clients want quick and cheap without thinking of the implications or ramifications of not knowing the source of the data and how it can impact decision-making. Much of my resistance to automation is rooted in knowing what the sample definition is and where the sample is coming from. Because that can vary so much, we often have to use different approaches or caveat results. We’re held to a very high standard on the accuracy of our analysis and that is very much contingent on the quality of the inputs – primarily data – that we have to work with. I would love to see the industry put more resources into getting the ‘front end’ of research right so that automation is much more effective on the back end.

  4. @Ekavat, thanks for your feedback. I agree 100% with you. BTW, I just returned from ESOMAR LATAM Congress and recommend anyone reading the paper “The Joy of Research” by Unilever and DeLaRiva. Here is one of my favorite statements: “The market research industry has become very effective in the last few years in connecting with consumers through digital tools, consuming less of everyone’s time. We are becoming better at it and we’re still fighting to be even more efficient, and even faster. But that comes at great cost: we try to become so fast and efficient that we forget good research needs engaged informers.”.

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